IoT Tips

Thing Subscription This post is intended for novice ThingWorx users who wants to understand what the definition of Thing Subscription is and the overall purpose of using Thing Subscriptions.   Definition of a Thing Subscription? A Thing subscription is a script(JavaScript) that is called each time an event occurs. Events are property states which are of end users interest (e.g. temperature) and therefore indicators to kick off some functionality in a Thing subscription when any action needed. Events can e.g. be triggered by an Alert that detects a change or an anomaly in property values. The Thing subscription is explicitly linked to an event and when the event is fired the data is being passed to the subscriber.    Why Use a Thing Subscription? Imagine your machine is running 24 hours 7 days a week with supervised human interaction. If a pump temperature exceeds accepted value it needs to be regulated by the manufacturing department. But no one in the department knows when the temperature will exceed accepted value or drop suddenly therefore, the machines is always sporadically physically supervised by humans which leads to heavy costs for the manufacture. With a Thing Subscription a notification alert email can be sent directly to the department manager who acts based on the email notification.   Thing Subscription must have A Thing subscription must have defined a rule which gets executed when an event occurs. The definition of the rule may accommodate any appropriate business logic.   Thing Subscription example process In this scenario Thing subscription is using a predictive analytics model to detect Data Change or any anomaly values going through a Thing Property. So, based on historical data including failure information, a predictive analytics model begins to analyze run-time values from individual Things/properties to the analytics server. The predictive analytics model detects a pattern which detects past failures, when the analytics model predicts a failure/event based on the analyzed patterns an action is being fired via a Thing subscription. That action could be for ThingWorx to create a service ticket or send a notification email to the service department.   Example of a simple Thing Subscription set-up without using Analytics model to analyze data but instead a build-in ThingWorx alert Below example of Thing Subscription will send a notification email when temperature exceeds defined values from ThingWorx alert configuration. Prerequisites; it is necessary to have a mail server extension imported into the ThingWorx Composer this enables the service department to receive the email notification when an event have occurred. The extension can be downloaded from the marketplace. 1. Create a Thing with the MailServer[i] as the Base Thing template.     2. Create a new Thing and add Properties together with an alert that is triggered when the value exeeds user defined temerature.   3. Enable the Thing Subcriptions by Select Subscription and click +Add Make sure to mark the checkbox Enabled Selecting your Event name and your Property name In the right side of the screen you can enter your script/function that will notify ThingWorx email service to create the email notification Select Done and Save   4. Enable Email notification by selecting Services Provide an name Select Me/Entities Mark Other entity Find your Thing where the MailServer is the Thing Template   5. Then find the SendMessage snippet/script and fill out the snippet with your personal information.   [i] View this blog for more information on how to install the MailServer

Connect and Monitor Industrial Plant Equipment Learning Path   Learn how to connect and monitor equipment that is used at a processing plant or on a factory floor.   NOTE: Complete the following guides in sequential order. The estimated time to complete this learning path is 180 minutes.   Create An Application Key  Install ThingWorx Kepware Server Connect Kepware Server to ThingWorx Foundation Part 1 Part 2 Create Industrial Equipment Model Build an Equipment Dashboard Part 1 Part 2

ThingWorx is great for storing large amounts of data coming from your devices but it can also be used like a traditional, row based database for information you would like to integrate with your thing data. Attached to this blog entry is a short example of creating an address book database using a DataTable and a DataShape. It does not focus on creating mashups but sticks with discussing the modeling and service calls you would use to create a simple database.

Original Post Date:     June 6, 2016 Description: This is a video tutorial on creating a Value Stream, adding the Value Stream to a Remote Thing, adding, binding and querying the (remote) properties.      

How to input Database User Credentials at RunTime. This Blog considers that you have already imported the Database Extension and Configured the Thing Template. If you have not done this already please see Steps to connecting to your Relational Database first. Steps: Create a Database Thing template with correct configuration. Example configuration for MySql Database: jDBCDriverClass: com.mysql.jdbc.Driver jDBCConnectionURL: jdbc:mysql://127.0.0.1:3306/<DatabaseNameHere>?allowMultiQueries=true connectionValidationString: SELECT NOW() maxConnections: 100 userName: <DataBaseUserNameHere> password: <DataBasePasswordHere> Create any Generic Thing and add a service to create thing based on the Thing template created in Step 1. Example: // NewDataBaseThingName is the String input for name the database thing to be created. // MySqlServerUpdatedConfiguration is the Thing template with correct configuration var params = {      name: NewDataBaseThingName /* STRING */,      description: NewDataBaseThingName /* STRING */,     thingTemplateName: "MySqlServerUpdatedConfiguration" /* THINGTEMPLATENAME */,     tags: undefined /* TAGS */ }; // no return Resources["EntityServices"].CreateThing(params); Add code to enable and then restart the above thing using EnableThing() and RestartThing() service. Example Things[NewDataBaseThingName].EnableThing(); Things[NewDataBaseThingName].RestartThing(); Test and confirm that the Database Thing services runs as expected. Now Create a DataShape with following Fields: jDBCDriverClass: STRING jDBCConnectionURL: STRING connectionValidationString: STRING maxConnections: NUMBER userName: STRING password: PASSWORD Now in the Generic Thing created in Step 1 add code to update the configuration settings of DataBase Thing. Make sure JDBC Driver Class Name should never be changed. If different database connection is required use different Thing Template. Also, add code to restart the DataBase Thing using RestartThing() service. Example: var datashapeParams = {     infoTableName : "InfoTable",     dataShapeName : "DatabaseConfigurationDS" }; // CreateInfoTableFromDataShape(infoTableName:STRING("InfoTable"), dataShapeName:STRING):INFOTABLE(DatabaseConfigurationDS) var config = Resources["InfoTableFunctions"].CreateInfoTableFromDataShape(datashapeParams); var passwordParams = {         data: "DataBasePasswordHere" /* STRING */ }; // DatabaseConfigurationDS entry object var newEntry = new Object(); newEntry.jDBCDriverClass= "com.mysql.jdbc.Driver"; // STRING newEntry.jDBCConnectionURL = "jdbc:mysql://127.0.0.1:3306/<DatabaseNameHere>?allowMultiQueries=true"; // STRING newEntry.connectionValidationString = "SELECT NOW()"; // STRING newEntry.maxConnections = 100; // NUMBER newEntry.userName = "DataBaseUserNameHere"; // STRING newEntry.password = Resources["EncryptionServices"].EncryptPropertyValue(passwordParams); // PASSWORD config.AddRow(newEntry); var configurationTableParams = { configurationTable: config /* INFOTABLE */, persistent: true /* BOOLEAN */, tableName: "ConnectionInfo" /* STRING */ }; // ThingNameForConfigurationUpdate is the input string for Thing Name whose configuration needs to be updated. // no return Things[ThingNameForConfigurationUpdate].SetConfigurationTable(configurationTableParams); Things[ThingNameForConfigurationUpdate].RestartThing(); Test and confirm that the Database Thing services runs as expected.

You can control the Tracking Indicator that is used to mark the ThingMark position. The Tracking Indicator is a green hexagon, in the screenshot below the red arrow points to it. You can control the display of this tracking indicator via the Display Tracking Indicator property of the ThingMark widget: But you can also get fancier. Here is an exmaple that shows the tracking indicator for 3 seconds when the tracking has started and then hides it automatically. To achieve such a behavior you'll have to use a bit of Javascript. We'll first create a function hideIn3Sec() in the javascript section of our view and then add it to the javascript handler of the Tracking Acquired event of the ThingMark widget. Step 1: Here is the code for copy/paste convenience: $scope.hideIn3Sec=function(){   // The $timeout function has two arguments: the function to execute (defined inline here)   // and the time in msec after which the function is invoked.   $timeout( function hide(){     // you may have to change 'thingMark-1' by the id of the ThingMark in your own experience     $scope.app.view['Home'].wdg['thingMark-1']['trackingIndicator']=false;   },   3000); } Step 2: That's it. Have fun!

Hi all,   ThingWorx contains lots of useful functionality for your services (last count is 339 Snippets in ThingWorx 8.5.2). These snippets are an important part of the platform application building capabilities, and most of them are simple enough to understand based on their name and the description that appears when hovering on them.   I have witnessed that however, in some cases, the platform users are not aware of their full capabilities. With this in mind, I started creating some time ago a Snippet Guide for my personal use that I'm sharing now with the community. It contains additional explanations, documentation links and sample source code tested by me.   Please bear in mind that it was done for an earlier ThingWorx version and I did not have enough time to update it for 8.5.x, but it should work the same here as well.   This enhanced documentation is not supported by PTC, so please 1. do not open a Tech Support ticket based on the content of this document and, instead 2. Comment on this thread if there are things I can improve on it.   Happy New Year!

This might be a well-known topic for some, but I recently had a need that Event Routers fit into perfectly and wanted to share. If you have some neat applications for Event Routers on mashups, feel free to reply!   What? Event Routers are a function on Mashups that let you connect multiple inputs to a single output. For my use case, this was extremely helpful to let me have two different Service Outputs go to the same Widget. They are a really simple tool that can save a lot of headache.   How? Event Routers work by funneling the latest data through to a single output. This is particularly useful for  user-activated actions with the output tied to a widget or another service. The Event Router automatically activates when any one of the Inputs changes.   Example I have two services that generate HTML from different sources, but I want to display just the latest one that the user had activated in a single HTML Text Area widget. The two different services are activated with two different buttons. But how do I show these two outputs in a single widget? Create an Event Router with two HTML inputs!         Now I just tie each service output to the Inputs and tie the Output to the HTML Text Area Text (note: the icon for Input2 is incorrect—it should be HTML as well; this system is running 8.5.1, perhaps it's an issue in that release).         Now when the user clicks on either button, the correct service’s HTML is sent to the HTML Text Area. Ta-da!   P.S. I noticed in some older posts that Event Routers used to be a widget or extension that came and went. Now (8.5+) it is baked into the Functions on the far right side of Mashup Builder.

One of the recurring patterns on the Axeda Platform is making requests from custom objects to other services, to be called either via Scripto, or through Expression Rules that help integrate Axeda data with your custom systems or third parties such as Salesforce.com.  Java developers would normally use a URLConnection to do this, but due to security requirements, access to the URLConnection API is sandboxed, and the HTTPBuilder API is provided instead. Below is a short example of GETting a payload from http://www.mocky.io/v2/57d02c05100000c201208cb5 to your custom object.  One of the requirements of many services is being able to pass in API keys as part of the header request.  While in this example the API key is embedded in the code, the recommended way of storing API keys on the Axeda Platform is to use the External Credential lockbox API.  This allows you to change the API keys securely without needing to change code. import groovyx.net.http.HTTPBuilder import static groovyx.net.http.ContentType.* import static groovyx.net.http.Method.* def http = new HTTPBuilder('https://www.mocky.io') http.request( GET, JSON ) {     uri.path = '/v2/57d02c05100000c201208cb5'     uri.headers.'appKey' = '7661392f-2372-4cba-a921-f1263c938090'     response.success = { resp ->         println "POST response status: ${resp.statusLine}"         logger.info "POST RESPONSE status: ${resp.statusLine}"         assert resp.statusLine.statusCode == 201     } } An example for Salesforce might look like so: import groovyx.net.http.HTTPBuilder import static groovyx.net.http.ContentType.* import static groovyx.net.http.Method.* def xml_body = """<?xml version="1.0" encoding="utf-8" ?> <env:Envelope xmlns:xsd="http://www.w3.org/2001/XMLSchema"     xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"     xmlns:env="http://schemas.xmlsoap.org/soap/envelope/">   <env:Body>     <n1:login xmlns:n1="urn:partner.soap.sforce.com">       <n1:username>johndoe@example.com</n1:username>       <n1:password>Password+SECRETKEY</n1:password>     </n1:login>   </env:Body> </env:Envelope> """ def http = new HTTPBuilder('https://login.salesforce.com/') http.request( POST ) {     uri.path = '/services/Soap/u/35.0 '     body = xml_body     response.success = { resp ->         println "POST response status: ${resp.statusLine         logger.info "POST RESPONSE status: ${resp.statusLine}"         assert resp.statusLine.statusCode == 201     } } This request will give you a security token you can use in future calls to Salesforce APIs; you would use Groovy's native XmlSlurper/XmlParser to parse the response and get the session id to use in future requests.  You would then use this session id like in the following example to get the available REST resources: import groovyx.net.http.HTTPBuilder import static groovyx.net.http.ContentType.* import static groovyx.net.http.Method.* def http = new HTTPBuilder('https://na1.salesforce.com/') http.request( POST ) {     uri.path = '/services/data/v29.0'     uri.headers.'Authorization' = 'Bearer SESSIONID'     response.success = { resp ->         println "POST response status: ${resp.statusLine}"         logger.info "POST RESPONSE status: ${resp.statusLine}"         assert resp.statusLine.statusCode == 201     } } Further reading: HttpBuilder Wiki - https://github.com/jgritman/httpbuilder/wiki Groovy Xml Processing - http://groovy-lang.org/processing-xml.html

The following code snippet will retrieve a months worth of data from the system and return it as a CSV document suitable for import into your spreadsheet or reporting tool of choice. import static com.axeda.sdk.v2.dsl.Bridges.* import com.axeda.drm.sdk.Context import com.axeda.common.sdk.id.Identifier import com.axeda.services.v2.* import com.axeda.sdk.v2.exception.* def ac = new AuditCriteria() ac.fromDate = Date.parse('yyyy-MM-dd', '2017-03-01') ac.toDate   = Date.parse('yyyy-MM-dd', '2017-03-31') def retString = '' tcount = 0 while ( (results = auditBridge.find(ac)) != null  && tcount < results .totalCount) {   results.audits.each { res ->     retString += "${res?.user?.id},${res?.asset?.serialNumber},${res?.category},${res.message},${res.date}\n"     tcount++   }   ac.pageNumber = ac.pageNumber + 1 } return retString

Design Your Data Model Guide Part 1   Overview   This project will introduce the process of taking your IoT solution from concept to design. Following the steps in this guide, you will create a solution that doesn’t need to be constantly revamped, by creating a comprehensive Data Model before starting to build and test your solution. We will teach you how to utilize a few proposed best practices for designing the ThingWorx Data Model and provide some prescriptive methods to help you generate a high-quality framework that meets your business needs. NOTE: This guide’s content aligns with ThingWorx 9.3. The estimated time to complete ALL 3 parts of this guide is 60 minutes. All content is relevant but there are additional tools and design patterns you should be aware of. Please go to this link for more details.    Step 1: Data Model Methodology   We will start by outlining the overall process for the proposed Data Model Methodology.       Step Description 1 User Stories Identify who will use the application and what information they need. By approaching the design from a User perspective, you should be able to identify what elements are necessary for your system. 2 Data Sources Identify the real-world objects or systems which you are trying to model. To create a solid design, you need to identify what the “things” are in your system and what data or functionality they expose. 3 Model Breakdown Compose a representative model of modular components to enable uniformity and reuse of functionality wherever possible. Break down user requirements and data, identifying how the system will be modeled in Foundation. 4 Data Strategy Identify the sources of data, then evaluate how many different types of data you will have, what they are, and how your data should be stored. From that, you may determine the data types and data storage requirements. 5 Business Logic Strategy Examine the functional needs, and map them to your design for proper business logic implementation. Determine the business logic as a strategic flow of data, and make sure everything in your design fits together in logical chunks. 6 User Access Strategy Identify each user's access and permission levels for your application. Before you start building anything, it is important to understand the strategy behind user access. Who can see or do what? And why? NOTE: Due to the length of this subject, the ThingWorx Data Model Methodology has been divided into multiple parts. This guide focuses on the first three steps = User Stories, Data Sources, and Model Breakdown. Guides covering the last three steps are linked in the final Next Steps page.    Step 2: User Stories     With a user-based approach to design, you identify requirements for users at the outset of the process. This increases the likelihood of user satisfaction with the result. Utilizing this methodology, you consider each type of user that will be accessing your application and determine their requirements according to each of the following two categories: Category Requirement Details Functionality Determine what the user needs to do. This will define what kind of Services and Subscriptions will need to be in the system and which data elements and Properties must be gathered from the connected Things. Information What information do they need? Examine the functional requirements of the user to identify which pieces of information the users need to know in order to accomplish their responsibilities.   Factory Example   Let’s revisit our Smart Factory example scenario. The first step of the User Story phase of the design process is to identify the potential users of your system. In this example scenario, we have defined three different types of users for our solution: Maintenance Operations Management Each of these users will have a different role in the system. Therefore, they will have different functional and informational needs.   Maintenance   It is the maintenance engineer’s job to keep machines up and running so that the operator can assemble and deliver products. To do this well, they need access to granular data for the machine’s operating status to better understand healthy operation and identify causes of failure. They also need to integrate their maintenance request management system to consolidate their efforts and to create triggers for automatic maintenance requests generated by the connected machines. Required Functionality Get granular data values from all assets Get a list of maintenance requests Update maintenance requests Set triggers for automatic maintenance request generation Automatically create maintenance requests when triggers have been activated Required Information Granular details for each asset to better understand healthy asset behavior Current alert status for each asset When the last maintenance was performed on an asset When the next maintenance is scheduled for an asset Maintenance request for information, including creation date, due date, progress notes   Operations   The operator’s job is to keep the line running and make sure that it’s producing quality products. To do this, operators must keep track of how well their line is running (both in terms of speed and quality). They also need to be able to file maintenance requests when they have issues with the assets on their line. Required Functionality File maintenance request Get quality data from assets on their line Get performance data for the whole line Get a prioritized list of production orders for their line Create maintenance requests Required Information Individual asset performance metrics Full line performance metrics Product quality readings   Management   The production manager oversees the dispatch of production orders and ensures quotas are being met. Managers care about the productivity of all lines and the status of maintenance requests. Required Functional Create production orders Update production orders Cancel production orders Access line productivity data Elevate maintenance request priority Required Information Production line productivity levels (OEE) List of open maintenance requests   Step 3: Data Sources – Thing List     Thing List   Once you have identified the users' requirements, you'll need to determine what parts of your system must be connected. These will be the Things in your solution. Keep in mind that a Thing can represent many different types of connected endpoints. Here are some examples of possible Things in your system: Devices deployed in the field with direct connectivity or gateway-connectivity to Foundation Devices deployed in the field through third-party device clouds Remote databases Connections to external business systems (e.g., Salesforce.com, Weather.com, etc.)   Factory Example   In our Smart Factory example, we have already identified the users of the system and listed requirements for each of those users. The next step is to identify the Things in our solution. In our example, we are running a factory floor with multiple identical production lines. Each of these lines has multiple different devices associated with it. Let’s consider each of those items to be a connected Thing. Things in each line: Conveyor belt x 2 Pneumatic gate Robotic Arm Quality Check Camera Let's also assume we already have both a Maintenance Request System and a Production Order System that are in use today. To add this to our solution, we want to build a connector between Foundation and the existing system. These connectors will be Things as well. Internal system connection Thing for Production Order System Internal system connection Thing for Maintenance Request System NOTE: It is entirely possible to have scenarios in which you want to examine more granular-level details of your assets. For example, the arm and the hand of the assembly robot could be represented separately. There are endless possibilities, but for simplicity's sake, we will keep the list shorter and more high-level. Keep in mind that you can be as detailed as needed for this and future iterations of your solution. However, being too granular could potentially create unnecessary complexity and data overload.    Click here to view Part 2 of this guide.

This post covers how to build and operationalize a time series model using Thingworx Analytics. A lookback window is used to read multiple previous rows before the current one, and base the prediction on those lookback rows.   In this example we use time series data to predict water flow for different water pumps in a system.   There is a full explanation of the method attached, also all necessary resources are included in the attached files.

This example provides the ability to generate a simple entity structure and some historical data for each entity. Historical data is run through a ThingWorx service to generate histogram data for display in a bar chart.  The provided ThingWorx entities and PDF document provide the example as well as documentation.

Please find here an Labview implementation to connect to Thingworx via RestCalls. Have Fun using it. Any Feedback is appreciated. https://github.com/Seppel1985/LabVIEW_TWX_RestAPI

This simple example creates an infotable of hierarchical data from an existing datashape that can be used in a tree or D3 Tree widget.  Attachments are provides that give a PDF document as well as the ThingWorx entities for the example.  If you were just interested in the service code, it is listed below: var params = {   infoTableName : "InfoTable",   dataShapeName : "TreeDataShape" }; // CreateInfoTableFromDataShape(infoTableName:STRING("InfoTable"), dataShapeName:STRING):INFOTABLE(TreeDataShape) var result = Resources["InfoTableFunctions"].CreateInfoTableFromDataShape(params); var NewRow = {}; NewRow.Parent = "No Parent"; NewRow.Child = "Enterprise"; NewRow.ChildDescription = "Enterprise"; result.AddRow(NewRow); NewRow.Parent = "Enterprise"; NewRow.Child = "Site1"; NewRow.ChildDescription = "Wilmington Plant"; result.AddRow(NewRow); NewRow.Parent = "Site1"; NewRow.Child = "Site1.Line1"; NewRow.ChildDescription = "Blow Molding"; result.AddRow(NewRow); NewRow.Parent = "Site1.Line1"; NewRow.Child = "Site1.Line1.Asset1"; NewRow.ChildDescription = "Preform Staging"; result.AddRow(NewRow); NewRow.Parent = "Site1.Line1"; NewRow.Child = "Site1.Line1.Asset2"; NewRow.ChildDescription = "Blow Molder"; result.AddRow(NewRow); NewRow.Parent = "Site1.Line1"; NewRow.Child = "Site1.Line1.Asset3"; NewRow.ChildDescription = "Bottle Unscrambler"; result.AddRow(NewRow); NewRow.Parent = "Site1"; NewRow.Child = "Site1.Line2"; NewRow.ChildDescription = "Filling"; result.AddRow(NewRow); NewRow.Parent = "Site1.Line2"; NewRow.Child = "Site1.Line2.Asset1"; NewRow.ChildDescription = "Rinser"; result.AddRow(NewRow); NewRow.Parent = "Site1.Line2"; NewRow.Child = "Site1.Line2.Asset2"; NewRow.ChildDescription = "Filler"; result.AddRow(NewRow); NewRow.Parent = "Site1.Line2"; NewRow.Child = "Site1.Line2.Asset3"; NewRow.ChildDescription = "Capper"; result.AddRow(NewRow); NewRow.Parent = "Site1"; NewRow.Child = "Site1.Line3"; NewRow.ChildDescription = "Packaging"; result.AddRow(NewRow); NewRow.Parent = "Site1.Line3"; NewRow.Child = "Site1.Line3.Asset1"; NewRow.ChildDescription = "Printer Labeler"; result.AddRow(NewRow); NewRow.Parent = "Site1.Line3"; NewRow.Child = "Site1.Line3.Asset2"; NewRow.ChildDescription = "Packer"; result.AddRow(NewRow); NewRow.Parent = "Site1.Line3"; NewRow.Child = "Site1.Line3.Asset3"; NewRow.ChildDescription = "Palletizing"; result.AddRow(NewRow); NewRow.Parent = "Enterprise"; NewRow.Child = "Site2"; NewRow.ChildDescription = "Mobile Plant"; result.AddRow(NewRow); NewRow.Parent = "Site2"; NewRow.Child = "Site2.Line1"; NewRow.ChildDescription = "Blow Molding"; result.AddRow(NewRow); NewRow.Parent = "Site2.Line1"; NewRow.Child = "Site2.Line1.Asset1"; NewRow.ChildDescription = "Preform Staging"; result.AddRow(NewRow); NewRow.Parent = "Site2.Line1"; NewRow.Child = "Site2.Line1.Asset2"; NewRow.ChildDescription = "Blow Molder"; result.AddRow(NewRow); NewRow.Parent = "Site2.Line1"; NewRow.Child = "Site2.Line1.Asset3"; NewRow.ChildDescription = "Bottle Unscrambler"; result.AddRow(NewRow); NewRow.Parent = "Site2"; NewRow.Child = "Site2.Line2"; NewRow.ChildDescription = "Filling"; result.AddRow(NewRow); NewRow.Parent = "Site2.Line2"; NewRow.Child = "Site2.Line2.Asset1"; NewRow.ChildDescription = "Rinser"; result.AddRow(NewRow); NewRow.Parent = "Site2.Line2"; NewRow.Child = "Site2.Line2.Asset2"; NewRow.ChildDescription = "Filler"; result.AddRow(NewRow); NewRow.Parent = "Site2.Line2"; NewRow.Child = "Site2.Line2.Asset3"; NewRow.ChildDescription = "Capper"; result.AddRow(NewRow); NewRow.Parent = "Site2"; NewRow.Child = "Site2.Line3"; NewRow.ChildDescription = "Packaging"; result.AddRow(NewRow); NewRow.Parent = "Site2.Line3"; NewRow.Child = "Site2.Line3.Asset1"; NewRow.ChildDescription = "Printer Labeler"; result.AddRow(NewRow); NewRow.Parent = "Site2.Line3"; NewRow.Child = "Site2.Line3.Asset2"; NewRow.ChildDescription = "Packer"; result.AddRow(NewRow); NewRow.Parent = "Site2.Line3"; NewRow.Child = "Site2.Line3.Asset3"; NewRow.ChildDescription = "Palletizing"; result.AddRow(NewRow);

Let's assume I collect Timeseries Data of two temperature sensors, located next to each other. This is done for redundancy and ensuring the quality of measures. Each of the sensors is logged into its Property in ThingWorx and I can create a Timeseries for the individual sensors. However I would like to create a combined InfoTable that holds information for both sensors, but averages out their values.   Instead of reading values from a stream, I just create some custom data for both InfoTables. After this I use the UNION function to combine the two tables and sort them. Once they are sorted, the INTERPOLATE function allows to group the InfoTable by timestamp.   With this, I have combined the two sensor result into on result set. Taking the average of numbers will give closer results to the real value (as both sensors might not be 100% accurate). In case one sensor does not have data for a given point in time, it will still be considered in the final output.   InfoTable1:   2018-12-18 00:00:00.000 2 2018-12-19 00:00:00.000 3 2018-12-20 00:00:00.000 5 2018-12-21 00:00:00.000 7   InfoTable2:   2018-12-18 00:00:00.000 1 2018-12-19 12:00:00.000 2 2018-12-20 00:00:00.000 3 2018-12-21 00:00:00.000 4   Combined Result:   2018-12-18 00:00:00.000 1.5 2018-12-19 00:00:00.000 3 2018-12-19 12:00:00.000 2 2018-12-20 00:00:00.000 4 2018-12-21 00:00:00.000 5.5     This can be done with the following code:   // Required DataShape "myInfoTableShape": "timestamp" = DATETIME, "value" = NUMBER // The Service Output is an InfoTable based on the same DataShape var params = { infoTableName : "InfoTable", dataShapeName : "myInfoTableShape" }; // Create two InfoTables, representing the data of each sensor var infoTable1 = Resources["InfoTableFunctions"].CreateInfoTableFromDataShape(params); var infoTable2 = Resources["InfoTableFunctions"].CreateInfoTableFromDataShape(params); var newEntry = new Object(); // Create custom data for InfoTable1 newEntry.timestamp = 1545091200000; newEntry.value = 2; infoTable1.AddRow(newEntry); newEntry.timestamp = 1545177600000; newEntry.value = 3; infoTable1.AddRow(newEntry); newEntry.timestamp = 1545264000000; newEntry.value = 5; infoTable1.AddRow(newEntry); newEntry.timestamp = 1545350400000; newEntry.value = 7; infoTable1.AddRow(newEntry); // Create custom data for InfoTable2 newEntry.timestamp = 1545091200000; newEntry.value = 1; infoTable2.AddRow(newEntry); newEntry.timestamp = 1545220800000; newEntry.value = 2; infoTable2.AddRow(newEntry); newEntry.timestamp = 1545264000000; newEntry.value = 3; infoTable2.AddRow(newEntry); newEntry.timestamp = 1545350400000; newEntry.value = 4; infoTable2.AddRow(newEntry); // Combine the two InfoTables via the UNION function var unionTable = Resources["InfoTableFunctions"].Union({ t1: infoTable1, t2: infoTable2 }); // Optional: Sort the table by timestamp var sortedTable = Resources["InfoTableFunctions"].Sort({ sortColumn: "timestamp", t: unionTable, ascending: true }); // Interpolate the (sorted) table by Interval and take average values and build the result var result = Resources["InfoTableFunctions"].Interpolate({ mode: "INTERVAL", timeColumn: "timestamp", t: sortedTable, ignoreMissingData: undefined, stats: "AVG", endDate: 1545609600000, columns: "value", count: undefined, startDate: 1545004800000 });  

Video Author:                    Christophe Morfin Original Post Date:            June 9, 2017 Applicable Releases:        ThingWorx Analytics 8.0   Description: In this video we go through the steps to install ThingWorx Analytics Server 8.0.    

Original Post Date:     June 6, 2016 Description: This tutorial video will walk you through the installation process for the PostgreSQL-based version of the ThingWorx Platform in a Windows environment.  All required software components will be covered in this video.    

I recently had a customer who wanted to run services on ThingWorx from Power BI to retrieve existing operational data, and we were a bit stumped on how to pass the API key over in the headers, so I did a bit of Googling and pieced together the solution. It's not quite intuitive on the Power BI side, so I thought it would be helpful to share. If you have any other experience with integrating ThingWorx with Power BI, feel free to add a comment.    Prepare ThingWorx Create an Application Key that has Run Time execution access to the services you need. Understand the inputs needed for the service you would like. I'll have examples of none, one, an InfoTable, and multiple inputs.   Power BI Following the following steps in Power BI: 1. In Power BI, create a new blank query   2. On the left, right click on Query1 and go to the Advanced Editor:   3. Replace all of the body content with the following, replacing your API key, appropriate end point, and base URL as needed (this is an example with NO input parameters, I'll follow with examples of other parameters):     let appKey = "your-application-key-here", endpoint = "Things/YourThingNameHere/Services/YourServiceNameHere", baseUrl = "https://YourServerNameHere/Thingworx/", url = Text.Combine({baseUrl,endpoint}), body = "", request = Web.Contents( url, [ Headers = [ appKey = appKey, #"Content-Type" = "application/json", Accept = "application/json" ], Content = Text.ToBinary(body) ] ), Source = Json.Document(request) in Source       4. Click "Done", and now you'll have a warning about how to connect. Click the "Edit Credentials" button. 5. Leave it on Anonymous and click "Connect":   6. You should now see the return data coming from ThingWorx.   Note that I had a little trouble with this authentication initially and it saved the wrong method. To clear that out, go to the ribbon bar item "Data source settings" and select the server and clear it out.   Other Examples Here is an example for sending a single string parameter:   let appKey = "your-application-key-here", endpoint = "Things/YourThingNameHere/Services/YourServiceNameHere", baseUrl = "https://YourServerNameHere/Thingworx/", url = Text.Combine({baseUrl,endpoint}), body = "{""InputParameter"": ""InputValue""}", request = Web.Contents( url, [ Headers = [ appKey = appKey, #"Content-Type" = "application/json", Accept = "application/json" ], Content = Text.ToBinary(body) ] ), Source = Json.Document(request) in Source     Here's an example of sending a string and an integer: let appKey = "your-application-key-here", endpoint = "Things/YourThingNameHere/Services/YourServiceNameHere", baseUrl = "https://YourServerNameHere/Thingworx/", url = Text.Combine({baseUrl,endpoint}), body = "{""InputString"": ""Hello, world!"", ""InputNumber"" : 42}", request = Web.Contents( url, [ Headers = [ appKey = appKey, #"Content-Type" = "application/json", Accept = "application/json" ], Content = Text.ToBinary(body) ] ), Source = Json.Document(request) in Source   Here is an example for sending an InfoTable. Note that you must supply the dataShape with fieldDefinitions. If you're using an existing Data Shape, you can get the JSON by using the service GetDataShapeMetadataAsJSON() that is on the data shape.     let appKey = "your-application-key-here", endpoint = "Things/YourThingNameHere/Services/YourServiceNameHere", baseUrl = "https://YourServerNameHere/Thingworx/", url = Text.Combine({baseUrl,endpoint}), body = "{""propertyNames"": { ""rows"": [ { ""name"": ""FirstEntityName"", ""description"": ""The first entity"" }, { ""name"": ""SecondEntityName"", ""description"": ""The second entity"" }], ""dataShape"": { ""fieldDefinitions"": { ""name"": { ""name"": ""name"", ""aspects"": { ""isPrimaryKey"": true }, ""description"": ""Entity name"", ""baseType"": ""STRING"", ""ordinal"": 0 }, ""description"": { ""name"": ""description"", ""aspects"": {}, ""description"": ""Entity description"", ""baseType"": ""STRING"", ""ordinal"": 0 } } } }}", request = Web.Contents( url, [ Headers = [ appKey = appKey, #"Content-Type" = "application/json", Accept = "application/json" ], Content = Text.ToBinary(body) ] ), Source = Json.Document(request) in Source       If I find any more interesting ways to use Power BI with ThingWorx services, I'll add them on here.  

One of the interesting features of ThingWorx Analytics Manager is its ability to run distributed models created in Excel (and more of course).  Most people having been tasked with understanding data have built models in Excel and have sometimes built quite complex models (or even applications) with it.   The ability to tie these models to real data coming from various systems connected through ThingWorx and operationalise their execution is a really simple way for people to leverage their existing work and I.P. on a connected analytics journey.   To demonstrate this power and ease of implementation, I created a sample data set with historical data, traffic profile, and a simple anomaly detection model to execute with Analytics Manager.  (files are attached)   The online help center was quite helpful in explaining the process of Creating the Excel Workbook, however I got stuck at the XML mapping stage.  The Analytics and Excel documentation both neglect to mention one important detail -- you must be using the Windows version of Excel in order to get the XML Source functionality (and I use Mac).  Once using Windows, it was easy to do - here is a video of the XML mapping part of the process (for the inputs and results).   

This example is to achieve to update objects in Windchill thru extensions. It is really hard to find a resource for Windchill extension's services to take an advantage of them. So, I wrote a simple example to update objects in Windchill from Thingworx.   There are three data shapes needed to do this. One is "PTC.PLM.WindchillPartUfids" which has only "value" field (String) in it and another is "PTC.PLM.WindchillPartCheckedOutDS" which has a "ufid" field (String). Last one is "PTC.PLM.WindchillPartPropertyDS" which has a "ufid" field (String) and fields for "attributes". For an instance of the last data shape, there might be three fields as "ufid", "partPrice" and "quantity" to update parts. In this example, this data shape has two fields which are "ufid" and "almProjectId".   In this example, this needs two input parameters. One is ufid (String) and almProjectId (String). If you need to have multiple objects to update at once, you can use InfoTable type as an "ufid" input parameter instead of String type.   Note that this is an example code and need to handle exceptions if needed.     // To var params = {     infoTableName : "InfoTable",     dataShapeName : "PTC.PLM.WindchillPartUfids" };   // CreateInfoTableFromDataShape(infoTableName:STRING("InfoTable"), dataShapeName:STRING):INFOTABLE(PTC.PLM.WindchillPartUfids) var ufids = Resources["InfoTableFunctions"].CreateInfoTableFromDataShape(params);   // PTC.PLM.WindchillPartUfids entry object var newValue = new Object(); newValue.value = ufid; // STRING   ufids.AddRow(newValue);   // Check out var params = {     ufids: ufids /* INFOTABLE */,     comment: undefined /* STRING */,     dataShape: "PTC.PLM.WindchillPartCheckedOutDS" /* DATASHAPENAME */ };   // checkedOutObjs: INFOTABLE dataShape: "undefined" var checkedOutObjsFromService = me.CheckOut(params);   var params = {     infoTableName : "InfoTable",     dataShapeName : "PTC.PLM.WindchillPartUfids" };   // CreateInfoTableFromDataShape(infoTableName:STRING("InfoTable"), dataShapeName:STRING):INFOTABLE(PTC.PLM.WindchillPartUfids) var checkedOutObjs = Resources["InfoTableFunctions"].CreateInfoTableFromDataShape(params);   try {     var tableLength = checkedOutObjsFromService.rows.length;       for (var x = 0; x < tableLength; x++) {         var row = checkedOutObjsFromService.rows;               // PTC.PLM.WindchillPartUfids entry object         var checkedOutObj = new Object();         checkedOutObj.value = row.ufid.substring(0,row.ufid.lastIndexOf(":")); // STRING               //logger.warn("UFID : " + checkedOutObj.value);         checkedOutObjs.AddRow(checkedOutObj);           /* Update Objects in Windchill */         var params = {             infoTableName : "InfoTable",             dataShapeName : "PTC.PLM.WindchillPartPropertyDS"         };           // CreateInfoTableFromDataShape(infoTableName:STRING("InfoTable"), dataShapeName:STRING):INFOTABLE(PTC.ALM.WindchillPartPropertyDS)         var wcInfoTable = Resources["InfoTableFunctions"].CreateInfoTableFromDataShape(params);           // PTC.ALM.WindchillPartPropertyDS entry object         var newEntry = new Object();         newEntry.ufid = checkedOutObj.value; // STRING         newEntry.almProjectId = almProjectId; // STRING           wcInfoTable.AddRow(newEntry);           var params = {             objects: wcInfoTable /* INFOTABLE */,             modification: "REPLACE" /* STRING */,             dataShape: "PTC.PLM.WindchillPartCheckedOutDS" /* DATASHAPENAME */         };           // result: INFOTABLE dataShape: "undefined"         var result = me.Update(params);     }   } catch(err) {     logger.warn("ERROR Catched");     var params = {         ufids: ufids /* INFOTABLE */,         dataShape: "PTC.PLM.WindchillPartCheckedOutDS" /* DATASHAPENAME */     };       // result: INFOTABLE dataShape: "undefined"     var result = me.CancelCheckOut(params);  }   var params = {     ufids: checkedOutObjs /* INFOTABLE */,     comment: undefined /* STRING */,     dataShape: "PTC.PLM.WindchillPartCheckedOutDS" /* DATASHAPENAME */ };   // result: INFOTABLE dataShape: "undefined" var result = me.CheckIn(params);