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  Step 6: Record Data   Now that we have a place to permanently store the values coming from the EMS engine simulator, we'll write a Service to take samples and place them within the Info Table.   Part of that Service, though, will be incrementing the identifier, so we'll need to create one last Property.   Ensure that you're on the Properties and Alerts tab of EdgeThing. At the top-left, click + Add.     In the Name field of the slide-out on the right, type identifier. Change the Base Type to NUMBER. Click Persistent. Click Has Default Value. In the Has Default Value field, type 0.   At the top-right, click the "Check" button for Done. At the top, click Save.   Store the Property Values   With all the pieces in place, we can now create our Service to add entries to our Info Table Property.   At the top of EdgeThing, click Services.   At the top-left, click + Add.   On the "+ Add" drop-down, select Local (JavaScript). In the Service Info > Name field, type recordService.     Expand Me/Entities > Properties.     Click the arrow beside infoTableProperty.     Type .AddRow({ after me.infoTableProperty to being the process of calling the "AddRow()" function.     We now have called the function which will add a row of information to the Info Table Property, one entry for each column of the formatting Data Shape.   We just need to specify which values go into which column.   Add the following lines to store the individual Identifier count into the first column of the Info Table Property: identifier:me.identifier, Because we want the identifier in the stored data to increment on each run, and we want to start the count at 1 (and the Default Value is 0), add the following line to the top of the Service: me.identifier=me.identifier+1;       Add the low_grease value with the following line: low_grease:me.low_grease, Add the following lines to store the five frequency bands of the first sensor: s1_fb1:me.s1_fb1, s1_fb2:me.s1_fb2, s1_fb3:me.s1_fb3, s1_fb4:me.s1_fb4, s1_fb5:me.s1_fb5, Add the final lines to store the five frequency bands of the second sensor and close out the AddRow() function: s2_fb1:me.s2_fb1, s2_fb2:me.s2_fb2, s2_fb3:me.s2_fb3, s2_fb4:me.s2_fb4, s2_fb5:me.s2_fb5 }); You completed Service should look like the following: me.identifier=me.identifier+1; me.infoTableProperty.AddRow({ identifier:me.identifier, low_grease:me.low_grease, s1_fb1:me.s1_fb1, s1_fb2:me.s1_fb2, s1_fb3:me.s1_fb3, s1_fb4:me.s1_fb4, s1_fb5:me.s1_fb5, s2_fb1:me.s2_fb1, s2_fb2:me.s2_fb2, s2_fb3:me.s2_fb3, s2_fb4:me.s2_fb4, s2_fb5:me.s2_fb5 });     At the top, click Done. At the top, click Save.       Run the Service   With our Service completed, let's run it to store a sampling of the data coming from our EMS Engine Simulator.   Under the Execute column in the center, on the recordService row, click the "Play" icon for Execute service. At the bottom-right, click Execute.     At the bottom-right, click Done. At the top, click Properties and Alerts.   Under the Value column, on the infoTableProperty row, click the "Pencil" icon for Set value of property.   Note that the Service has captured a snap-shot of the vibration data and grease condition and permanently stored it within the Info Table Property. You now have not only an Engine Simulator that is constantly sending data from a remote EMS, but a way to permanently record data at points that you deem significant.   Feel free to return to the Service and call it several more times. Each time, the values coming from the Engine Simulator will be stored in another entry in the Info Table Property.       Step 7: Next Steps   Congratulations! You've successfully completed the Use the EMS to Create an Engine Simulator guide, and learned how to:   Modify an EMS Template Provision Thing Properties and Values from an EMS rather than Foundation Send information from an EMS to Foundation Store large amounts of data in an InfoTable Property Create a simulator for testing   The next guide in the Vehicle Predictive Pre-Failure Detection with ThingWorx Platform learning path is Engine Simulator Data Storage. Learn More We recommend the following resources to continue your learning experience: Capability Guide Build Engine Simulator Data Storage Build Implement Services, Events and Subscriptions Additional Resources If you have questions, issues, or need additional information, refer to: Resource Link Community Developer Community Forum Support Analytics Builder Help Center  

    Step 7: Access Data   Now that we have a basic display in-place, we need to access the backend data.   To do so, we'll make use of built-in Mashup Data Services.   At the top-right, ensure that the Data tab is selected.   Click the green + button.   In the Entities Filter field of the Add Data Pop-up, search for and select MDSD_Thing. In the Services Filter field, type getprop. Click the arrow beside GetProperties. Note that the GetProperties() Service has been added to the right section. Check the Execute on Load checkbox.   At the bottom-right of the pop-up, click Done. Note how the GetProperties() Mashup Data Service has been added to the top-right under the Data tab.   Bind Info Table Property   Now that we have access to the Data Service within the Mashup, we'll use it to pull backend data into the Mashup (specifically, the aggregated Info Table Property), and then bind it to the Grid Widget.   Expand the GetProperties Service.   Drag-and-drop MDSD_InfoTable_Property onto the Grid Advanced Widget.   On the Select Binding Target Pop-up, select Data.   Note how the bottom-center Connections Window indicates that the aggregated Info Table Property is now bound to the grid.   Access the Aggregation Service   Because we selected the Execute on Load option for GetProperties(), the Service will grab the information from the aggregated Info Table Property and propagate that into the Grid Advanced Widget on initially opening the Mashup in a web browser.   However, we currently have no way to call our custom aggregation Service besides diving into the backend as we did when we first created it and performed testing.   Instead, we want the Mashup itself to have the ability to call the aggregation Service.   We'll do so via the Button Widget's Clicked Event, but we first need to gain access to our custom Service in the Mashup.   In the top-right Data tab beside Things_MDSD_Thing, click the green </> button. Note that the Add Data Pop-up opens with the MDSD_Thing pre-selected.   On the left of the Add Data Pop-up, expand Select Service Category, and choose **Uncategorized**. Note our custom MDSD_Aggregation_Service.   Beside MDSD_Aggregation_Service, click the right arrow to add it to the Selected Services section. Note that we do NOT want to check "Execute on Load", because don't want the Service called upon initially opening the Mashup in a web browser.   At the bottom-right, click Done. Note the MDSD_Aggregation_Service has been added to the far-right Data tab.   Bind Button to Aggregation Service   Now that we can reference the aggregation Service in the Mashup, we'll bind it to pressing the Button Widget.   Click the Button Widget to select it.   Click the top-left of the Button Widget to reveal the Drop Down Menu.   Drag-and-drop the Clicked Event onto the MDSD_Aggregation_Service under the Data Tab.   On the bottom-right, with the MDSD_Aggregation_Service selected, drag-and-drop the MDSD_Aggregation_Service's ServiceInvokeCompleted Event onto GetProperties in the Data Tab. This causes the completion of the aggregation Service to re-call GetProperties, which updates the grid; as such, a new entry into the Info Table Property created by the custom Service will immediately show up in the Grid Widget. In the top-right, click the GetProperties Service to see all of its interactions in the bottom-center Connections window.   At the top, click Save.       Step 8: Test Application   Our MVP MRI Service Application is now complete.   Let's test it.   At the top, click View Mashup. Note the pre-existing single entry from our Service test which we executed directly from the backend.   Click Retrieve MRI Statistics.   Wait a moment and click Retrieve MRI Statistics again. Note that each click adds another entry to the Grid Widget.   Each time that you press the Button Widget, what you're really doing is calling our custom aggregation Service in the Foundation backend.   This Service then goes out and pulls in information from our various EMS-connected Edge sub-systems.   To add additional sub-systems (maybe a "friction" detection on the patient-bed indicating that it needs additional grease) all you would have to do is repeat the steps in this Learning Path, i.e. connect the additional sub-system with the EMS, add another Field Definition to the Data Shape, and modify the aggregation Service to retrieve that info and store it in the Info Table Property.   In addition, you may wish to improve the GUI. Rather than using a Positioning: Static Mashup, you could utilize a Responsive setup, sub-divide the Canvas into various sections, and then add items such as your company's logo. This would also make the GUI more friendly to different screen resolutions.   You can even add business logic to the Mashup itself. For instance, the Auto Refresh Widget (Legacy) can effectively be used as a "timer". In the same way that the Button Widget's Clicked Event calls the aggregation Service, the Auto Refresh Widget could be used to trigger the Service call at a set interval. Then, as long as the Mashup was open, the Button Widget would only be needed when you wanted an immediate status update.   For more information on implementing additional business logic, refer to the Create Custom Business Logic guide.   Or the Time Selector Widget could be used to restrict the information in the Grid Widget to only the timeframe you wanted to investigate.       Step 9: Next Steps   Congratulations! You've successfully completed the Medical Data Storage and Display guide, and learned how to:   Create a Data Shape and Info Table Property to store Medical Data Create a Service to combine data from multiple Edge devices into a single, logical Thing Create a Mashup to view and retrieve Medical data   This is the last guide in the Medical Device Service learning path.   Learn More   We recommend the following resources to continue your learning experience:    Capability     Guide Build Methods for Data Storage Experience Create Your Application UI   Additional Resources   If you have questions, issues, or need additional information, refer to:    Resource       Link Community Developer Community Forum Support ThingWorx Help Center  

    Step 5: Properties   In the Delivery Truck application, there are three Delivery Truck Things. Each Thing has a number of Properties based on its location, speed, and its deliveries carried out. In this design, when a delivery is made or the truck is no longer moving, the Property values are updated. The deliveryTruck.c helper C file is based on the DeliveryTruck Entities in the Composer. After calling the construct function, there are a number of steps necessary to get going. For the SimpleThing application, there are a number of methods for creating Properties, Events, Services, and Data Shapes for ease of use.   Properties can be created in the client or just registered and utilized. In the SimpleThingClient application, Properties are created. In the DeliveryTruckClient application, Properties are bound to their ThingWorx Platform counterpart. Two types of structures are used by the C SDK to define Properties when it is seen fit to do so and can be found in [C SDK HOME DIR]/src/api/twProperties.h:    Name                   Structure            Description Property Definitions twPropertyDef Describes the basic information for the Properties that will be available to ThingWorx and can be added to a client application. Property Values twProperty Associates the Property name with a value, timestamp, and quality.   NOTE: The C SDK provides a number of Macros located in [C SDK HOME DIR]/src/api/twMacros.h. This guide will use these Macros while providing input on the use of pure function calls.   The Macro example below can be found in the main source file for the SimpleThingClient application and the accompanying helper file simple_thing.c.   TW_PROPERTY("TempProperty", "Description for TempProperty", TW_NUMBER); TW_ADD_BOOLEAN_ASPECT("TempProperty", TW_ASPECT_ISREADONLY,TRUE); TW_ADD_BOOLEAN_ASPECT("TempProperty", TW_ASPECT_ISLOGGED,TRUE);   NOTE: The list of aspect configurations can be seen in [C SDK HOME DIR]/src/api/twConstants.h. Property values can be set with defaults using the aspects setting. Setting a default value in the client will affect the Property in the ThingWorx platform after binding. It will not set a local value in the client application.   For the DeliveryTruckClient, we registered, read, and update Properties without using the Property definitions. Which method of using Properties is based on the application being built.   NOTE: Updating Properties in the ThingWorx Platform while the application is running, will update the values in the client application. To update the values in the platform to match, end the Property read section of your property handler function with a function to set the platform value.   The createTruckThing function for the deliveryTruck.c source code takes a truck name as a parameter and is used to register the Properties, functions, and handlers for each truck.   The updateTruckThing function for the deliveryTruck.c source code takes a truck name as a parameter and is used to either initialize a struct for DeliveryTruck Properties, or simulate a truck stop Event, update Properties, then fire an Event for the ThingWorx platform.   Connecting properties to be used on the platform is as easy as registering the property and optionally adding aspects. The following shows the properties that correlate to those in the DeliveryTruck entities in the Composer. To do this within the code, you would use the TW_PROPERTY macro as shown in the deliveryTruck.c. This macro must be proceeded by either TW_DECLARE_SHAPE, TW_DECLARE_TEMPLATE or TW_MAKE_THING because these macros declare variables used by the TW_PROPERTY that follow them.   //TW_PROPERTY(propertyName,description,type) TW_PROPERTY(PROPERTY_NAME_DRIVER, NO_DESCRIPTION, TW_STRING); TW_PROPERTY(PROPERTY_NAME_DELIVERIES_LEFT, NO_DESCRIPTION, TW_NUMBER); TW_PROPERTY(PROPERTY_NAME_TOTAL_DELIVERIES, NO_DESCRIPTION, TW_NUMBER); TW_PROPERTY(PROPERTY_NAME_DELIVERIES_MADE, NO_DESCRIPTION, TW_NUMBER); TW_PROPERTY(PROPERTY_NAME_LOCATION, NO_DESCRIPTION, TW_LOCATION); TW_PROPERTY(PROPERTY_NAME_SPEED, NO_DESCRIPTION, "TW_NUMBER);   Read Properties   Reading Properties from a ThingWorx platform Thing or the returned Properties of a Service can be done using the TW_GET_PROPERTY macro. Examples of its use can be seen in all of the provided applications. An example can be seen below:   int flow = TW_GET_PROPERTY(thingName, "TotalFlow").number; int pressue = TW_GET_PROPERTY(thingName, "Pressure").number; twLocation location = TW_GET_PROPERTY(thingName, "Location").location; int temperature = TW_GET_PROPERTY(thingName, "Temperature").number;   Write Properties   Writing Properties to a ThingWorx platform Thing from a variable storing is value uses a similarly named method. Using the TW_SET_PROPERTY macro will be able to send values to the platform. Examples of its use can be seen in all of the provided applications. An example is shown below:   TW_SET_PROPERTY(thingName, "TotalFlow", TW_MAKE_NUMBER(rand() / (RAND_MAX / 10.0))); TW_SET_PROPERTY(thingName, "Pressure", TW_MAKE_NUMBER(18 + rand() / (RAND_MAX / 5.0))); TW_SET_PROPERTY(thingName, "Location", TW_MAKE_LOC(gpsroute[location_step].latitude,gpsroute[location_step].longitude,gpsroute[location_step].elevation));   This macro utilizes the twApi_PushSubscribedProperties function call to push all property updates to the server. This can be seen in the updateTruckThing function in deliveryTruck.c.   Property Change Listeners   Using the Observer pattern, you can take advantage of the Property change listener functionality. With this pattern, you create functions that will be notified when a value of a Property has been changed (whether on the server or locally by your program when the TW_SET_PROPERTY macro is called).   Add a Property Change Listener   In order to add a Property change listener, call the twExt_AddPropertyChangeListener function using the:   Name of the Thing (entityName) Property this listener should watch Function that will be called when the property has changed   void simplePropertyObserver(const char * entityName, const char * thingName,twPrimitive* newValue){ printf("My Value has changed\n"); } void test_simplePropertyChangeListener() { { TW_MAKE_THING("observedThing",TW_THING_TEMPLATE_GENERIC); TW_PROPERTY("TotalFlow", TW_NO_DESCRIPTION, TW_NUMBER); } twExt_AddPropertyChangeListener("observedThing",TW_OBSERVE_ALL_PROPERTIES,simplePropertyObserver); TW_SET_PROPERTY("observedThing","TotalFlow",TW_MAKE_NUMBER(50)); } NOTE: Setting the propertyName parameter to NULL or TW_OBSERVE_ALL_PROPERTIES, the function specified by the propertyChangeListenerFunction parameter will be used for ALL properties.   Remove a Property Change Listener   In order to release the memory for your application when done with utilizing listeners for the Property, call the twExt_RemovePropertyChangeListener function.   void simplePropertyObserver(const char * entityName, const char * thingName,twPrimitive* newValue){ printf("My Value has changed\n"); } twExt_RemovePropertyChangeListener(simplePropertyObserver);       Step 6: Data Shapes   Data Shapes are an important part of creating/firing Events and also invoking Services.   Define With Macros   In order to define a Data Shape using a macro, use TW_MAKE_DATASHAPE.   NOTE: The macros are all defined in the twMacros.h header file.   TW_MAKE_DATASHAPE("SteamSensorReadingShape", TW_DS_ENTRY("ActivationTime", TW_NO_DESCRIPTION ,TW_DATETIME), TW_DS_ENTRY("SensorName", TW_NO_DESCRIPTION ,TW_NUMBER), TW_DS_ENTRY("Temperature", TW_NO_DESCRIPTION ,TW_NUMBER), TW_DS_ENTRY("Pressure", TW_NO_DESCRIPTION ,TW_NUMBER), TW_DS_ENTRY("FaultStatus", TW_NO_DESCRIPTION ,TW_BOOLEAN), TW_DS_ENTRY("InletValve", TW_NO_DESCRIPTION ,TW_BOOLEAN), TW_DS_ENTRY("TemperatureLimit", TW_NO_DESCRIPTION ,TW_NUMBER), TW_DS_ENTRY("TotalFlow", TW_NO_DESCRIPTION ,TW_INTEGER) );   Define Without Macros   In order to define a Data Shape without using a macro, use the twDataShape_CreateFromEntries function. In the example below, we are creating a Data Shape called SteamSensorReadings that has two numbers as Field Definitions.   twDataShape * ds = twDataShape_Create(twDataShapeEntry_Create("a",NULL,TW_NUMBER)); twDataShape_AddEntry(ds, twDataShapeEntry_Create("b",NULL,TW_NUMBER)); /* Name the DataShape for the SteamSensorReadings service output */ twDataShape_SetName(ds, "SteamSensorReadings");     Step 7: Events and Services   Events and Services provide useful functionality. Events are a good way to make a Service be asynchronous. You can call a Service, let it return, then your Entity can subscribe to your Event and not keep the original Service function waiting. Events are also a good way to allow the platform to respond to data when it arrives on the edge device without it having to poll the edge device for updates.   Fire Events   To fire an Event you first need to register the Event and load it with the necessary fields for the Data Shape of that Event using the twApi_RegisterEvent function. Afterwards, you would send a request to the ThingWorx server with the collected values using the twApi_FireEvent function. An example is as follows:   twDataShape * ds = twDataShape_Create(twDataShapeEntry_Create("message", NULL,TW_STRING)); /* Event datashapes require a name */ twDataShape_SetName(ds, "SteamSensorFault"); /* Register the service */ twApi_RegisterEvent(TW_THING, thingName, "SteamSensorFault", "Steam sensor event", ds); …. struct { char FaultStatus; double Temperature; double TemperatureLimit; } properties; …. properties. TemperatureLimit = rand() + RAND_MAX/5.0; properties.Temperature = rand() + RAND_MAX/5.0; properties.FaultStatus = FALSE; if (properties.Temperature > properties.TemperatureLimit && properties.FaultStatus == FALSE) { twInfoTable * faultData = 0; char msg[140]; properties.FaultStatus = TRUE; sprintf(msg,"%s Temperature %2f exceeds threshold of %2f", thingName, properties.Temperature, properties.TemperatureLimit); faultData = twInfoTable_CreateFromString("message", msg, TRUE); twApi_FireEvent(TW_THING, thingName, "SteamSensorFault", faultData, -1, TRUE); twInfoTable_Delete(faultData); }   Invoke Services   In order to invoke a Service, you will use the twApi_InvokeService function. The full documentation for this function can be found in [C SDK HOME DIR]/src/api/twApi.h. Refer to the table below for additional information.    Parameter         Type                  Description entityType Input The type of Entity that the service belongs to. Enumeration values can be found in twDefinitions.h. entityName Input The name of the Entity that the service belongs to. serviceName Input The name of the Service to execute. params Input A pointer to an Info Table containing the parameters to be passed into the Service. The calling function will retain ownership of this pointer and is responsible for cleaning up the memory after the call is complete. result Input/Output A pointer to a twInfoTable pointer. In a successful request, this parameter will end up with a valid pointer to a twInfoTable that is the result of the Service invocation. The caller is responsible for deleting the returned primitive using twInfoTable_Delete. It is possible for the returned pointer to be NULL if an error occurred or no data is returned. timeout Input The time (in milliseconds) to wait for a response from the server. A value of -1 uses the DEFAULT_MESSAGE_TIMEOUT as defined in twDefaultSettings.h. forceConnect Input A Boolean value. If TRUE and the API is in the disconnected state of the duty cycle, the API will force a reconnect to send the request.   See below for an example in which the Copy service from the FileTransferSubsystem is called:   twDataShape * ds = NULL; twInfoTable * it = NULL; twInfoTableRow * row = NULL; twInfoTable * transferInfo = NULL; int res = 0; const char * sourceRepo = "SimpleThing_1"; const char * sourcePath = "tw/hotfolder/"; const char * sourceFile = "source.txt"; const char * targetRepo = "SystemRepository"; const char * targetPath = "/"; const char * targetFile = "source.txt"; uint32_t timeout = 60; char asynch = TRUE; char * tid = 0; /* Create an infotable out of the parameters */ ds = twDataShape_Create(twDataShapeEntry_Create("sourceRepo", NULL, TW_STRING)); res = twDataShape_AddEntry(ds, twDataShapeEntry_Create("sourcePath", NULL, TW_STRING)); res |= twDataShape_AddEntry(ds, twDataShapeEntry_Create("sourceFile", NULL, TW_STRING)); res |= twDataShape_AddEntry(ds, twDataShapeEntry_Create("targetRepo", NULL, TW_STRING)); res |= twDataShape_AddEntry(ds, twDataShapeEntry_Create("targetPath", NULL, TW_STRING)); res |= twDataShape_AddEntry(ds, twDataShapeEntry_Create("targetFile", NULL, TW_STRING)); res |= twDataShape_AddEntry(ds, twDataShapeEntry_Create("async", NULL, TW_BOOLEAN)); res |= twDataShape_AddEntry(ds, twDataShapeEntry_Create("timeout", NULL, TW_INTEGER)); it = twInfoTable_Create(ds); row = twInfoTableRow_Create(twPrimitive_CreateFromString(sourceRepo, TRUE)); res = twInfoTableRow_AddEntry(row, twPrimitive_CreateFromString(sourcePath, TRUE)); res |= twInfoTableRow_AddEntry(row, twPrimitive_CreateFromString(sourceFile, TRUE)); res |= twInfoTableRow_AddEntry(row, twPrimitive_CreateFromString(targetRepo, TRUE)); res |= twInfoTableRow_AddEntry(row, twPrimitive_CreateFromString(targetPath, TRUE)); res |= twInfoTableRow_AddEntry(row, twPrimitive_CreateFromString(targetFile, TRUE)); res |= twInfoTableRow_AddEntry(row, twPrimitive_CreateFromBoolean(asynch)); res |= twInfoTableRow_AddEntry(row, twPrimitive_CreateFromInteger(timeout)); twInfoTable_AddRow(it,row); /* Make the service call */ res = twApi_InvokeService(TW_SUBSYSTEM, "FileTransferSubsystem", "Copy", it, &transferInfo, timeout ? (timeout * 2): -1, FALSE); twInfoTable_Delete(it); /* Grab the tid */ res = twInfoTable_GetString(transferInfo,"transferId",0, &tid);   Bind Event Handling   You may want to track exactly when your edge Entities are successfully bound to or unbound from the server. The reason for this is that only bound items should be interacting with the ThingWorx Platform and the ThingWorx Platform will never send any requests targeted at an Entity that is not bound. A simple example that only logs the bound Thing can be seen below. After creating this function, it will need to be registered using the twApi_RegisterBindEventCallback function before the connection is made.   void BindEventHandler(char * entityName, char isBound, void * userdata) { if (isBound) TW_LOG(TW_FORCE,"BindEventHandler: Entity %s was Bound", entityName); else TW_LOG(TW_FORCE,"BindEventHandler: Entity %s was Unbound", entityName); } …. twApi_RegisterBindEventCallback(thingName, BindEventHandler, NULL);   OnAuthenticated Event Handling   You may also want to know exactly when your Edge device has successfully authenticated and made a connection to the ThingWorx platform. Like the bind Event handling, this function will need to be made and registered. To register this handler, use the twApi_RegisterOnAuthenticatedCallback function before the connection is made. This handler form can also be used to do a delay bind for all Things.   void AuthEventHandler(char * credType, char * credValue, void * userdata) { if (!credType || !credValue) return; TW_LOG(TW_FORCE,"AuthEventHandler: Authenticated using %s = %s. Userdata = 0x%x", credType, credValue, userdata); /* Could do a delayed bind here */ /* twApi_BindThing(thingName); */ } … twApi_RegisterOnAuthenticatedCallback(AuthEventHandler, NULL);     Click here to view Part 3 of this guide.

  Step 6: Create Event Router   What do you do when a user can perform multiple events in which data is generated, and want those outputs to go through the same exact process? An Events Router Function is your solution. The Events Router Function allows for multiple data sources to be funneled to one location. Let's create a simple example in our MyFunctionsMashup Mashup. In this Mashup, we'll add two Text Field Widgets and a Label Widget. The two Text Field Widgets will take user input and then an Events Router will send the output to the Label. Let's start!   Open the MyFunctionsMashup Mashup to the Design tab. Click on the Widgets tab. Type in the Filter text box for Text Field.   Drag and drop TWO (2) Text Field Widgets to the Mashup Canvas. Type in the Filter text box for Label.   Drag and drop ONE (1) Label Widget to the Mashup Canvas. We now have all the Widgets we need for this example. Let's get started on the Events Router Function. Click the + button in the Functions panel. Select Events Router in the dropdown.   Set the Name to routeUserInput.   Click Next. Set the Inputs field to 2.   Click Done. We have our Events Router setup. Now, we'll bind our new items together. Click the Bind (arrows) button on the routeUserInput Events Router.   Click the down arrow next to Input1. Select Add Source.   In the Widgets tab, scroll to the bottom and select Text Property of the first of the two recent Text Fields we created (it should be third to last).   Click Next. Click the down arrow next to Input2. Select Add Source.   In the Widgets tab, scroll to the bottom and select Text Property of the second of the two recent Text Fields we created (it should be second to last).   Click Next. Click the down arrow next to Output. Select Add Target.   In the Widgets tab, scroll to the bottom and select LabelText Property of the recent Label we created (it should be last).   Click Next. Click Done. Click Save for the Mashup. You have just created an Events Router that will update a Label based on the typed input from two Text Fields. View your Mashup and play around with the bottom two text boxes. For a completed example, download and unzip, then import the attached FunctionsGuide_Entities.zip.     Step 7: Next Steps   Congratulations! You've successfully completed the Explore UI Functions guide, and learned best practices for building a complex Mashup that navigations, multiple data inputs, confirmations, and all working together effectively for an enhanced user experience.   Learn More   We recommend the following resources to continue your learning experience:    Capability    Guide Experience Object-Oriented UI Design Tips   Additional Resources   If you have questions, issues, or need additional information, refer to:    Resource       Link Community Developer Community Forum Support Mashup Builder Support Help Center

  Step 7: Real World Model   We’ll now rerun model creation with the Real World data.   Even though Signals and Profiles are possibly telling us that only Sensor 1 is needed, the first Model you’ll create will contain all the data, while the second Model will exclude Sensor 2. We’ll then compare the Models to see which one is going to work the best for predicting engine failures.   On the left, click Analytics Builder > Models. Click New….   In the Model Name field, enter vibration_model. In the Dataset field, select vibration_dataset.   Click Submit. After ~60 seconds, the Model Status will change to COMPLETED. Select the model that was created in the previous step, i.e. vibration_model. Click View… to open the Model Information page. Note that your model may differ slightly from the picture below, as the automatically-withheld "test" data is randomly chosen.       Unlike our simulated dataset, this real-world data is not perfect. However, it’s still pretty good, and is much more representative of what a real-world scenario would indicate.   The True Positive Rate shown on the Receiver Operating Characteristic (ROC) chart are much higher than the False Positives.   The curve is relatively high and to the left, which indicates a high accuracy level.   You may also click on the Confusion Matrix tab in the top-left, which will show you the number of True Positive and True Negatives in comparison to False Positives and False Negatives.     NOTE: The number of correct predictions is much higher than the number of incorrect predictions.   As such, we now know that our Sensors have a relatively good chance at predicting an impending failure by detecting low grease conditions before they cause catastrophic engine failure.   Refined Model   We can now compare this first Model that includes both Sensors to a Model using only Sensor 1, since we suspect that Sensor 2 may not be necessary to achieve our goal. On the left, click Analytics Builder > Models. Click New…. In the Model Name field, enter vibration_model_s1_only. In the Dataset field, select vibration_dataset.   On the right beside Excluded Fields from Model, click the Excluded Fields button.   Select s2_fb1 through s2_fb5.   While all the s2 values are selected, click the green "right-arrow", i.e. > button, in the middle.   At the bottom-left, click Save.   Click Submit. After ~60 seconds, the Model State will change to COMPLETED. With vibration_model_s1_only selected, click View….     The ROC chart is comparable to the original model (including Sensor 2).   Likewise, the Confusion Matrix (on the other tab) indicates a good ratio of correct predictions versus incorrect predictions.     NOTE: These Models may vary slightly from your own final scores, as what data is used for the prediction versus for evaluation is random.   ThingWorx Analytics’s Models have indicated that you are likely to receive roughly the same accuracy of predicting a low-grease condition whether you use one sensor or two!   If we can get an accurate early-warning of the low grease condition with just one sensor, it then becomes a business decision as to whether the extra cost of Sensor 2 is necessary.     Step 8: Next Steps   Congratulations! You've successfully completed the Build an Engine Analytical Model guide, and learned how to:   Load an IoT dataset Generate machine learning predictions Evaluate the analytics output to gain insight   The next guide in the Vehicle Predictive Pre-Failure Detection with ThingWorx Platform learning path is Manage an Engine Analytical Model.   Learn More   We recommend the following resources to continue your learning experience:   Capability Guide Analyze Operationalize an Analytics Model Build Implement Services, Events, and Subscriptions Additional Resources   If you have questions, issues, or need additional information, refer to:   Resource Link Community Developer Community Forum Support Analytics Builder Help Center

  Step 4: Simulated Model   Models are primarily used by Analytics Manager (which will be discussed in the next guide), but they can still be used to estimate the accuracy of predictions.   When Models are calculated, they inherently withhold a certain amount of data (~20%). The prediction model is then run against the withheld data. This provides a form of "accuracy measure".   The withheld-data is selected randomly, so you'll actually get a slightly different model and accuracy measure each time that you create a Model versus the same dataset.   On the left, click Analytics Builder > Models.   Click New….   In the Model Name field, enter simulated_model. In the Dataset field, select simulated_dataset.   Click Submit. After ~60 seconds, the Model Status will change to COMPLETED.     Select the model that was created in the previous step, i.e. simulated_model. Click View… to open the Model Information page.   As with Signals and Profiles, our Model is once again "too good". In fact, it's perfect.   The expected "Precision" is 1.0, i.e. 100%. The True vs False Positive rate shown in the graph goes straight up to the top immediately.   While you want a graph that is "high and left", you're very unlikely to ever see real-world scenarios such as shown here.   Still, you've been able to progress the process of using Foundation (and now Analytics) to build an analytical model of MotorCo's prototype engine.   What needs to happen now is to receive real world data from your R&D engineers.     Step 5: Upload Real World Data   In your process of using the EMS Engine Simulator, the idea has always been to get a headstart on the engine developers.   At some point, they would wire sensors into the EMS and start providing real world data.   In our scenario, that has now happened. Real world data is being fed from the EMS to Foundation, Foundation is collecting that data in an Info Table Property, and you've even exported the data as a .csv. file.   This new dataset is over periods of both good and bad grease conditions. The engineers monitoring the process can flip a sensor switch connected to the EMS to log the current grease situation as either good or bad at the same time that the vibration sensors are taking readings.   We will now load this real world dataset into Analytics in the same manner that we did earlier with the simulated dataset.   Download the attached analytics_vibration.zip file to your computer. Unzip the analytics_vibration.zip file to access the vibration_data_and_header.csv and vibration_metadata.json files. On the left, click Analytics Builder > Data. Under Datasets, click New....   In the Dataset Name field, enter vibration_dataset. In the File Containing Dataset Data section, search for and select vibration_data_and_header.csv. In the File Containing Dataset Field Configuration section, search for and select vibration_metadata.json.   Click Submit.     Step 6: Real World Signals and Profiles   Now that the real-world vibration data has been uploaded, we’ll re-run Signals and Profiles just as we did before.   Hopefully, we’ll start seeing some patterns.   On the left, click Analytics Builder > Signals. At the top, click New….   In the Signal Name field, enter vibration_signal. In the Dataset field, select vibration_dataset.   Click Submit. Wait ~30 seconds for Signal State to change to COMPLETED     The results show that the five Frequency Bands for Sensor 1 are the most highly correlated with determining our goal of detecting a low grease condition.   For Sensor 2, only bands one and four seem to be related, while bands two, three, and five are hardly relevant at all.   This is a very different result than our earlier simulated data. Instead, it looks like it’s possible that the vibration-frequencies getting pickup up by our first sensor are explicitly more important.   Profiles   We’ll now re-run Profiles with our real-world dataset. On the left, click Analytics Builder > Profiles. Click New….   In the Profile Name field, enter vibration_profile. In the Dataset field, select vibration_dataset.   Click Submit. After ~30 seconds, the Signal State will change to COMPLETED.     The results show several Profiles (combinations of data) that appear to be statistically significant.   Only the first few Profiles, however, have a significant percentage of the total number of records. The later Profiles can largely be ignored.   Of those first Profiles, both Frequency Bands from Sensor 1 and Sensor 2 appear.   But in combination with the result from Signals (where Sensor 1 was always more important), this could possibly indicate that Sensor 1 is still the most important overall.   In other words, since Sensor 1 is statistically significant both by itself and in combination (but Sensor 2 is only significant in combination  with Sensor 1), then Sensor 2 may not be necessary.     Click here to view Part 3 of this guide.

This video continues Module 3: Data Profiling of the ThingWorx Analytics Training videos. It describes metadata, and how it is used to ensure that your data is handled appropriately when running Signals, Profiles, Training, Scoring, and other jobs inside ThingWorx Analytics.

  Enhance your Engine Failure-Prediction GUI.     GUIDE CONCEPT   This guide will use ThingWorx Foundation’s Mashup Builder to create a more advanced Graphical User Interface (GUI) than the one we originally created to display results from Analytics Manager’s engine-failure predictions.   Following the steps in this guide, you will learn how to utilize Widgets and backend data to more completely visualize customer failure conditions.       YOU'LL LEARN HOW TO   Create a Mashup with a Header Divide your Mashup into Sub-sections Use a Contained Mashup to reuse development Store historical data in a Value Steam Display historical data in a Time Series Chart Show spreadsheet data via a Grid Widget Tie Mashup controls into the ThingWorx backend   NOTE: The estimated time to complete all parts of this guide is 60 minutes.     Step 1: Scenario   In this guide, we’re taking our previous MotorCo Minimum Viable Product (MVP) Mashup and expanding it.   Our original Mashup showed the results from ThingWorx Analytics as it determined whether or not a low-grease condition was currently present.   The goal of this guide is to create an Enhanced GUI to visualize those predicted “low grease” conditions in a more complete manner.     GUI-creation to visualize analytical model deployment can be extremely helpful for the automative segment in particular. For instance, each car that comes off the factory line could have an EMS constantly sending data from which an analytical model could automatically detect engine trouble.   This could enable your company to offer an engine monitoring subscription service to your customers.   This guide will show you how to visualize the results of an engine analytic model for a smart, connected products play.     Step 2: Create Mashup   Just like in the last guide, we're now going to create a Mashup to visualize ThingWorx Analytics results.   This one is simply going to be more complicated to include additional functionality.   But before we can start designing our GUI, we must first instantiate a Mashup onto which we can place our Widgets.       1. In ThingWorx Foundation, click Browse > Visualization > Mashups.         2. Click + New.       3. On the New Mashup pop-up under Responsive Templates, click Header Only.       4. Click OK.       5. In the Name field, type EEFV_Mashup.       6. If Project is not already set, search for and select PTCDefaultProject.       7. At the top, click Save.       8. At the top, click Design.         Step 3: Set Layout   Now that we’re in Mashup Builder, you can see the separate top-section of the central Canvas area created by our selection of “Header Only” on the New Mashup pop-up.   Unlike the original Mashup where we used Static Positioning, most of this Mashup will continue to use Responsive so that it can grow and shrink as resolution changes on various viewing devices.   To add multiple Responsive Widgets to a Responsive Positioning Mashup, though, you need to create some additional sub-sections. We’ll do so now.       1. In the top-left of Mashup Builder, click the Layout tab.       2. Click the main, bottom section of the Canvas, i.e. the non-header section, to select it.       3. On the Layout tab, click Add Top.       4. With the top-half of the original bottom section still selected, click Add Left.       5. Click in the bottom section to select the bottom-half of the original container.       6. Click Add Left.       7. At the top, click Save.      You now have a Responsive Positioning Mashup with five (5) sub-sections, i.e. :   Header Top-left Top-Right Bottom-left Bottom-right       Step 4: Adjust Header    In this step, we'll outfit the Header sub-section with a company name and logo.       1. Select the top Header section and ensure that you're still on the Layout tab in the top-left.         2. Change the Positioning to Static.       3. In the top-left, select the Widgets tab.       4. Drag-and-drop an Image Widget onto the Header section.       5. Expand the size of the Image Widget by dragging the corners.       6. Drag-and-drop a Label Widget onto the Header section.       7. Expand the size of the Label Widget.       8. With the Label Widget still selected, change the LabelText Property (in the bottom-left) to MotorCo, and hit the keyboard Tab key to lock-in your modification.         9. In the bottom-left, change to the Style Properties tab.       10. Expand Base > Label, and change font-size to 72px.       11. At the top, click Save.   Upload Media Image   We want to set the earlier Image Widget to the company logo.   To do so, we need to upload it to Foundation by creating a Media Entity.       1. Click Browse > Visualization > Media.       2. Click + New.       3. In the Name field, type EEFV_Logo.       4. If Project is not already set, search for and select PTCDefaultProject.       5. Right-click and "Save as" to download motorco-logo.jpg.       6. Under Image, click Change.       7. Navigate to and select the motorco-logo.jpg file you just downloaded.       8. Click Open.       9. At the top, click Save.   Change Image to Logo   Now that we have the company logo stored within ThingWorx, we can update the Image Widget to reference it.       1. Return to EEFV_Mashup.       2. Click the Image Widget to select it, and ensure that the bottom-left Properties tab is active.         3. Scroll down in the Properties until you find SourceURL.         4. In the Search Media field, type eefv.         5. Select EEFV_Logo.         6. Click Save.     Change Background Color   Finally, we want to change the background color of the Header.       1. In the top-left, select the Explorer tab. Note that the Explorer tab may be in the top-left drop-down if you're using a lower-resolution screen.         2. Select the Header itself.         3. In the bottom-left, select the Style Properties tab and expand Base > Container.         4. Beside background, click the white square to open a color-selector.       5. Select a color you desire.         6. Click Select.         7. Click Save.     Click here to view Part 2 of this guide.

  Display project burn up/down via a convenient Mashup Widget.   GUIDE CONCEPT   Long term projects need to be managed. As a project is scoped, requirements get defined and delivery-timeframes are estimated. As work is done, requirements are completed.   One way to track this project progress is with a Waterfall Chart.   This guide will show you how to utilize a Waterfall Chart Widget to easily display the project workflow.        YOU'LL LEARN HOW TO   Create a Data Shape Create a Thing Create an Info Table Property Populate an Info Table with appropriate data for a Waterfall Chart Create a Mashup Utilize a Waterfall Chart to display project progress   NOTE: This guide's content aligns with ThingWorx 9.3. The estimated time to complete this guide is 30 minutes     Step 1: Create Data Shape   In this scenario, we'll store the Waterfall Chart's data in a Property type called an Info Table.   An Info Table is a spreadsheet-like Property, but in order to define the columns of the table, we first have to define a Data Shape. We'll do that in this step.   In the left-side navigation, click Browse > Modeling > Data Shapes.   At the top, click + New.   In the Name field, type TPWC_DataShape. If Project is not already set, search for and select PTCDefaultProject .   At the top, click Field Definitions.   At the top-left, click + Add.   On the right-side slide-out, in the Name field, type month. Note that you want to leave "Base Type" as the default of "STRING". Check Is Primary Key.   Click the "check with a plus" button for Done and Add.   In the Name field, type amount. Change Base Type, to NUMBER.   Click the "check" button for Done.   At the top, click Save .     Step 2: Create Thing   Now that we have our Data Shape, we can create a Thing to document the project progress over time.   As already mentioned, we'll use an Info Table Property, formatted by the previously-created Data Shape, to do so.   Click Browse > Modeling > Things.   Click + New.   In the Name field, type TPWC_Thing. If Project is not already set, search for and select PTCDefaultProject. In the Base Thing Template field, search for and select GenericThing. At the top, click Save.   Add Info Table Property Now that we have our Thing instantiated, we want to add an Info Table Property. At the top, click Properties and Alerts.   Click + Add.   On the right-side slide-out, in the Name field, type InfoTable_Property. Change Base Type to INFOTABLE. In the Data Shape field, search for and select TPWC_DataShape. Note that the Data Shape field will not appear until you set Base Type to INFOTABLE. Check Persistent.   At the top-right, click the "check" button for Done. At the top, click Save.   Set Value of Property Now that we have a place in which to store spreadsheet-like values, we'll do so manually for testing.  On the InfoTable_Property row, under the Value column, click the "pencil" icon for Set value of property.   On the pop-up, click + Add.   Enter the following values in each field as per the table below: Field Name Value month January amount 380   Click Add.   Repeat Steps 2-4 multiples times until all of the below values have been entered. Note that amount should be left blank for both Mid-Term and Total. Note that you may enter fewer than all the values listed below if so desired, though your final Waterfall Chart will not match the following screenshots. month amount February 85 March 50 April 1000 May -300 June 0 Mid-Term   July 30 August -655 September -100 October -250 November 350 December -100 Total     On the pop-up, click Save.   At the top, click Save.   Step 3: Create Mashup   Now that we have our data in-place for testing (and could be connected to automated systems after we finish testing), we need to visualize the data.   As mentioned, we'll use a Waterfall Chart Widget, but first, we need to create a Mashup into which we can place the Widget.   Click Browse > Visualization > Mashups.   Click + New.   Leave the defaults and click OK.   In the Name field, type TPWC_Mashup. If Project is not already set, search for and select PTCDefaultProject. At the top, click Save.   At the top, click Design.   At the top-left, click the Widgets tab.   Drag-and-drop a Waterfall Chart Widget onto the central Canvas.   At the top, click Save.     Click here to view Part 2 of this guide.

    Keys to utilizing the C and Java SDK for ThingWorx application development   GUIDE CONCEPT   This project will introduce to coding examples utilized for SDKs to be used with Java and C. You can also use the Java SDK for Android development.   Following the steps in this guide, you will be better prepared to creating your own application using one of our SDKs.   We will teach you how to handle Properties, Entities, data, make Service calls and creating Remote Services.     YOU'LL LEARN HOW TO   How to create, update, and retrieve Property values Utilize Data Shapes for handling data and triggering Events Construct Info Tables for Services and retrieving data after Service calls Add key features of an edge/remote application   NOTE: The estimated time to complete this guide is 30 minutes.     Step 1: Connection Process   he ThingWorx SDKs follows a three-step process when connecting to the ThingWorx Platform.   NOTE: In this context, Client refers to the application and the SDK running on the device and Server refers to the ThingWorx Platform.   Websocket   The client opens a Websocket to the server using the host and port. With the ThingWorx platform you can connect via HTTP and HTTPS with access to Services, Properties, Events, Entities, and Resources.   Authentication   In order to connect and access information from the server, you must utilize an authorization method. Application Keys provide a secure method for the SDK to log into the platform and perform transactions. The client sends an authentication message to the server containing an Application Key.   Binding   Binding is an optional step in the client connection process. The SDK client allows one or more VirtualThings to be associated with a Websocket connection, using their names or identifiers. Binding a property in your ThingWorx application to that of your source code provides several benefits, including being able to update properties while offline.     Click here to view Part 2 of this guide.

  Send voice and text messages with Twilio.   GUIDE CONCEPT   This project will demonstrate how you can create applications that provide information to users, even when they are away from their computer. Users who are on the go can benefit from your application by receiving text and voice messages.   Following the steps in this guide, you will learn how to configure and use the Twilio Widget and explore it’s ability to send messages.   We will teach you how data can be used to send pertinent information to any cell phone.   YOU'LL LEARN HOW TO   Download and import the Twilio Widget extension Create a Thing using the Twilio Thing Template Configure the Twilio Thing to use your Twilio account Send text messages using a Service   NOTE:  The estimated time to complete this guide is 30 minutes.     Step 1: Install Twilio Extension   Download the Twilio Extension from IQNOX.com. Note:  IQNOX is a PTC Partner and will be maintaining and supporting specific extensions going forward.  It will be necessary to create an account on the IQNOX website, but the ThingWorx extensions are free. In the lower-left side of Composer, click Import/Export, then Import.   In the Import From File pop-up, under Import Option select Extension from the drop-down, then click Browse. Navigate to the .zip file you downloaded.   Click Import in the Import From File pop-up, then click Close after file is successfully imported.     Step 2: Create Twilio Thing   In this step, you will create a Thing that represents a connection with the Twilio service.   Start on the Browse, folder icon tab on the far left of ThingWorx Composer.  Under the Modeling tab, hover over Things then click the + button. Type twilio-connector in the Name field.   NOTE: This name, with matching capitalization, is required for the example code which will be entered in a later step. If Project is not already set, click the + in the Project text box and select the PTCDefaultProject. In the Base Thing Template text box, click the + and select Twilio.     Click Save.     Step 3: Configure Twilio Thing   Now that we have created a Thing to represent the Twilio connection, we will configure it with your Twilio account credentials.   When the Twilio Extension is installed, it does not include the Twilio account credentials required to send messages.   You will need Twilio account credentials to complete this step. If you do not already have a Twilio account, you can click on this link to create a Twilio account.   Open the twilio-connection Thing if it is not already open. Click on the Configuration tab. Click the pencil icon next to the authToken field.   Copy your AUTH TOKEN from your Twilio account dashboard.   Paste your AUTH TOKEN into the New Password and Confirm Password fields under authToken.   Click the pencil icon next to the accountSID field. Copy your ACCOUNT SID from your Twilio account dashboard, and paste it into the New Password and Confirm Password fields under accountSID. Follow the steps in your Twilio account dashboard to get a trial phone number.   Copy your PHONE NUMBER from your Twilio account dashboard, and paste it into the callerID field.   Click Save.     Step 4: Test Twilio Thing   Now that we have created a Thing to represent the Twilio connection and configured it with Twilio account credentials, we will confirm that everything is working.   Click the Services tab at the top of the twilio-connector Thing.     Click the link to the SendSMSMessage Service in the Services Name column. Enter a phone number in the to field. Enter a test message in the text field.   Click the Execute button to send the SMS message. The service should execute without any errors within a couple of seconds and the phone number will receive your message. Click Close to end testing the service.     Step 5: Sample Alerting App   At this point, you have created and tested a Thing that can send text messages. This step will demonstrate sending a message when a Property Value is out of the desired range.   Import Simulated Freezer Thing   Download and unzip the attached sample Things_freezer.zip. In Composer, click the Import/Export icon at the lower-left of the page.   Click Import. Leave all default values and click Browse to select the Things_freezer.twx file that you just downloaded. Click Open, then Import. When you see the success message, click Close.   Explore Imported Entities   Navigate to the freezer Thing by using the search bar at the top of the screen. Click the Subscriptions tab.   Click reportFreezer under Name. Open the Subscription Info tab. Select the Enabled checkbox.   Click Done then Save to save any changes.   Verify Data Simulation   Open the freezer Thing and click Properties and Alerts tab. Click the Set value in the alertedPhone Property row, in the Value column.   Enter a phone number to receive the SMS alert, then click the Check icon above where you entered the phone number. Click the pencil icon in the temp Property row, in the Value column. Enter a value for the temp property that is greater than 30, and click the Check icon. In a couple seconds, the phone number you entered will receive an alert that includes the value you entered.      Step 6: Next Steps   Congratulations!   In this guide, you learned how to:   Create a Thing using the Twilio Thing Template Configure the Twilio Thing to use your Twilio account Send text messages using a Service   Additional Resources   If you have questions, issues, or need additional information, refer to:   Resource Link Community Developer Community Forum Support Twilio Extension Help Center

  Step 5: Format Timed Values   At the top, click the Services section of scts_thing.   In the Ihnerited Services section, you will see the built-in services of the Statistical Calculation Thing Shape. These services can perform a variety of analytical calculations.   Timed Values Service   The Statistical Calculation Thing Shape can only perform analytics operations on time-series datasets. However, accessing a time-series Value Stream can have a performance hit on the system.   Instead, a Property with an Info Table using a timestamp/value Data Shape is used as the universal input to each built-in service of the Statistical Calculation Thing Shape.   For efficiency, we only reference the Value Stream once to create a formatted timedValues that is used as an input to all other service calls.   At the top, click Services.   Click + Add.   In the Name field, enter timed_values_service. In the Javascript field, copy and past the following code: me.timed_values = me.QueryTimedValuesForProperty({ propertyName: "numbers", maxItems: 10, startTime: me.start_time, endTime: me.end_time });   At the bottom, click Save and Execute.   Click Done, and return to Properties and Alerts. On the timed_values property row, click the pencil icon for Set value of property.   In the pop-up, note that there are now seven entries - each with the 1, 5, 9, 5, 9, 1, and 9 values and the timestamps when you entered them.   In the pop-up, click Cancel. If needed, in the top-right, click the icon to close the slide-out.   Step 6: Calculation Services   Now that the numbers, start_time, end_time, and timed_values service inputs have been set, you can use the built-in Services of the Statistical Calculation Thing Shape to perform a variety of analytics calculations.   Mean Service   First, you will utilize the built-in CalculateMeanValue service.   The dataset is the following: 1, 5, 9, 5, 9, 1, 9.   As such, the mean should be (1+5+9+5+9+1+9)/7 = 39/7 = 5.571...   Return to the Services section. At the top, click + Add. In the Name field, enter mean_service. In the Javascript code section, copy and paste the following: me.mean_result = me.CalculateMeanValue({ timedValues: me.timed_values }); At the top, click Save and Continue.   At the bottom, click Execute. Click Done, then return to the Properties and Alerts section. Note that the mean_result property now has the value 5.571....     Median Service   Next, you will utilize the built-in CalculateMedianValue service.   With our dataset having 5 as the middle value, that should be the result.   Return to the Services section. At the top, click + Add. In the Name field, enter median_service. In the Javascript code section, copy and paste the following: me.median_result = me.CalculateMedianValue({ timedValues: me.timed_values }); At the top, click Save and Continue. At the bottom, click Execute. Click Done, and return to the Properties and Alerts section. Note that the median_result Property now has the value 5.     Mode Service   You will now utilize the built-in CalculateModeValue service.   With the dataset having 9 as the most common value, that should be the result.   Return to the Services section. At the top, click + Add. In the Name field, enter mode_service. In the Javascript code section, copy and paste the following: me.mode_result = me.CalculateModeValue({ timedValues: me.timed_values }); At the top, click Save and Continue.   At the bottom, click Execute. Click Done, and return to the Properties and Alerts section. On the mode_result row and under the Value column, click the "pencil" icon for Set value of property.   In the popup, note that the mode_result Property now has the value 9.   Click Cancel to close the popup. If necessary, at the top-right, click the button to close the slide-out.   Standard Deviation Service   Lastly, you will utilize the built-in CalculateStandardDeviationValue service.   There are multiple free Standard Deviation calculators to check the answer.   Accordingly, the Standard Deviation should be 3.59894...   Return to the Service section. At the top, click + Add. In the Name field, enter standarddev_service. In the Javascript code section, copy and paste the following: me.standarddev_result = me.CalculateStandardDeviationValue({ timedValues: me.timed_values }); At the top, click Save and Continue.   At the bottom, click Execute. Click Done, and return to the Properties and Alerts section. Note that the standarddev_result property now has the value 3.59894...       Step 7: Other Options   The Mean, Median, Mode, and Standard Deviation services you have completed are just a sampling of what the Statistical Calculation Thing Shape offers.   Below is a table of additional built-in services:   Calculation Service Name Description Binned Data Distribution for Bin Size CalculateBinnedDataDistributionForBinSize Calculate the binned distribution of data points based on the desired bin size. Binned Data Distribution for Number of Bins CalculateBinnedDataDistributionForNumberOfBins Calculate the binned distribution of data points based on the desired number of bins. Confidence Interval Values CalculateConfidenceIntervalValues Confidence Interval Values Based on a specified confidence interval percentage, calculate the minimum, median, and maximum interval values. Five Number Property Values CalculateFiveNumberPropertyValues Calculate the five number values: minimum, lower quartile, median, upper quartile, and maximum. Fourier Transform CalculateFourierTransform Calculate the results of running the fast Fourier transform on the specified values. Maximum Value CalculateMaximumValue Calculate the maximum property value in the provided infotable. Minimum Value CalculateMinimumValue Calculate the minimum property value in the provided infotable. Sampling Frequency Values CalculateSamplingFrequencyValues Calculate the sampling frequency values: minimum, median, and maximum.     Step 8: Next Steps   Congratulations!   In this guide, you have learned how to:   Create a Value Stream and Data Shape Create a Thing with the Statistical Calculation Thing Shape Modify a property to record values to the Value Stream Utilize various built-in services for analytical calculations   Learn More   We recommend the following resources to continue your learning experience:   Capability Guide Build Build a Predictive Analytics Model Build Operationalize an Analytics Model   Additional Resources   If you have questions, issues, or need additional information, refer to:   Resource Link Community Developer Community Forum Support Descriptive Analytics Help Center

   

  Learn how to create systems to handle logistics and production distribution   GUIDE CONCEPT   This project will introduce complex aspects of the ThingWorx Composer and solution building.   Following the steps in this guide, you will develop your own IoT application or get a jump start in how to utilize ThingWorx for your needs.   We will teach you how to create a focused rules engine or service level logic to be used with the ThingWorx Platform.     YOU'LL LEARN HOW TO   Create automated logistical processes Use Services, Alerts, and Subscriptions to handle processes without human interaction Integrating complex logic with straight forward step by step systems   NOTE: This guide's content aligns with ThingWorx 9.3. The estimated time to complete All parts of this guide is 60 minutes.      Step 1: Examples and Strategy   This guide builds on the knowledge gained in Factory Line Automation.   Download FoodIndustry.zip attached to this guide and extract/import the contents.   For the completed example, download the automated_food_industry.zip, also attached here. This download provides three Users and a Security Group. Please watch your count for Users or the import could fail.   In this tutorial we continue with our real-world scenario for the Fizos food company. We already have our factory data, and automated cooking processed for our sausage product lines. Now, let's see how we can use the data model we built before into making a smarter system of deliveries. We will take into consideration the locations of our factories, the vehicles we have available, our customers (stores and individuals), and see how much we can automate.   Setting Up Orders   One important part of being in business is having a product that people or companies want to buy. You'll need a way to track these sales and we're going to start with doing just that. Let's create our order shapes and tables.   In the ThingWorx Composer, click the + New in the top left of the screen.     Select Data Shape in the dropdown.     In the name field, enter Fizos.Orders.DataShape and select a Project (ie, PTCDefaultProject). All of our orders will be based off this Data Shape.     Click Save then Edit to store all changes now. Add the list of properties below: Name Base Type Aspects Description ID Integer 0 minimum, primary key, default 0 Row identifier CustomerId Integer N/A String used as unique identifer across multiple platforms Type String N/A Type of customer (individual or another company) Factors Tag Data Tag This will hold the different type of data points or tags that will help to analyze a customer's order Products Infotable Data Shape: Fizos.DataShapes.Products List of orders TotalPrice Number Minimum 0 Price of the order Status String N/A The current order status (ie, processed, shipped, completed, etc) Completed Boolean N/A Whether the order has been completed   The Properties for the Fizos.Orders.DataShape Data Shape are as follows:   6. In the ThingWorx Composer, click the + New in the top left of the screen.   7. Select Data Table in the dropdown and select Data Table in the prompt.   8. In the name field, enter Fizos.Orders.DataTable. Our differing types of customers will fall under this template. 9. For the Data Shape field, select Fizos.Orders.DataShape and select a Project (ie, PTCDefaultProject).     10. Click Save then Edit to store all changes now. 11. This Entity will be used to house our data and provide assistance with our analytics.   We now have our model of orders ready to be stored. Of course, our orders are simplified. We can add much more to get them rolling, but the most important aspect right now is our Factors field. While we know a ton of information about customers, we can also analyze what kind of products they're buying and their ordering habits.     Step 2: Expanding Customer Models    Let's start with our customers. We created the data shape for customers before when we decided to put them in data tables. This time, we'll add some customers, but also expand on our modeling of what a customer entails. In this step, as with all the steps in this learning path, you can go as granular as you like. If you'd like to make 100 data tags, then it helps with understanding your customer, but it might be too much based on your goals. Remember, more data means more processing of that data.   Creating Customer Data Tags   These data tags will help us decide priority, relationships, and much more.   In the ThingWorx Composer, click the + New in the top left of the screen.     Select Data Tag in the dropdown.     In the name field, enter Fizos.CustomerTags and select a Project (ie, PTCDefaultProject). Check the Dynamic checkbox. This allows for new vocabulary terms to be created during runtime.   Click on the Vocabulary Terms tab, and add the following terms and then add as many more as you see fit: Name  Store  Individual  Office  Company  FirstTime  Repeat  Partner  LongTerm  ShortTerm  Old  MiddleAged  Young  Loyal We just added a number of data tags based on customer type, age, times the customer has bought from us, etc. This will help us with characterizing and modeling our customers. We'll also cheat a bit and use these data tags to help with deliveries. If you're a partment brand, we might work faster to send goods. For example, the code below returns the list of orders that were made by partners. We can add this as a service to our Fizos.Logistics template.   var index; var customerId; var partnerObj = {}; var query = { "filters": { "type": "EQ", "fieldName": "Completed", "value": false } }; var orders = Things["Fizos.Orders.DataTable"].QueryDataTableEntries({ query: query }); var customers = Things["Fizos.Customers.DataTable"].GetDataTableEntries(); var result = Resources["InfoTableFunctions"].CreateInfoTableFromDataShape({ infoTableName : "InfoTable", dataShapeName : "Fizos.Orders.DataShape" }); var partners = Resources["InfoTableFunctions"].TagFilter({ inclusive: true, fieldName: "Factors", t: customers, tags: "Fizos.CustomerTags:Partner" }); for(index = 0; index < partners.rows.length; index++) { customerId = partners.rows[index].ID; partnerObj[customerId] = true; } for(index = 0; index < orders.rows.length; index++) { customerId = orders.rows[index].CustomerId; if(partnerObj[customerId] === true) { var newEntry = new Object(); newEntry.ID = orders.rows[index].ID; newEntry.CustomerId = orders.rows[index].CustomerId; newEntry.Type = orders.rows[index].Type; newEntry.Products = orders.rows[index].Products; newEntry.Factors = orders.rows[index].Factors; newEntry.TotalPrice = orders.rows[index].TotalPrice; result.AddRow(newEntry); } } This code will retrieve all orders that are not in a completed state. It will then figure out which orders are for partners and return those orders. You can see in this simple example how Data Tags can be used.     Click here to view Part 2 of this guide.

  Step 5: Widget Properties   You can configure Properties to change the style of the map as well as specify a custom image to use for map markers. Other Properties allow two linear paths and polynomial regions to also be displayed on the map Widget with optional tooltip data.   Bindable   Name Type  Default Direction  Description Data Infotable None Input Source for the data that is displayed as discrete markers LocationField MenuName None Input Field that contains Location type data to plot markers MarkerField MenuName None Input Field that contains data of type Image used to plot markers ShowMarkerTooltip Boolean True Input Hovering over map markers will display a tooltip when set to true ToolTipField1 thru 4 MenuName None Input Optional field displayed in tooltip when the user hovers over a map marker ToolTipLabel1 thru 4 String None Input Optional label for tooltip data RouteData Infotable None Input Source for the data that is displayed as a connected route RouteLocationField MenuName None Input Field that contains Location type data to plot connected route line ShowRoute Boolean False Input Show route data on map when set to true PlannedRouteData Infotable None Input Source for the data that is displayed as a second connected route PlannedRouteLocationField MenuName None Input Field that contains Location type data to plot a second connected route line ShowPlannedRoute Boolean False Input Show planned route data on map when set to true RegionData Infotable None Input Source for the data that is displayed as a region RegionLocationData Infotable None Input Region location data source RegionLocationsField MenuName None Input Field which will provide location table information for region RegionLayerField MenuName None Input Field that contains Numeric data used for region layer number ShowRegions Boolean False Input Show region data on map when set to true ShowRegionTooltips Boolean True Input Hovering over region will display a tooltip when set to true RegionToolTipField1 thru 4 MenuName None Input Optional field displayed in tooltip when the user hovers over a region RegionToolTipLael1 thru 4 String None Input Optional label for region tooltip data RegionFillOpacity Number 1 Input Opacity of region fill color from 0 being transparent to 1 being opaque SelectedLocation Location None Input/Output The currently selected location CurrentZoom Number 8 Output The currently displayed zoom level ( 1 - 15 ) Zoom Number 8 Input Number used to set the zoom level ( 1 - 15 ) ShowMarkers Boolean True Input Shows map markers if set to true ShowPathMarkers Boolean True Input Shows map markers if set to true ShowTraffic Boolean False Input Shows traffic data color overlay on map if set to true NEBoundary Location None Output The northeast boundary location NWBoundary Location None Output The northwest boundary location SEBoundary Location None Output The southeast boundary location NWBoundary Location None Output The southwest boundary location Visible Boolean True Input Widget is visible if set to true     Static   Name Type  Default Description DisplayName String None Name used for widget in user facing interactions Description String None Description used for widget in user facing interactions MapType Roads/Satellite/Hybrid/Terrain Roads The type of map content displayed MapSkin Normal/Blue/Grey Normal Options for styling maps monochromatically AutoZoomBehavior Data change/Initial Data only Data Change Controls when map will automatically zoom to show all markers ClusterLocations Boolean False Combines multiple location markers that are near one another into a single marker if true MultiSelect Boolean False Enable multiple marker selection   Widget Events   DoubleClicked- Triggered when user double clicks on the Google Map. Changed- Triggered when the data for this widget is modified. BoundsChanged- Triggered when the bounding box of the displayed map changes.     Step 6: Next Steps   If you have questions, issues, or need additional information, refer to:   Resource     Link Community Developer Community Forum Support Google Map Widget Help Center Free Google Maps Widget Extension IQNOX  

    Step 5: Create InfoTable   Now that we have connected values coming from our EMS engine simulator, we want a method of permanent storage whenever we feel it's appropriate to take a sample.   From repeated sampling, we'll be able to build up a historical record usable for both manual inspection, as well as automatic analysis via ThingWorx Analytics (though ThingWorx Analytics is beyond the scope of this guide).   To hold these records, we'll use an Info Table Property.   But any time that you create an Info Table, you first need a Data Shape to format the columns.   Click Browse > MODELING > Data Shapes.     At the top-left, click + New.   In the Name field, type esimDataShape.     If Project is not already set, search for and select PTCDefaultProject. At the top, click Field Definitions.     We now want to add a separate Field Definition for each entry of our engine simulator data, i.e. low_grease, s1_fb1 through s1_fb5, and s2_fb1 through s2_fb5.   In addition, we'll add an additional field named identifier which simply keeps a rolling count of the current log entry number.   Click + Add.     In the Name field on the right slide-out, type identifier Change the Base Type to NUMBER. Check Is Primary Key   At the top-right, click the "Check with a +" button for Done and Add.     Repeatedly add additional definitions as per the chart below: Note that you will NOT check the "Is Primary Key" box, as you only need one, i.e. identifier. Name Base type low_grease NUMBER s1_fb1 NUMBER s1_fb2 NUMBER s1_fb3 NUMBER s1_fb4 NUMBER s1_fb5 NUMBER s2_fb1 NUMBER s2_fb2 NUMBER s2_fb3 NUMBER s2_fb4 NUMBER Create one additional entry for s2_fb5 and NUMBER, but click the "Check" button for DONE. At the top, click Save.     Create Info Table   Now that we have a Data Shape we can add an Info Table Property to EdgeThing. Return to the Properties and Alerts tab of EdgeThing.   At the top-left, click + Add.   In the Name field of the slide-out on the right, type infoTableProperty.   Change the Base Type to INFOTABLE.   In the new Data Shape field, search for and select esimDataShape.   Check the Persistent checkbox.   At the top-right, click the "Check" button for Done. At the top, click Save.     Click here for Part 4 of this guide.

U Term Definition user An account that can be used to access ThingWorx (design time and/or run time). user group A collection of users to provide a common level of security-access. Allows you to categorize users of the ThingWorx system. User groups can contain users and groups. All permission settings and overrides are cumulative. The ThingWorx default security policy is restrictive. When you create a new group or user, the account will not have any rights in ThingWorx until you assign them. user management subsystem Subsystem that manages session and password hash settings. See Subsystem.   V Term Definition value stream processing subsystem Subsystem that manages value stream storage and retrieval. See Subsystem. value stream A storage table for time-series information about a Thing's property values. Querying a Value Stream returns the value of the specified property. virtual Thing A modeled Thing defined in Edge that is represented as a remote Thing in the ThingWorx Platform. visibility A simple form of access control. If an entity is visible to members of an organizational unit, those members have access to the entity, and the underlying granular security model determines what interaction members of that organization unit have with a specific asset. Visibility can be set at the collection level, the individual entity level, or at the visibility level of the Thing Template instance. vocabulary A collection of terms used to create tags.   W Term Definition WebSocket-based Edge MicroServer (WS EMS) Allows edge devices or data stores to connect to the ThingWorx Platform through the internet or a firewall using the AlwaysOn™ binary protocol. WebSocket communications subsystem Subsystem that handles core WebSocket communications. See Subsystem. WebSocket execution processing subsystem Subsystem that handles WebSocket execution processing. See Subsystem. widget The components placed on a Mashup such as grids, charts, text boxes, buttons, and navigation links. Anything that is visible or clickable is a widget. wiki A type of Widget that mimics the functionality of a 'collaborative website', and allows collaborative editing of its content and structure by its users. Wikis may have posts added by both human users and the system itself.

    Watch a video tutorial on utilizing the Mashup Builder to create a User Interface (UI) for your IoT application.   Guide Concept   This project will introduce the ThingWorx Mashup Builder through the use of an instructional video. Following the steps in this video-guide, you will learn how to use this tool to create a Graphical User Interface (GUI) for your IoT Application. We will teach you how to rapidly create and update a Mashup, which is a custom visualization built to display data from devices according to your application's business and technical requirements.     You'll learn how to   Create new Mashups Choose a Static or Responsive layout Add Widgets to your Mashup Bind data Services to Widgets in your Mashup Create a functional GUI with applied usage of Widgets and Services   NOTE: The estimated time to complete this guide is 30 minutes       Step 1: Video   Click the link below to enjoy the video. You may set the video to full screen by clicking the button in the bottom-right.   If you're following along within your own ThingWorx environment, you may wish to pre-download and extract the attached MBQS_Entities.zip file. It will be used in the later half of the video as a backend data simulator.   Create Your Application UI - Video Guide     Step 2: Next Steps   Congratulations! You've successfully completed the Video Guide - Create Your Application UI, and learned how to:   Create new Mashups Choose a Static or Responsive layout Add Widgets to your Mashup Bind data Services to Widgets in your Mashup Create a functional GUI with applied usage of Widgets and Services   Learn More   We recommend the following resources to continue your learning experience:   Capability Guide Build Data Model Introduction Experience Object-Oriented UI Design Tips   Additional Resources   If you have questions, issues, or need additional information, refer to:   Resource Link Community Developer Community Forum Support Mashup Builder Support Help Center

    Step 2: Java Properties (cont.)   Annotation @ThingworxPropertyDefinitions(properties = { @ThingworxPropertyDefinition(name = "Temperature", description = "Current Temperature", baseType = "NUMBER", category = "Status", aspects = { "isReadOnly:true" }), @ThingworxPropertyDefinition(name = "Pressure", description = "Current Pressure", baseType = "NUMBER", category = "Status", aspects = { "isReadOnly:true" }), @ThingworxPropertyDefinition(name = "FaultStatus", description = "Fault status", baseType = "BOOLEAN", category = "Faults", aspects = { "isReadOnly:true" }), @ThingworxPropertyDefinition(name = "InletValve", description = "Inlet valve state", baseType = "BOOLEAN", category = "Status", aspects = { "isReadOnly:true" }), @ThingworxPropertyDefinition(name = "TemperatureLimit", description = "Temperature fault limit", baseType = "NUMBER", category = "Faults", aspects = { "isReadOnly:false" }), @ThingworxPropertyDefinition(name = "TotalFlow", description = "Total flow", baseType = "NUMBER", category = "Aggregates", aspects = { "isReadOnly:true" }), })   NOTE: The call to VirtualThing.initializeFromAnnotations is necessary if there are properties, services, and events that are annotated.   Code //Create the property definition with name, description, and baseType PropertyDefinition property1 = new PropertyDefinition(property, "Description for Property1", BaseTypes.BOOLEAN); //Create an aspect collection to hold all of the different aspects AspectCollection aspects = new AspectCollection(); //Add the dataChangeType aspect aspects.put(Aspects.ASPECT_DATACHANGETYPE, new StringPrimitive(DataChangeType.NEVER.name())); //Add the dataChangeThreshold aspect aspects.put(Aspects.ASPECT_DATACHANGETHRESHOLD, new NumberPrimitive(0.0)); //Add the cacheTime aspect aspects.put(Aspects.ASPECT_CACHETIME, new IntegerPrimitive(0)); //Add the isPersistent aspect aspects.put(Aspects.ASPECT_ISPERSISTENT, new BooleanPrimitive(false)); //Add the isReadOnly aspect aspects.put(Aspects.ASPECT_ISREADONLY, new BooleanPrimitive(false)); //Add the pushType aspect aspects.put("pushType", new StringPrimitive(DataChangeType.NEVER.name())); //Add the defaultValue aspect aspects.put(Aspects.ASPECT_DEFAULTVALUE, new BooleanPrimitive(true)); //Set the aspects of the property definition property1.setAspects(aspects); //Add the property definition to the Virtual Thing this.defineProperty(property1);   Update Properties   Property values can be updated using the provided Macros or using the API directly.   The VirtualThing.setPropertyVTQ and VirtualThing.setProperty methods are used to update properties connected to the ThingWorx Platform. It is often easiest to use the setProperty method because it allows the usage of values outside of IPrimitiveType. Using these methods will fire a property changed event and also look to add the update to the pending list of changes to the Platform based on your DataChangeType aspect used for the property. An example of how to use VirtualThing.setProperty can be seen below: double temperature = 400 + 40 * Math.random(); super.setProperty("Temperature", temperature);   NOTE: setPropertyVTQ and setProperty are both methods inside of the VirtualThing class. All objects you would like to have represented in the ThingWorx Platform as an Entity, must extend the VirtualThing class.   When finished with updating all property values, use the VirtualThing.updateSubscribedProperties method to send the queue of changes to the Platform. Property value updates will NOT be sent to the platform if this method is not called. An example can be seen below:   super.updateSubscribedProperties(15000);   Retrieve Properties   Property values can be retrieved using the provided Macros or using the API directly.   The VirtualThing.getProperty and VirtualThing.getCurrentPropertyValue methods are used to retrieve properties connected to the ThingWorx Platform. The VirtualThing.getProperties returns a PropertyCollection which provides a collection type behavior for all properties initialized within your implementation. An example of how to use VirtualThing.getProperty can be seen below:   double temperatureLimit = (Double) getProperty("TemperatureLimit").getValue().getValue();   NOTE: getProperty and getCurrentPropertyValue are both methods inside of the VirtualThing class. All objects you would like to have represented in the ThingWorx Platform as an Entity, must extend the VirtualThing class.   Synchronize Updates   The VirtualThing.synchronizeState method is called when a connect or reconnect occurs. If property values are not synced with the ThingWorx Platform on a regular basis, this method should be overridden with a call to sync properties. An example of this is shown below: public void synchronizeState() { super.synchronizeState(); super.syncProperties(); }   Scan Cycles The VirtualThing.processScanRequest method should be overridden and used to perform the tasks that should occur during a scan cycle. A scan cycle could be considered a reoccurring period in which a task is performed. This should be called and performed after a connection is made and while the application is still connected to the ThingWorx Platform. An example is as follows: while (!client.isShutdown()) { if (client.isConnected()) { for (VirtualThing thing : client.getThings().values()) { try { thing.processScanRequest(); } catch (Exception exception) { System.out.println("Error Processing Scan Request for [" + thing.getName() + "] : " + exception.getMessage()); } } } Thread.sleep(1000); }       Step 3: Java - Data Shapes   DataShapes are used for Events, Services, and InfoTables. In order to create a DataShape, you will use the FieldDefinitionCollection class with a FieldDefinition object to set each aspect and field type for the DataShape. The VirtualThing.defineDataShapeDefinition method adds the recently created definition to the Entities list of DataShapes. If the DataShape is located on the ThingWorx Platform, utilize the ConnectedThingClient.getDataShapeDefinition method in order to retrieve it. An example is shown below of how to create a DataShape and store it to the list of available DataShapes: // Data Shape definition that is used by the delivery stop event // The event only has one field, the message FieldDefinitionCollection fields = new FieldDefinitionCollection(); fields.addFieldDefinition(new FieldDefinition(ACTIV_TIME_FIELD, BaseTypes.DATETIME)); fields.addFieldDefinition(new FieldDefinition(DRIVER_NAME_FIELD, BaseTypes.STRING)); fields.addFieldDefinition(new FieldDefinition(TRUCK_NAME_FIELD, BaseTypes.BOOLEAN)); fields.addFieldDefinition(new FieldDefinition(TOTAL_DELIVERIES_FIELD, BaseTypes.NUMBER)); fields.addFieldDefinition(new FieldDefinition(REMAIN_DELIVERIES_FIELD, BaseTypes.NUMBER)); fields.addFieldDefinition(new FieldDefinition(LOCATION_FIELD, BaseTypes.LOCATION)); defineDataShapeDefinition("DeliveryTruckShape", fields);       Step 4: Java - Info Tables   Infotables are used for storing and retrieving data from service calls.   The provided InfoTable object uses a DataShapeDefinition object to describe the name, base type, and additional information about each field within the table.   The InfoTable class is a collection of ValueCollection entries for each row based on the DataShapeDefinition. When reading values from an InfoTable or loading an InfoTable with data, you will need to use the ValueCollection class.   Create and Load   The code below shows how to utilize these classes in order to create and add data to an InfoTable: DataShapeDefinition dsd = (DataShapeDefinition) this.getDataShapeDefinitions().get("SteamSensorReadings"); InfoTable table = new InfoTable(dsd); ValueCollection entry = new ValueCollection(); DateTime now = DateTime.now(); try { // entry 1 entry.clear(); entry.SetStringValue(SENSOR_NAME_FIELD, "Sensor Alpha"); entry.SetDateTimeValue(ACTIV_TIME_FIELD, now.plusDays(1)); entry.SetNumberValue(TEMPERATURE_FIELD, 50); entry.SetNumberValue(PRESSURE_FIELD, 15); entry.SetBooleanValue(FAULT_STATUS_FIELD, false); entry.SetBooleanValue(INLET_VALVE_FIELD, true); entry.SetNumberValue(TEMPERATURE_LIMIT_FIELD, 150); entry.SetNumberValue(TOTAL_FLOW_FIELD, 87); table.addRow(entry.clone()); // entry 2 entry.clear(); entry.SetStringValue(SENSOR_NAME_FIELD, "Sensor Beta"); entry.SetDateTimeValue(ACTIV_TIME_FIELD, now.plusDays(2)); entry.SetNumberValue(TEMPERATURE_FIELD, 60); entry.SetNumberValue(PRESSURE_FIELD, 25); entry.SetBooleanValue(FAULT_STATUS_FIELD, true); entry.SetBooleanValue(INLET_VALVE_FIELD, true); entry.SetNumberValue(TEMPERATURE_LIMIT_FIELD, 150); entry.SetNumberValue(TOTAL_FLOW_FIELD, 77); table.addRow(entry.clone()); } catch (Exception e) { e.printStackTrace(); }   Read   This code shows how to read a value from an InfoTable. InfoTable result = client.readProperty(ThingworxEntityTypes.Things, "SteamSensor", "name", 10000); String name = result.getFirstRow().getStringValue("name");   The example highlighted below showcases one way to get a property reading from a Thing in the ThingWorx Platform. InfoTable result = client.readProperty(ThingworxEntityTypes.Things, "SteamSensor", "name", 10000); ValueCollection entry = result.getFirstRow(); String name = entry.getStringValue("name");     Click here to view Part 4 of this guide.  

    Use the Pareto Chart Widget to visualize how issues compound to cause problems.   GUIDE CONCEPT   The Pareto Chart Widget is a useful method of displaying aggregate information.  In particular, it is often used to display multiple issues and how they combine to form an overall, larger problem.    This can be helpful when trying to determine "easy wins" by pointing out where your efforts will have the greatest impact.       YOU'LL LEARN HOW TO   Create a Data Shape Create a Thing Create an Info Table Property Populate an Info Table with appropriate data for a Pareto Chart Create a Mashup Utilize a Pareto Chart to display issue-aggregation   NOTE: This guide's content aligns with ThingWorx 9.3. The estimated time to complete this guide is 30 minutes       Step 1: Scenario   In this guide, we'll assume a scenario where a factory is being automated using ThingWorx Foundation. In particular, this factory has some known issues with a robot arm that performs welding at a point along a conveyor belt.    When this welding robot has these issues, the factory line has to come to a complete halt while maintenance is performed on it.   Management has decided that these slow-downs are costing enough money that the robot arm needs some extra attention, up to and including modification to help alleviate these maintenance stops.    However, they're not sure what to tackle first. Every issues leads to a slow down, but some happen more frequently than others.    After talking with maintenance, four primary issues are identified, i.e.   Excess temperature on the welding end has caused some welds to fail due to simply burning through the material. Some of the joints need regular lubrication, preventing the arm from getting to the correct location in time as the part moves down the conveyor belt. The welding filler-material sometimes runs out, causing a stop while more is reloaded. The welding shielding gas sometimes runs out, causing a stop while more is reloaded.   Your task, then, is to start counting the number of times each of these failures occur. In addition, you need to create a small GUI which displays both how often these errors occur, and how they contribute to the overall downtime.    To accomplish this, you'll use a Pareto Chart Widget.     Step 2: Create Data Shape   In this scenario, we'll store the Pareto Chart's data in a Property type called an Info Table.   An Info Table is a spreadsheet-like Property, but in order to define the columns of the table, we first have to define a Data Shape. We'll do that in this step.   In the left-side navigation, click Browse > Modeling > Data Shapes. At the top, click + New. In the Name field, type TIPC_DataShape. If Project is not already set, search for and select PTCDefaultProject. At the top, click Field Definitions. At the top-left, click + Add. On the right-side slide-out, in the Name field, type month. Note that you want to leave "Base Type" as the default of "STRING". Check Is Primary Key. Click the "check with a plus" button for Done and Add. Add each of the following Field Definitions, entering the Name and selecting the Base Type from the drop-down as described in the table: Note that you will NOT enable "Is Primary Key" on any other Field Definitions, as you only need one Primary Key. Note that you will simply click the "check" button for Done after the last entry . Name Base Type  excess_temperature NUMBER  need_lubricant NUMBER  low_filler NUMBER  low_gas NUMBER At the top, click Save.   Step 3: Create Thing   Now that we have our Data Shape, we can create a Thing to hold the collected counts of various issues.   As already mentioned, we'll use an Info Table Property, formatted by the previously-created Data Shape, to do so.   Click Browse > Modeling > Things.   Click + New. In the Name field, type TIPC_Thing. If Project is not already set, search for and select PTCDefaultProject. In the Base Thing Template field, search for and select GenericThing.   At the top, click Save.     Add Info Table Property   Now that we have our Thing instantiated, we want to both add an Info Table Property, as well as set some Default Values.   At the top, click Properties and Alerts.   Click + Add.   On the right-side slide-out, in the Name field, type InfoTable_Property. Change Base Type to INFOTABLE. In the Data Shape field, search for and select TIPC_DataShape. Note that the Data Shape field will not appear until you set Base Type to INFOTABLE. Check Persistent.   At the top-right, click the "check" button for Done. At the top, click Save.   Set Value of Property Now that we have a place in which to store spreadsheet-like values, we'll do so manually for testing.   On the InfoTable_Property row, under the Value column, click the "pencil" icon for Set value of property.   On the pop-up, click + Add.   Enter the following values in each field as per the table below: Field Name Value month  January excess_temperature 5 need_lubricant 2 low_filler 1 low_gas 2   Click Add.   Click + Add again, enter the following values, and finish input by clicking Add, as per above. Field Name Value month February excess_temperature 7 need_lubricant 1 low_filler 3 low_gas 2 6. Click + Add again, enter the following values, and finish input by clicking Add, as per above. Field Name Value month March excess_temperature 6 need_lubricant 2 low_filler 1 low_gas 1   7. On the pop-up, click Save.   8. At the top, click Save.   Step 4: Create Mashup   Now that we have our data in-place for testing (and could be connected to automated systems after we finish testing), we need to visualize the data.   As mentioned, we'll use a Pareto Chart Widget, but first, we need to create a Mashup into which we can place the Widget.   Click Browse > Visualization > Mashups.   Click + New.   Leave the defaults and click OK.   In the Name field, type TIPC_Mashup. If Project is not already set, search for and select PTCDefaultProject. At the top, click Save .   At the top, click Design.   At the top-left, click the Widgets tab.   Drag-and-drop a Pareto Chart Widget onto the central Canvas.   At the top, click Save.   Click here to view Part 2 of this guide.

  Step 6: Create OPC UA Tag in ThingWorx   We will now create a Device in Kepware with a Tag whose value will be shown in ThingWorx.   Right-click on Channel1 that was just created, then click Next to accept the default name Device1       Click Next six times to accept the default settings, Then click the Select import items button.     Expand the remote OPC UA server URL, then expand OpcPlc and Telemetry.     Click SlowUint1 to select it, then click Add items >>. Click OK, Next, Finish. Return to ThingWorx Composer. Under Browse > Modeling > Industrial Connections, open IndConn_Server. Expand Channel1 > Device1 > OpcPlc, then click Telemetry.     Click the check-box next to SlowUint1. Click Bind to New Entity.     Select RemoteThing, then click OK. Enter azure-opcua-plc in the Name field, then click Save.     Click Properties and Alerts, then Click Refresh to see the property value changing every 10 seconds.     Step 7: Next Steps   Congratulations! You've successfully completed the Connect to an Azure OPC UA Server guide, and learned how to:   Create an OPC UA Server in Azure Configure Kepware as on OPC UA Client Connect Kepware to ThingWorx Foundation Monitor OPC UA data in ThingWorx Composer   Learn More   We recommend the following resources to continue your learning experience: Capability Guide Experience Create Your Application UI   Additional Resources   If you have questions, issues, or need additional information, refer to:   Resource Link Community Developer Community Forum Support Getting Started with ThingWorx Documentation Kepware documentation Support Kepware Support site