IoT Tips

Video Author:                     Polina Osipova Original Post Date:            June 10, 2016   Description: This is a video tutorial on adding State Formatting in a Mashup using State Definitions.      

ThingTemplate   A ThingTemplate, at it's root is nothing but a class definition. Things are instances of a ThingTemplate which encapsulates business logic for a specific asset class.   This could be equated to that of a Class in an object-oriented programming concept. ThingTemplates provides initial state & implementation of behaviour for the Things implementing it. See ThingTemplates in Help Center & Similarities to Object-Oriented Programming for more.   ThingTemplate Use Cases   It's among the many building blocks for an IoT Solution which belong to the highest level objects created and maintained, i.e. Entities. There are several Entity Types in ThingWorx allowing users to model the physical world within the virtual realm of ThingWorx platform. There are following type of entities available within ThingWorx for modeling:   Things Thing Shapes Thing Templates Additional useful read Programming for the IoT Thing-Centric vs Traditional Query Approaches Model-View-Controller (MVC)   Ways to explore the out of the box provided ThingTemplates   All the available ThingTemplates can be listed and reviewed by navigating to the /Server via the ThingWorx REST API. List of ThingTemplates can be reviewed by using one of the following : <serverName>:<portNumber>/Thingworx/Server in a web browser and then locate and click on the ThingTemplates, or by; Typing <serverName>:<postNumber>/Thingworx/ThingTemplates in the web browser Either of the above listed options will display the following list in the web browser   List of ThingTemplates List shows all available ThingTemplates i.e. ThingTemplates that were provided OOTB and the ones that were created by the users as well. Using the column isSystemObject one can verify if the displayed ThingTemplate is provided OOTB or is custom one created by the user.   Accessing ThingTemplate Class description / details   This is covered under the JavaDocs for the ThingWorx Platform API, which can be accessed via the API Documentation   Search for ThingTemplate for following result   API Documentation: ThingTemplate While creating a custom ThingTemplate outside of ThingWorx composer, e.g. creating ThingWorx extension it is must to have following two entities in the metadata.xml file.     <Entities> <ThingTemplate> </ThingTemplate> </Entities> Note: If Eclipse Plugin is used for creating the ThingTemplate, above mentioned entries will automatically be created in the metadata.xml     Tips & tricks How to modify Base Template for a ThingTemplate for a Thing How to iterate through list of Things to identify their ThingTemplate & based on that set a particular property in those Things Add run time permissions through script to Thing Templates, Thing Shapes, etc Changing a Thing's implemented ThingTemplate after it has been created in ThingWorx Basic troubleshooting  Error "Thing [] is not running" when editing ThingTemplates in ThingWorx Troubleshooting Entity Relationship issues in ThingWorx Best Practises How to search for All entities in ThingWorx or by Thing Type How to create custom ThingTemplate when developing custom ThingWorx Extension Inheriting Permissions from a ThingTemplate      

ThingWorx Manufacturing Tips & Tricks Webinar is a weekly opportunity to hear PTC Subject Matter Experts present on various topics related to the manufacturing space and applications.   Agenda for this week's recorded session - - Overview & Application Demo - Aron Semle - Architecture Overview - Varathan Ranganathan - Q&A  

    Go beyond functional application development and learn how you can dress up your UI to enhance the user experience. In this webinar, we'll show you how to implement common design elements throughout your UI including custom logos, color schemes, and styles.   In this video, UI expert Tsveta Saul will demonstrate valuable tips and tricks for making a sophisticated IoT application with ThingWorx, including: Masters and Menus - enhance your app framework with personalized menu titles, backgrounds, and custom headers Layout and Labels - create consistency in your application by combining commonly used widgets State and Style Definitions - define widget styles to illustrate your brand Images - integrate visuals to describe thousands of words' worth of design and development specifications Watch the recording above, and download this sample Mashup containing all the data and entities shared in the video.   Q&A   We didn’t have time to get to all of the questions during the live webcast, but we’ve answered them here on our blog. Have any additional questions? Please leave us a comment. WHERE ELSE CAN STATE DEFINITIONS BE APPLIED? State Definitions can be applied to the Map Widget. Not only can you add color-coded pins, but also images that describe certain types of assets, for example. You can also add State Definitions to your Time Series Chart. For instance, you can color-code for values that exceed a certain threshold.   ARE THERE ANY IMPORTANT OR HIDDEN PROPERTIES THAT I SHOULD KNOW ABOUT? One feature to take note of is the Z-index, which helps you control the position of a widget in relation to another widget. This option can control whether users see the specific widget or not. ThingWorx has a robust a system that handles permissions – from users and groups to organizations. There’s a lot of control as to who can see what either through Model, or through specific services and conditions inside the Mashup.   HOW CAN I DISABLE A USER FROM SEEING SOMETHING OR DOING A CERTAIN ACTION? Again, that is handled through the security system of ThingWorx. There are multiple ways of authenticating users from other systems. You can create services that are related to your Things or user session parameters, and define whether a user can see those parameters or not.   HOW CAN WE CHANGE DATE FORMAT FOR X-AXIS IN TIME SERIES CHART? This property is available within the Time Series Chart Widget. It uses standard programming language – you can add or delete in the property.   CAN LAYOUT SPACING BE A PERCENTAGE? The spacing within the layout (none, 5px, 10px, 15px, or 20px).

  Based on real use cases and industry-leading solutions, this webinar looks at how developers can deliver valuable analytical outputs through experiences that ensure easy consumption of trusted analyses.   By taking a deep dive into a range of the analytics capabilities within ThingWorx, we will demonstrate how you can visualize complex analytic outputs to help your users understand what really matters in your data - and ultimately make quick, insightful business decisions.   Q&A   We didn’t have time to get to all of the questions during the live webcast, but we’ve answered them here on our blog. Have any additional questions? Please leave us a comment.   THIS SESSION TALKED ABOUT CONNECTIVITY WITH OTHER ANALYTICS PROGRAMS, SUCH AS R. HOW WOULD THINGWORX INTERACT WITH THE R PLATFORM? There are multiple reasons for using R and other analytics tools. Say you’re using R to build a predictive model, for instance—you can interact with data and load that information into our Analytics Server, even outside Analytics Builder. You can also interface in script within ThingWorx to run certain calculations driven by R. Moreover, even if you are building a model in R or any other tool, you can use Analytics Manager to operationalize data coming in from a Thing model that’s being scored against variables created elsewhere. Our ultimate goal is not to migrate you away from the tools you’re already using, but rather augment the development experience with ThingWorx integration.   HOW WOULD A DEVELOPER GO ABOUT CREATING & OBTAINING JSON AND CSV DATA FOR ANALYSIS? In terms of creating a historical data view, there are two separate methods. There’s creating a descriptive view for which you are using to create the model, and then there is operationalizing the model. On the operational side, it’s data coming from the Thing model being scored against the actual predictive model that’s created. For the descriptive view, the tool of choice ultimately boils down to organizational preference. How you load represented data into the Analytics Server is completely based on the tools with which you work.   CAN YOU EXPLAIN IN DETAIL THE STEPS FOR CONNECTING A MACHINE TO THE THINGWORX ANALYTICAL MODEL, INCLUDING HOW TO DEFINE THE DATA COMING FROM THE MACHINE TO CREATE THE MODEL? Absolutely. I’d encourage you to go check out our new Operationalize an Analytics Model developer guide available on the ThingWorx Developer Portal. In just 30 minutes, you’ll learn how to use Analytics Manager and ThingPredictor to automatically perform analytical calculations.   OUR ORGANIZATION SEES FEATURE ENGINEERING AS A KEY PART OF THE DATA ANALYSIS PROCESS. DO THINGWORX ALGORITHMS HANDLE FEATURE ENGINEERING INTERNALLY? Yes. There’s feature engineering in terms of getting a dataset ready for consumption. The technology ThingWorx provides is being able to automatically sift through the data and use various features to guide the selection of algorithms. Feature enrichment is what’s really powerful about our supervised machine learning capabilities.    HOW DO I INCORPORATE ADVANCED STYLING IN MY UI, LIKE ANIMATIONS AND RESPONSIVE BEHAVIORS? The standard way of achieving advanced styling in ThingWorx is to leverage the Media Entities, Style and State Definitions. Many widgets, such as the Value Display and the Shape Widget, have out-of-the-box ability to take a State Definition and apply advanced styling for things like severity of risks, etc. Watch our IoT Application Makeover webcast for more information about this topic.   DO YOU HAVE ANY RECOMMENDATIONS FOR GUARANTEEING DESIGN CONSISTENCY IN MY IOT APPLICATION? For non-designers: to keep your design clean and consistent, it is important to properly manage your Style Definitions. Define styles and stick to re-using them; don’t have five different styles for showing model accuracy, for instance. I would recommend creating 5-10 styles for text, and then from there choosing a color scheme for things like buttons, labels, charts, grid headers, and other elements where you need a vibrant color.

The purpose of this document is to see how you can setup an MXChip IoT DevKit and also how send the readings of this microprocessor to ThingWorx through an Azure cloud server. You will also learn how to view the values that are being sent.

First we need to Understand below terms: Quantitative Variable: A quantitative variable is naturally measured as a number for which meaningful arithmetic operations make sense. Examples: Height, age, crop yield, GPA, salary, temperature, area, air pollution index (measured in parts per million), etc. Categorical variable: Any variable that is not quantitative is categorical. Categorical variables take a value that is one of several possible categories. As naturally measured, categorical variables have no numerical meaning. Examples: Hair color, gender, field of study, college attended, political affiliation, status of disease infection. Ordinal Variables: An ordinal variable is a categorical variable for which the possible values are ordered. Ordinal variables can be considered “in between” categorical and quantitative variables. Example: Educational level might be categorized as     1: Elementary school education     2: High school graduate     3: Some college     4: College graduate     5: Graduate degree •    In this example (and for many ordinal variables), the quantitative differences between the categories are uneven, even though the differences between the labels are the same. (e.g., the difference between 1 and 2 is four years, whereas the difference between 2 and 3 could be anything from part of a year to several years) •    Thus it does not make sense to take a mean of the values. •    Common mistake: Treating ordinal variables like quantitative variables without thinking about whether this is appropriate in the particular situation at hand. Ordinal regression: In statistics, ordinal regression (also called "ordinal classification") is a type of regression analysis used for predicting an ordinal variable. The Ordinal Regression procedure allows you to build models, generate predictions, and evaluate the importance of various predictor variables in cases where the dependent (target) variable is ordinal in nature. Ordinal dependents and linear regression: When you are trying to predict ordinal responses, the usual linear regression models don't work very well. Those methods can work only by assuming that the outcome (dependent) variable is measured on an interval scale. Because this is not true for ordinal outcome variables, the simplifying assumptions on which linear regression relies are not satisfied, and thus the regression model may not accurately reflect the relationships in the data. In particular, linear regression is sensitive to the way you define categories of the target variable. With an ordinal variable, the important thing is the ordering of categories. So, if you collapse two adjacent categories into one larger category, you are making only a small change, and models built using the old and new categorizations should be very similar. Unfortunately, because linear regression is sensitive to the categorization used, a model built before merging categories could be quite different from one built after. Below are some examples pf ordered logistic regression: Example 1: A marketing research firm wants to investigate what factors influence the size of soda (small, medium, large or extra large) that people order at a fast-food chain. These factors may include what type of sandwich is ordered (burger or chicken), whether or not fries are also ordered, and age of the consumer. While the outcome variable, size of soda, is obviously ordered, the difference between the various sizes is not consistent. The difference between small and medium is 10 ounces, between medium and large 8, and between large and extra large 12. Example 2: A researcher is interested in what factors influence modaling in Olympic swimming. Relevant predictors include at training hours, diet, age, and popularity of swimming in the athlete’s home country. The researcher believes that the distance between gold and silver is larger than the distance between silver and bronze. Example 3: A study looks at factors that influence the decision of whether to apply to graduate school. College juniors are asked if they are unlikely, somewhat likely, or very likely to apply to graduate school. Hence, our outcome variable has three categories. Data on parental educational status, whether the undergraduate institution is public or private, and current GPA is also collected. The researchers have reason to believe that the “distances” between these three points are not equal. For example, the “distance” between “unlikely” and “somewhat likely” may be shorter than the distance between “somewhat likely” and “very likely”. How to use and get result by Ordinal Regression: Clink this link for PDF                                                                                                                                                                                                                                                                                                                        PDF source: http://www.norusis.com

The Axeda Platform has a mature data model that's important to understand when planning to build applications. First, this will introduce the existing objects and how they relate to each other. Axeda Agents can communicate Model – the definition of a type of asset. The model consists of a set of dataitems (its inputs and outputs) and alarms. The platform applies logic to a model, so as assets grow, the system is scalable in terms of management. Asset – or sometimes called Device. An asset has an identifier called a Serial Number which must be unique within its model. Agents report information in terms of the asset. Logic is applied to data and events about that asset. Dataitem – a named reading, such as a sensor or computer value. Dataitems are timestamped values in a sequence. For example, hourly temperatures, or odometer readings, or daily usage statistics. The number of named dataitems is unlimited. Dataitems can be written as well as read, so a value can be sent to an “output”. A dataitem can be a Digital (boolean), Analog (real value) or a String. Mobile Location - a lat/long pair typically read from GPS. This is used to map assets as they move. Alarms – have a name, severity, description, active flag, timestamp, and optional embedded dataitem and value. Alarms sent from an agent may result from logic that detects a condition, or from traps, error codes, etc. An alarm indicates something that's wrong. Files – arbitrary files can be uploaded from an agent. Files are sent with a Hint string. This is metadata that allows rules to process the file based on something other than the file extension. Files are often uploaded when an alarm has been raised, or on demand from a user or rule. Axeda agents have flexible ways to send and receive this information based on time, data changes, user request, etc. The Adaptive Machine Messaging Protocol (AMMP) allows anyone to make an agent that interacts with Axeda Platform using the same data model. Axeda Platform is asset-centric. An asset is an instance of a Model. Each asset is identified by its Model and Serial Number pair. Associated with an asset is Organization (typically the customer) Location or home of the asset (a street address). A location is in a Region. Contacts – people who have a relationship to the asset. Contacts have a role, such as Owner, or Service Agent. Asset Groups – assets are members of groups, and groups can be used to grant privileges, for navigation, or to apply commands. Properties – are additional named attributes of an asset. Properties do not have a time series history like a dataitem. The value of a property may be used to dynamically group assets. Condition – the current condition may be good, warning, error, or needs maintenance, based on the existence of alarms, for example. And, of course, dataitems, alarms and files. Information is processed and organized in the context of an asset, but the processing is managed for models. The only scalable way to manage a lot of assets is to apply rules by kind of asset, not individual assets. Rules apply logic to data as it happens. When a new dataitem is reported, a rule may check against its threshold. When an alarm is created, a rule may create a trouble ticket, or notify the user. All types of rules in the platform – Expression Rules, State Machines, and Threshold Rules – are event based. Rules apply to models, or sometimes to all (such as a standard way of notification on Alarms). The only exceptions are rules that apply to user logins and rules on a system timer. Software packages are another entity in the Platform. Packages are used to distribute files, software, patches, etc. and to script some commands around their delivery. So packages often upgrade or patch software, or load a new option of help file. Packages are defined for a model, and the deployment may be automatic or manual, to one or many.User logins are members of user groups. User groups have both privileges (what they can do) and visibility (which assets they can see). User group visibility allows the group to access assets in an Asset Group, or a Model or Region. How do solutions take advantage of this? Dataitems can be configured to store no data, current value, or history. History is needed if you want to see the temperature plot over the last day. Many times, current value is all that's needed to process rules and see the state of an asset. The option not to store a dataitem makes sense if the dataitem is only used to run a rule, or if it will just be sent to another application. An agent can send a dataitem string to the server, and the server puts the string on the Message Queue to deliver to another application. In a pass-through mode, the dataitem doesn't need to be stored at all. A similar situation is if a string dataitem is parsed by the rule calling a Groovy script. The script can parse the string (which may be XML or part of a log file) and use the SDK to do some action. Alarms are almost always used to notify people that they should do something. Alarms in Axeda have a lifecycle that corresponds to how people interact with them. An alarm begins its life when it's created. From that point, the alarm can be Acknowledged – this means that someone has seen it Escalated – the alarm condition hasn't been fixed for some time Closed – the end of the Alarm's life Suppressed – the alarm is logged in the history, but users don't see it. Set an alarm to suppressed when its just an annoyance and doesn't have any action required. Disabled – occurrences of this alarm are thrown away. Rules don't even see them. The Suppressed and Disabled modes are applied to an alarm of a given name, because they affect all future alarms by that name. Files are uploaded for a few reasons. Log files are typically uploaded so a service tech can diagnose a problem. Data files can be uploaded so a script or external system can process the file and take appropriate action. This can be another way of sending information that doesn't fit in a dataitem. The configuration of an asset – both hardware and software – is called Inventory, and the inventory of assets is important in diagnostics, planning spare parts, knowing what patch to apply, and many more. Extended Objects are attributes that can be added to the objects described here, or can be complete objects that live on their own. Your application can read and write these objects or attributes, and query them. The use is up to you. Resources You can find more information on the architecture of the platform in the Introduction to the Axeda Platform. The Platform SDK and Web Services expose most of these objects for configuration as well as runtime. That means an application can provision models and assets, create the rules and apply them to models, then monitor the behavior of assets, all through Web Services.

Sampling Strategy​ This Blog Post will cover the 4 sampling Strategies that are available in ThingWorx Analytics.  It will tell you how the sampling strategy runs behind the scenes, when you may want to use that strategy, and will give you the pros and cons of each strategy. SAMPLE_WITH_REPLACEMENT This strategy is not often used by professionals but still may be useful in certain circumstances.  When you sample with replacement, the value that you randomly selected is then returned to the sample pool.  So there is a chance that you can have the same record multiple times in your sample. Example Let’s say you have a hat that contain 3 cards with different people’s names on them. John Sarah Tom Let’s say you make 2 random selections. The first selection you pull out the name Tom. When you sample with replacement, you would put the name Tom back into the hat and then randomly select a card again.  For your second selection, it is possible to get another name like Sarah, or the same one you selected, Tom. Pros May find improved models in smaller datasets with low row counts Cons The Accuracy of the model may be artificially inflated due to duplicates in the sample SAMPLE_WITHOUT_REPLACEMENT This is the default setting in ThingWorx Analytics and the most commonly used sampling strategy by professionals.  The way this strategy works is after the value is randomly selected from the sample pool, it is not returned.  This ensures that all the values that are selected for the sample, are unique. Example Let’s say you have a hat that contain 3 cards with different people’s names on them. John Sarah Tom Let’s say you make 2 random selections. The first selection you pull out the name Tom. When you sample without replacement, you would randomly select a card from the hat again without adding the card Tom.  For your second selection, you could only get the Sarah or John card. Pros This is the sampling strategy that is most commonly used It will deliver the best results in most cases Cons May not be the best choice if the desired goal is underrepresented in the dataset UPSAMPLE_AND_SAMPLE_WITHOUT_REPLACEMENT This is useful when the desired goal is underrepresented in the dataset.  The features that represent the desired outcome of the goal are copied multiple times so they represent a larger share of the total dataset. Example Let’s say you are trying to discover if a patient is at risk for developing a rare condition, like chronic kidney failure, that affects around .5% of the US population.  In this case, the most accurate model that would be generated would say that no one will get this condition, and according to the numbers, it would be right 99.5% of the time.  But in reality, this is not helpful at all to the use case since you want to know if the patient is at risk of developing the condition. To avoid this from happening, copies are made of the records where the patient did develop the condition so it represents a larger share of the dataset.  Doing this will give ThingWorx Analytics more examples to help it generate a more accurate model. Pros Patterns from the original dataset remain intact Cons Longer training time DOWNSAMPLE_AND_SAMPLE_WITHOUT_REPLACEMENT This is also useful when the desired goal is underrepresented in the dataset. In downsample and sample without replacement, some features that do not represent the desired goal outcome are removed. This is done to increase the desired features percentage of the dataset. Example Let’s continue using the medical example from above.  Instead of creating copies of the desired records, undesired record are removed from the dataset.  This causes the records where patients did develop the condition to occupy a larger percentage of the dataset. Pros Shorter training time Cons Patterns from the original dataset may be lost

Expression rules are the heart of the Axeda Platforms processing capability. These rules have an If-Then-Else structure that's easy to create and understand. We think they're like a formula in a spreadsheet. For example, say your asset has a dataitem reading for temperature: IF: temperature > 80 THEN: CreateAlarm("High Temp", 100)                      This rule compares the temperature to 80 every time a reading is received. When this happens, the rule creates an alarm with name "High Temp" and severity 100. Dataitems represent readings from an asset. They are typically sensors or monitoring parameters in an application. But also think of dataitems as variables. The rule can be changed to IF: temperature > threshold                      so that each asset has its own threshold that can be adjusted independently. Look at the complete list of Expression Rule triggers - the events that trigger a rule to run variables - the information you can access in an expression functions - the functions that can be used within an expression actions - these are called in the Then or Else part of an expression to make something happen A rule can calculate a new value. For example, if you wanted to know the max temperature IF: temperature > maxTemperature THEN: SetDataItem("maxTemperature" temperature) To convert a temperature in celsius to fahrenheit IF: temperature THEN: SetDataItem("tempF", temperature*9/5 + 32) The If simply names the variable, so any change to that variable triggers the rule to run. There may be lots of other dataitems reported for an asset, and changes to the other dataitems should not recalculate the temperature. When rules should run only when an asset is in a particular mode or state, or when there is a complex sequence to model, read about how State Machines come to the rescue. Creating and Testing an Expression Rule ​ We're going to create a simple Expression Rule and show it running in a few steps. Above, you saw a rule that created an alarm when temperature > 80. Now, we will make one that converts a temperature in F to one in C. An Expression Rule consists of a few things: Name Description - an optional field to describe the rule Trigger - what makes this rule run? The trigger tells the rule if it applies to Alarms, Data, Files, or many others. If - the logic expression for the condition to evaluate Then - the logic to run if the condition is true Else - the logic to run if the condition is false To begin, log into an Axeda Platform instance. Navigate to the Manage tab Select ​New​, then ​Expression Rule​ Enter this Expression Rule information Name: TempConvert Type: Data Description: Enabled: Leave checked If: TempC Then: SetDataItem("TempF", TempC*9/5 + 32) If you click on functions or scroll down for actions in the Expression Tree, you will see a description in Details. Click the Apply to Asset​ button to select models and specific assets to apply this rule to. Now that you have an Expression Rule, lets try it. Testing the Expression Rule (NEEDS UPDATING) You can test the expression rule by simulating the TempC data using Axeda Simulator, as instructed below. Or, you can use the Expression Rules Debugger to simulate the reading and display the results. For information about using the Expression Rules Debugger, see the Expression Rules Debugger documentation in the on-line Help system.Simulate a TempC reading Launch the Axeda Simulator The Axeda Simulator will launch in a new browser window Enter your registered email address, Developer Connection password, and click Login.       Select asset1 from the Asset dropdown. Under the Data tab, enter the dataitem name TempC, and a value like 28: Then Click Send. To see the exciting result, go back to the Platform window and navigate to the Service tab: and you should see that 28C = 82.4F. You created an Expression Rule that triggers when a value of TempC is received, and creates a new dataitem TempF with a calculated value. This rule applies to your model, but if you had many models of assets, it could apply to as many as you want. You could change the rule to do the conversion only If: TempC > 9 and simulate inputs to see that this is the new behavior. Further Reading Read about how Rule Timers can trigger rules to run on a scheduled basis. (TODO)

I know most of us very happily use the Administrator account in Thingworx, however this is bad bad practice for development and even administration of the platform! Administrator is there by default and should be used to set up your initial users, which should include your Actual Platform Administrator (with a strong password of course) After that change the Administrator Password and Remove them from the Administrators group. I recommend this as a Best Practice even in your own Development environments, but especially in Runtime. Your very first steps would like: Install Thingworx Log in as Administrator Set up the new Platform Administrator account Remove Administrator from Administrators group Change Administrator password.

Create Custom Business Logic    Overview   This project will introduce you to creating your first ThingWorx Business Rules Engine.   Following the steps in this guide, you will know how to create your business rules engine and have an idea of how you might want to develop your own. We will teach you how to use your data model with Services, Events, and Subscriptions to establish a rules engine within the ThingWorx platform.   NOTE: This guide's content aligns with ThingWorx 9.3. The estimated time to complete this guide is 60 minutes.    Step 1: Completed Example   Download the attached, completed files for this tutorial: BusinessLogicEntities.xml.   The BusinessLogicEntities.xml file contains a completed example of a Business Rules Engine. Utilize this file to see a finished example and return to it as a reference if you become stuck during this guide and need some extra help or clarification. Keep in mind, this download uses the exact names for entities used in this tutorial. If you would like to import this example and also create entities on your own, change the names of the entities you create.   Step 2: Rules Engine Introduction   Before implementing a business rule engine from scratch, there are a number of questions that should first be answered. There are times in which a business rule engine is necessary, and times when the work can be down all within regular application coding.   When to Create a Rules Engine: When there are logic changes that will often occur within the application. This can be decisions on how to do billing based on the state or how machines in factories should operate based on a release. When business analysts are directly involved in the development or utilization of the application. In general, these roles are often non-technical, but being involved with the application directly will mean the need for a way to make changes. When a problem is highly complex and no obvious algorithm can be created for the solution. This often covered scenarios in which an algorithm might not be the best option, but a set of conditions will suffice.   Advantages of a Rules Engine The key reward is having an outlet to express solutions to difficult problems than can be easily verifiable. A consolidated knowledge base for how a part of a system works and a possible source of documentation. This source of information provides people with varying levels of technical skill to all have insight into a business model.   Business Logic with ThingWorx Core Platform: A centralized location for development, data management, versioning, tagging, and utilization of third party applications. The ability to create the rules engine within the ThingWorx platform and outside of ThingWorx platform. Being that the rules engine can be created outside of the ThingWorx platform, third party rules engines can be used. The ThingWorx platform provides customizable security and provided services that can decrease the time in development.     Step 3: Establish Rules   In order to design a business rules engine and establish rules before starting the development phase, you must capture requirements and designate rule characteristics.   Capture Requirements The first step to building a business rules engine is to understand the needs of the system and capture the rules necessary for success.   Brainstorm and discuss the conditions that will be covered within the rules engine Construct a precise list Identify exact rules and tie them to specific business requirements.   Each business rule and set of conditions within the business rule will need to be independent of other business rules. When there are several scenarios involved, it is best to create multiple rules – one handling each. When business rules are related to similar scenarios, the best methodology is to group the rules into categories.   Category Description Decision Rules Set of conditions regarding business choices Validation Rules Set of conditions regarding data verifications Generation Rules Set of conditions used for data object creation in the system Calculation Rules Set of conditions that handle data input utilized for computing values or assessments   Designate Rule Characteristics Characteristics for the rules include, but are not limited to: Naming conventions/identifiers Rule grouping Rule definition/description Priority Actions that take place in each rule.   After this is completed, you will be ready to tie business requirements to business rules, and those directly to creating your business rules engine within the platform.   Rules Translation to ThingWorx There are different methods for how the one to one connections can be made between rules and ThingWorx. The simplified method below shows one way that all of this can be done within the ThingWorx platform:   Characteristic  ThingWorx Aspect Rule name/identifier Service Name Ruleset  Thing/ThingTemplate Rule definition  Service Implementation Rule conditions Service Implementation Rule actions Service Implementation Data management DataTables/Streams   Much of the rule implementation is handled by ThingWorx Services using JavaScript. This allows for direct access to data, other provided Services, and a central location for all information pertaining to a set of rules. The design provided above also allows for easier testing and security management.   Step 4: Scenario Business Rule Engine    An important aspect to think about before implementing your business rules engine, is how the Service implementation will flow.   Will you have a singular entry path for the entire rules engine? Or will you have several entries based on what is being requested of it? Will you have create only Services to handle each path? Or will you create Events and Subscriptions (Triggers and Listeners) in addition to Services to split the workload?   Based on how you answer those questions, dictates how you will need to break up your implementation. The business rules for the delivery truck scenario are below. Think about how you would break down this implementation.   High Level Flow 1 Customer makes an order with a Company (Merchant). 1.A Customer to Merchant order information is created. 2 The Merchant creates an order with our delivery company, PTCDelivers. 2.A Merchant order information is populated. 2.B Merchant sets delivery speed requested. 2.C Merchant sets customer information for the delivery. 3 The package is added to a vehicle owned by PTCDelivers. 4 The vehicle makes the delivery to the merchant's customer.   Lower Level: Vehicles 1 Package is loaded onto vehicle 1.i Based on the speed selected, add to a truck or plane. 1.ii Ground speed option is a truck. 1.iii Air and Expedited speed options are based on planes usage and trucks when needed. 2 Delivery system handles the deliveries of packages 3 Delivery system finds the best vehicle option for delivery 4 An airplane or truck can be fitted with a limited number of packages.   Lower Level: Delivery 1 Delivery speed is set by the customer and passed on to PTCDelivers. 2 Delivery pricing is set based on a simple formula of (Speed Multiplier * Weight) + $1 (Flat Fee). 2.i Ground arrives in 7 days. The ground speed multiplier is $2. 2.ii Air arrives in 4 days. The air speed multiplier is $8. 2.iii Expedited arrives in 1 day. The expedited speed multiplier is $16. 3 Deliveries can be prioritized based on a number of outside variables. 4 Deliveries can be prioritized based on a number of outside variables. 5 Bulk rate pricing can be implemented.   How would you implement this logic and add in your own business logic for added profits? Logic such as finding the appropriate vehicle to make a delivery can be handled by regular Services. Bulk rates, prioritizing merchants and packages, delivery pricing, and how orders are handled would fall under Business Logic. The MerchantThingTemplate Thing contains a DataChange Subscription for it's list of orders. This Subscription triggers an Event in the PTCDelivers Thing.   The PTCDelivers Thing contains an Event for new orders coming in and a Subscription for adding orders and merchants to their respective DataTables. This Subscription can be seen as the entry point for this scenario. Nevertheless, you can create a follow-up Service to handle your business logic. We have created the PTCDeliversBusinessLogic to house your business rules engine.   Step 5: Scenario Data Model Breakdown   This guide will not go into detail of the data model of the application, but here is a high level view of the roles played within the application.   Thing Shapes ClientThingShape Shape used to represent the various types of clients the business faces (merchants/customers). VehicleThingShape Shape used to represent different forms of transportation throughout the system.   Templates PlaneThingTemplate Template used to construct all representations of a delivery plane. TruckThingTemplate Template used to construct all representations of a delivery truck. MerchantThingTemplate Template used to construct all representations of a merchant where goods are purchased from. CustomerThingTemplate Template used to construct all representations of a customer who purchases goods.   Things/Systems PTCDeliversBusinessLogic This Thing will hold a majority of the business rule implementation and convenience services. PTCDelivers A Thing that will provide helper functions in the application.   DataShapes PackageDeliveryDataShape DataShape used with the package delivery event. Will provide necessary information about deliveries. PackageDataShape DataShape used for processing a package. OrderDataShape DataShape used for processing customer orders. MerchantOrderDataShape DataShape used for processing merchant orders. MerchantDataShape DataShape used for tracking merchants.   DataTables OrdersDatabase DataTable used to store all orders made with customers. MerchantDatabase DataTable used to store all information for merchants.     Step 6: Next Steps   Congratulations! You've successfully completed the Create Custom Business Logic guide, and learned how to: Create business logic for IoT with resources provided in the ThingWorx platform Utilize the ThingWorx Edge SDK platforms with a pre-established business rule engine   We hope you found this guide useful.    The next guide in the Design and Implement Data Models to Enable Predictive Analytics learning path is Implement Services, Events, and Subscriptions.     

Check out this new KCS article which links to all known best practice documents available for ThingWorx. This article will get larger in time as more articles are published related to the Dos and Don'ts of building an IoT application! Do you know when to use timers, and where to implement their subscriptions? How about ensuring info tables are used at the proper time, and data tables at others? Pesky performance issues wherein ThingWorx runs slow for apparently no reason? All of these questions and more are addressed here!

We are pleased to announce that the Expert Sessions video series is now available in the ThingWorx Community. We are kicking off this availability with a new space dedicated to these helpful technical videos. In the first round of videos, we are highlighting two ThingWorx Foundation videos that are designed to provide foundational knowledge to get you up and running on the ThingWorx IoT platform. New Expert Sessions Available Now ThingWorx Foundation - Installation is an introduction to installing the ThingWorx platform. The video includes information on the environment, prerequisites, and configuration steps when installing ThingWorx, and includes walkthroughs of installing with H2 and PostgreSQL databases, an introduction and demonstration of the Linux installation script, solutions to common installation problems and more. ThingWorx Foundation - Scalability talks about platform sizing with dependency on the type of environment and correlated scalability options. The video educates you about federation and high availability as well as provides visual diagrams to understand the architecture of different ThingWorx solutions. What is an Expert Session? Expert Sessions are focused, technical webcasts (both recorded and live) where PTC subject matter experts share knowledge and best practices on topics related to the design, development, deployment and operation of PTC software. Expert Sessions are designed using five categories: Get Started, Design, Develop, Deploy, and Operate. Additional Expert Sessions will be highlighted here in the ThingWorx Community every few weeks. Visit the Online Success Guide to access our Expert Session videos at any time as well as additional information about ThingWorx training and services.

Insight into Performance Ensure asset availability by managing asset condition Identify potential equipment failure through rule-based alerts Faster notification providing more time to respond Access to real-time performance data enables time-sensitive decision making Review performance history of equipment to improve troubleshooting Key indicators/signals of future failures View asset information and sensor history to understand context of alert View multiple sensor data and trends to understand any correlations across sensors Diagnose and Understand Accelerate diagnostic processes to understand the root cause of issues more quickly prior to the customer reporting the issue Improve interactive diagnostics processes by incorporating connected machine data View detailed sensor information for speedy issue identification Automate service issue notifications Machine created events to alert of potential problems Notifications to service technicians or service dispatch systems about potential problems Resolve Service Issues Increase equipment uptime by remotely resolving equipment issues before they occur to improve customer retention and reduce service cost Leverage remote access to connected equipment Dashboard to view alerts and summary across all customers and assets Identify common issues across multiple assets Prevent unnecessary onsite service visits with remote service capabilities Capture logs and diagnostic information for speedy issue resolution Remote access equipment to perform diagnostics and resolve issues through configuration changes

Hi everybody, In this blogpost I want to share with you my local ThingWorx installation, with some optimizations that I did for local development. -use the -XX:+UseConcMarkSweepGC . This uses the older Garbage Collector from the JVM, instead of the newer G1GC recommended by the ThingWorx Installation guide since version 7.2. The advantage of ConcMarkSweepGC is that the startup time is faster and the total memory footprint of the Tomcat is far lower than G1GC. -use -agentlib:jdwp=transport=dt_socket,address=1049,server=y,suspend=n. This allows using your Java IDE of choice to connect directly to the Tomcat server, then debugging your Extension code, or even the ThingWorx code using the Eclipse Class Decompilers for example. Please modify the 1049 to your port of choice for exposing the server debugging port. -use -Dcom.sun.management.jmxremote -Dcom.sun.management.jmxremote.port=60000 -Dcom.sun.management.jmxremote.ssl=false                  -Dcom.sun.management.jmxremote.authenticate=false           This sets up the server to allow JMX monitoring. I usually use VisualVM from the JDK bin folder, but you can use any JMX monitoring tool.           This uses no Authentication, no SSL and uses port 6000 - modify if you need. I usually startup Tomcat manually from a folder via startup.bat, and the setenv.bat looks like: set JAVA_HOME=C:\Program Files\Java\jdk1.8.0_102 set JRE_HOME=C:\Program Files\Java\jdk1.8.0_102 set THINGWORX_PLATFORM_SETTINGS=D:\Work\servers\apache-tomcat-8.0.33 // this is where the platform-settings.json file is located set CATALINA_OPTS=-d64 -XX:+UseNUMA -XX:+UseConcMarkSweepGC -Dfile.encoding=UTF-8 -agentlib:jdwp=transport=dt_socket,address=1049,server=y,suspend=n -Dcom.sun.management.jmxremote -Dcom.sun.management.jmxremote.port=60000 -Dcom.sun.management.jmxremote.ssl=false -Dcom.sun.management.jmxremote.authenticate=false In this mode I can look at any errors in almost real time from the console and it makes killing the server for Java Extension reload a breeze -> Ctrl+C Please don't hesitate to provide feedback on this document, I certainly welcome it. Be warned: THESE ARE NOT PRODUCTION SETTINGS. Best regards, Vladimir

OpenDJ is a directory server which is also the base for WindchillDS. It can be used for centralized user management and ThingWorx can be configured to login with users from this Directory Service.   Before we start Pre-requisiste Docker on Ubuntu JKS keystore with a valid certificate JKS keystore is stored in /docker/certificates - on the machine that runs the Docker environments Certificate is generated with a Subject Alternative Name (SAN) extension for hostname, fully qualified hostname and IP address of the opendj (Docker) server Change the blue phrases to the correct passwords, machine names, etc. when following the instructions If possible, use a more secure password than "Password123456"... the one I use is really bad   Related Links https://hub.docker.com/r/openidentityplatform/opendj/ https://backstage.forgerock.com/docs/opendj/2.6/admin-guide/#chap-change-certs https://backstage.forgerock.com/knowledge/kb/article/a43576900   Configuration Generate the PKCS12 certificate Assume this is our working directory on the Docker machine (with the JKS certificate in it)   cd /docker/certificates   Create .pin file containing the keystore password   echo "Password123456" > keystore.pin   Convert existing JKS keystore into a new PKCS12 keystore   keytool -importkeystore -srcalias muc-twx-docker -destalias server-cert -srckeystore muc-twx-docker.jks -srcstoretype JKS -srcstorepass `cat keystore.pin` -destkeystore keystore -deststoretype PKCS12 -deststorepass `cat keystore.pin` -destkeypass `cat keystore.pin`   Export keystore and Import into truststore   keytool -export -alias server-cert -keystore keystore -storepass `cat keystore.pin` -file server-cert.crt keytool -import -alias server-cert -keystore truststore -storepass `cat keystore.pin` -file server-cert.crt     Docker Image & Container Download and run   sudo docker pull openidentityplatform/opendj sudo docker run -d --name opendj --restart=always -p 389:1389 -p 636:1636 -p 4444:4444 -e BASE_DN=o=opendj -e ROOT_USER_DN=cn=Manager -e ROOT_PASSWORD=Password123456 -e SECRET_VOLUME=/var/secrets/opendj -v /docker/certificates:/var/secrets/opendj:ro openidentityplatform/opendj   After building the container, it MUST be restarted immediately in order for recognizing the new certificates   sudo docker restart opendj   Verify that the certificate is the correct one, execute on the machine that runs the Docker environments: openssl s_client -connect localhost:636 -showcerts   Load the .ldif Use e.g. JXplorer and connect   Select the opendj node LDIF > Import File (my demo breakingbad.ldif is attached to this post) Skip any warnings and messages and continue to import the file   ThingWorx Tomcat If ThingWorx runs in Docker as well, a pre-defined keystore could be copied during image creation. Otherwise connect to the container via commandline: sudo docker exec -it <ThingworxImageName> /bin/sh Tomcat configuration cd /usr/local/openjdk-8/jre/lib/security openssl s_client -connect 10.164.132.9:636 -showcerts Copy the certifcate between BEGIN CERTIFACTE and END CERTIFICATE of above output into opendj.pem, e.g. echo "<cert_goes_here>" > opendj.pem Import the certificate keytool -keystore cacerts -import -alias opendj -file opendj.pem -storepass changeit   ThingWorx Composer As the IP address is used (the hostname is not mapped in Docker container) the certificate must have a SAN containing the IP address     Only works with the TWLDAPExample Directory Service not the ADDS1, because ADDS1 uses hard coded Active Directory queries and structures and therefore does not work with OpenDJ. User ID (cn) must be pre-created in ThingWorx, so the user can login. There is no automatic user creation by the Directory Service. Make sure the Thing is Enabled under General Information   Appendix LDAP Structure for breakingbad.ldif cn=Manager / Password123456 All users with password Password123456    

This tutorial applies to Axeda version 6.1.6+, with sections applicable to 6.5+ (indicated below) Custom objects (or Groovy scripts) are the backbone of Axeda custom applications.  As the developer, you decide what content type to give the data returned by the script. What this tutorial covers? This tutorial provides examples of outputting data in different formats from Groovy scripts and consuming that data via Javascript using the jQuery framework.  While Javascript and jQuery are preferred by the Axeda Innovation team, any front end technology that can consume web services can be used to build applications on the Axeda Machine Cloud.  On the same note, the formats discussed in this article are only a few examples of the wide variety of content types that Groovy scripts can output via Scripto.  The content types available via Scripto are limited only by their portability over the TCP protocol, a qualification which includes all text-based and downloadable binary mime types.  As of July 2013, the UDP protocol (content streaming) is not supported by the current version of the Axeda Platform. Formats discussed in this article: 1) JSON 2) XML 3) CSV 4) Binary content with an emphasis on image files (6.5+) For a tutorial on how to create custom objects that work with custom applications, check out Using Google Charts API with Scripto.  For a discussion of what Scripto is and how it relates to Groovy scripts and Axeda web services, take a look at Unleashing the Power of the Axeda Platform via Scripto. Serializing Data JSON For those building custom applications with Javascript, serializing data from scripts into JSON is a great choice, as the data is easily consumable as native Javascript objects. The net.sf.json JSON library is available to use in the SDK.  It offers an easy way to serialize objects on the Platform, particularly v2 SDK objects. import net.sf.json.JSONArray import static com.axeda.sdk.v2.dsl.Bridges.* def asset = assetBridge.findById(parameters.assetId) def response = JSONArray.fromObject(asset).toString(2) return ["Content-Type": "application/json", "Content": response] Outputs: [{     "buildVersion": "",     "condition": {         "detail": "",         "id": "3",         "label": "",         "restUrl": "",         "systemId": "3"     },     "customer": {         "detail": "",         "id": "2",         "label": "Default Organization",         "restUrl": "",         "systemId": "2"     },     "dateRegistered": {         "date": 11,         "day": 1,         "hours": 18,         "minutes": 7,         "month": 2,         "seconds": 49,         "time": 1363025269253,         "timezoneOffset": 0,         "year": 113     },     "description": "",     "detail": "testasset",     "details": null,     "gateways": [],     "id": "12345",     "label": "",     "location": {         "detail": "Default Organization",         "id": "2",         "label": "Default Location",         "restUrl": "",         "systemId": "2"     },     "model": {         "detail": "testmodel",         "id": "2345",         "label": "standalone",         "restUrl": "",         "systemId": "2345"     },     "name": "testasset",     "pingRate": 0,     "properties": [         {             "detail": "",             "id": "1",             "label": "TestProperty",             "name": "TestProperty",             "parentId": "2345",             "restUrl": "",             "systemId": "1",             "value": ""         },         {             "detail": "",             "id": "4",             "label": "TestProperty0",             "name": "TestProperty0",             "parentId": "2345",             "restUrl": "",             "systemId": "4",             "value": ""         },         {             "detail": "",             "id": "3",             "label": "TestProperty1",             "name": "TestProperty1",             "parentId": "2345",             "restUrl": "",             "systemId": "3",             "value": ""         },         {             "detail": "",             "id": "2",             "label": "TestProperty2",             "name": "TestProperty2",             "parentId": "2345",             "restUrl": "",             "systemId": "2",             "value": ""         }     ],     "restUrl": "",     "serialNumber": "testasset",     "sharedKey": [],     "systemId": "12345",     "timeZone": "GMT" }] This output can be traversed as Javascript object with its nodes accessible using dot (.) notation. For example, if you set the above JSON as the content of variable "json", you can access it in the following way, without any preliminary parsing needed: assert json[0].condition.id == 3 If you use jQuery, a Javascript library, feel free to make use of axeda.js, which contains utility functions to pass data to and from the Axeda Platform.  One function in particular is used in most example custom applications found on this site, the axeda.callScripto function.  It relies on the jQuery ajax function to make the underlying call. /**   * makes a call to the enterprise platform services with the name of a script and passes   * the script any parameters provided.   *   * default is GET if the method is unknown   *   * Notes: Added POST semantics - plombardi @ 2011-09-07   *   * original author: Zack Klink & Philip Lombardi   * added on: 2011/7/23   */ // options - localstoreoff: "yes" for no local storage, contentType: "application/json; charset=utf-8", axeda.callScripto = function (method, scriptName, scriptParams, attempts, callback, options) {   var reqUrl = axeda.host + SERVICES_PATH + 'Scripto/execute/' + scriptName + '?sessionid=' + SESSION_ID   var contentType = options.contentType ? options.contentType : "application/json; charset=utf-8"   var local   var daystring = keygen()   if (options.localstoreoff == null) {   if (localStorage) {   local = localStorage.getItem(scriptName + JSON.stringify(scriptParams))   }   if (local != null && local == daystring) {   return dfdgen(reqUrl + JSON.stringify(scriptParams))   } else {   localStorage.setItem(scriptName + JSON.stringify(scriptParams), daystring)   }   }   return $.ajax({   type: method,   url: reqUrl,   data: scriptParams,   contentType: contentType,   dataType: "text",   error: function () {   if (attempts) {   expiredSessionLogin();   setTimeout(function () {   axeda.callScripto('POST', scriptName, scriptParams, attempts - 1, callback, options)   }, 1500);   }   },   success: function (data) {   if (options.localstoreoff == null) {   localStorage.setItem(reqUrl + JSON.stringify(scriptParams), JSON.stringify([data]))   }   if (contentType.match("json")) {   callback(unwrapResponse(data))   } else {   callback(data)   }   }   }) }; Using the axeda.callScripto function: var postToPlatform = function (scriptname, callback, map) {         var options = {             localstoreoff: "yes",             contentType: "application/json; charset=utf-8"         }        // Javascript object "map" has to be stringified to post to Axeda Platform         axeda.callScripto("POST", scriptname, JSON.stringify(map), 2, function (json) {             // callback gets the JSON object output by the Groovy script             callback(json)         }, options)     } The JSON object is discussed in more detail here. Back to Top XML XML is the preferred language of integration with external applications and services. Groovy provides utilities to make XML serialization a trivial exercise. import groovy.xml.MarkupBuilder import static com.axeda.sdk.v2.dsl.Bridges.* def writer = new StringWriter() def xml = new MarkupBuilder(writer) def findAssetResult = assetBridge.find(new AssetCriteria(modelNumber: parameters.modelName)) // find operation returns AssetReference class. Contains asset id only def assets = findAssetResult.assets      xml.Response() {   Assets() {   assets.each { AssetReference assetRef ->   def asset = assetBridge.findById(assetRef.id)               // asset contains a ModelReference object instead of a Model.  ModelReference has a detail property, not a name property   Asset() {   id(asset.id)   name(asset.name)   serial_number(asset.serialNumber)   model_id(asset.model.id)   model_name(asset.model.detail)   }   }   }   } return ['Content-Type': 'text/xml', 'Content': writer.toString()] Output: <Assets>   <Asset>   <id>98765</id>   <name>testasset</name>   <serial_number>testasset</serial_number>   <model_id>4321</model_id>   <model_name>testmodel</model_name>   </Asset> </Assets Although XML is not a native Javascript object as is JSON, Javascript libraries and utilities are available for parsing XML into an object traversable in Javascript. For more information on parsing XML in Javascript, see W3 Schools XML Parser.  For those using jQuery, check out the jQuery.parseXML function. Back to Top Outputting Files (Binary content types) CSV CSV comes in handy for spreadsheet generation as it is compatible with Microsoft Excel. The following example is suitable for Axeda version 6.1.6+ as it makes use of the Data Accumulator feature to create a downloadable file. import com.axeda.drm.sdk.device.ModelFinder import com.axeda.drm.sdk.Context import com.axeda.drm.sdk.scripto.Request import com.axeda.common.sdk.id.Identifier import com.axeda.drm.sdk.device.Model import com.axeda.drm.sdk.device.DataItem import com.axeda.drm.sdk.device.DataItemValue import com.axeda.drm.sdk.data.DataValue import com.axeda.drm.sdk.device.DeviceFinder import com.axeda.drm.sdk.device.Device import com.axeda.drm.sdk.mobilelocation.MobileLocation import com.axeda.drm.sdk.data.DataValueList import com.axeda.drm.sdk.data.CurrentDataFinder import com.axeda.drm.sdk.mobilelocation.CurrentMobileLocationFinder import groovy.xml.MarkupBuilder import com.axeda.platform.sdk.v1.services.ServiceFactory /* * ExportObjectToCSV.groovy * * Creates a csv file from either all assets of a model of a single asset that can then be used to import them back into another system. * * @param model        -   (REQ):Str model name. * @param serial        -   (OPT):Str serial number. * * @author Sara Streeter <sstreeter@axeda.com> */ def writer = new StringWriter() def xml = new MarkupBuilder(writer) InputStream is try {    Context CONTEXT = Context.getSDKContext()    ModelFinder modelFinder = new ModelFinder(CONTEXT)     modelFinder.setName(Request.parameters.model)    Model model = modelFinder.find()    DeviceFinder deviceFinder = new DeviceFinder(CONTEXT)    deviceFinder.setModel(model)    List<Device> devices = [] def exportkey = model.name Device founddevice if (Request.parameters.serial){     deviceFinder.setSerialNumber(Request.parameters.serial)    founddevice = deviceFinder.find()    logger.info(founddevice?.serialNumber)    if (founddevice != null){    devices.add(founddevice)    }    else throw new Exception("Device ${Request.parameters.serial} cannot be found.")    exportkey += "${founddevice.serialNumber}" } else {     devices = deviceFinder.findAll()     exportkey += "all" } // use a Data Accumulator to store the information def dataStoreIdentifier = "FILE-CSV-export_____" + exportkey def daSvc = new ServiceFactory().dataAccumulatorService if (daSvc.doesAccumulationExist(dataStoreIdentifier, devices[0].id.value)) {   daSvc.deleteAccumulation(dataStoreIdentifier, devices[0].id.value) } List<DataItem> dataItemList = devices[0].model.dataItems def firstrow = [ "model", "serial", "devicename", "conditionname", "currentlat","currentlng" ]                     def tempfirstrow = dataItemList.inject([]){list, dataItem ->             list << dataItem.name;             list         }         firstrow += tempfirstrow            firstrow = firstrow.join(',')         firstrow += '\n'         daSvc.writeChunk(dataStoreIdentifier, devices[0].id.value, firstrow);     CurrentMobileLocationFinder currentMobileLocationFinder = new CurrentMobileLocationFinder(CONTEXT) devices.each{ device ->                 CurrentDataFinder currentDataFinder = new CurrentDataFinder(CONTEXT, device)                 currentMobileLocationFinder.deviceId = device.id.value                 MobileLocation mobileLocation = currentMobileLocationFinder.find()                 def lat = 0                 def lng = 0                 if (mobileLocation){                     lat = mobileLocation?.lat                     lng = mobileLocation?.lng                 }                 def row =                 [                     device.model.name,                     device.serialNumber,                     device.name,                     device.condition?.name,                     lat,                     lng                     ]                                     def temprow = dataItemList.inject([]){ subList,dataItem ->                         DataValue value = currentDataFinder.find(dataItem.name)                                             def val = "NULL"                         val = value?.asString() != "?" ? value?.asString() : val                         subList <<  val                         subList                     }                 row += temprow                 row = row.join(',')                 row += '\n'                 daSvc.writeChunk(dataStoreIdentifier, devices[0].id.value, row);             }    // stream the data accumulator to create the file is = daSvc.streamAccumulation(dataStoreIdentifier, devices[0].id.value) def disposition = 'attachment; filename=CSVFile' + exportkey + '.csv' return ['Content-Type': 'text/csv', 'Content-Disposition':disposition, 'Content': is.text] } catch (def ex) {    xml.Response() {        Fault {            Code('Groovy Exception')            Message(ex.getMessage())            StringWriter sw = new StringWriter();            PrintWriter pw = new PrintWriter(sw);            ex.printStackTrace(pw);            Detail(sw.toString())        }    } logger.info(writer.toString()) return ['Content-Type': 'text/xml', 'Content': writer.toString()] } return ['Content-Type': 'text/xml', 'Content': writer.toString()] Back to Top Image Files (6.5+) The FileStore in Axeda version 6.5+ allows fine-grained control of uploaded and downloaded files. As Groovy scripts can return binary data via Scripto, this allows use cases such as embedding a Groovy script url as the source for an image. The following example uses the FileStore API to create an Image out of a valid image file, scales it to a smaller size and stores this smaller file. import com.axeda.drm.sdk.Context import com.axeda.drm.sdk.data.* import com.axeda.drm.sdk.device.* import com.axeda.drm.sdk.mobilelocation.CurrentMobileLocationFinder import com.axeda.drm.sdk.mobilelocation.MobileLocation import com.axeda.drm.sdk.mobilelocation.MobileLocationFinder import com.axeda.sdk.v2.bridge.FileInfoBridge import static com.axeda.sdk.v2.dsl.Bridges.* import com.axeda.services.v2.ExecutionResult import com.axeda.services.v2.FileInfo import com.axeda.services.v2.FileInfoReference import com.axeda.services.v2.FileUploadSession import net.sf.json.JSONObject import groovy.json.JsonBuilder import net.sf.json.JSONArray import com.axeda.drm.sdk.scripto.Request import org.apache.commons.io.IOUtils import org.apache.commons.lang.exception.ExceptionUtils import com.axeda.common.sdk.id.Identifier import groovy.json.* import javax.imageio.ImageIO; import java.awt.RenderingHints import java.awt.image.BufferedImage import java.io.ByteArrayOutputStream; import java.awt.* import java.awt.geom.* import javax.imageio.* import java.awt.image.* import java.awt.Graphics2D import javax.imageio.stream.ImageInputStream /*    Image-specific FileStore entry point to post and store files */ def contentType = "application/json" final def serviceName = "StoreScaledImage" // Create a JSON Builder def json = new JsonBuilder() // Global try/catch. Gotta have it, you never know when your code will be exceptional! try {       Context CONTEXT = Context.getSDKContext()     def filesList = []     def datestring = new Date().time     InputStream inputStream = Request.inputStream       def reqbody = Request.body     // all of our Request Parameters are available here     def params = Request.parameters     def filename = Request?.headers?.'Content-Disposition' ?     Request?.headers?.'Content-Disposition' : "file___" + datestring + ".txt"     def filelabel = Request.parameters.filelabel ?: filename     def description = Request.parameters.description ?: filename     def contType = Request.headers?."content-type" ?: "image/jpeg"     def tag = Request.parameters.tag ?: "cappimg"     def encoded = Request.parameters.encoded?.toBoolean()   def dimlimit = params.dimlimit ? params.dimlimit : 280     // host is available in the headers when the script is called with AJAX     def domain = Request.headers?.host     byte[] bytes = IOUtils.toByteArray(inputStream);     def fileext = filename.substring(filename.indexOf(".") + 1,filename.size())     def outerMap = [:]     // check that file extension matches an image type     if (fileext ==~ /([^\s]+(\.(?i)(jpg|jpeg|png|gif|bmp))$)/){         if (inputStream.available() > 0) {                 def scaledImg                               try {                     def img = ImageIO.read(inputStream)                     def width = img?.width                              def height = img?.height                     def ratio = 1.0                     def newBytes                                       if (img){                                               if (width > dimlimit || height > dimlimit){                             // shrink by the smaller side so it can still be over the limit                             def dimtochange = width > height ? height : width                             ratio = dimlimit / dimtochange                                                       width = Math.floor(width * ratio).toInteger()                             height = Math.floor(height * ratio).toInteger()                         }                                             newBytes = doScale(img, width, height, ratio, fileext)                      if (newBytes?.size() > 0){                         bytes = newBytes                      }                     }                 }                 catch(Exception e){                     logger.info(e.localizedMessage)                                   }                                           outerMap.byteCount = bytes.size()                    FileInfoBridge fib = fileInfoBridge                 FileInfo myImageFile = new FileInfo(filelabel: filelabel,                                                     filename: filename,                                                     filesize: bytes?.size(),                                                     description: description,                                                     tags: tag                                                     )                    myImageFile.contentType = contType                    FileUploadSession fus = new FileUploadSession();                 fus.files = [myImageFile]                    ExecutionResult fer = fileUploadSessionBridge.create(fus);                 myImageFile.sessionId = fer.succeeded.getAt(0)?.id                               ExecutionResult fileInfoResult = fib.create(myImageFile)                               if (fileInfoResult.successful) {                     outerMap.fileInfoSave = "File Info Saved"                     outerMap.sessionId = "File Upload SessionID: "+fer.succeeded.getAt(0)?.id                     outerMap.fileInfoId = "FileInfo ID: "+fileInfoResult?.succeeded.getAt(0)?.id                     ExecutionResult er = fib.saveOrUpdate(fileInfoResult.succeeded.getAt(0).id,new ByteArrayInputStream(bytes))                     def fileInfoId = fileInfoResult?.succeeded.getAt(0)?.id                     String url = "${domain}/services/v1/rest/Scripto/execute/DownloadFile?fileId=${fileInfoId}"                     if (er.successful) {                         outerMap.url = url                     } else {                         outerMap.save = "false"                         logger.info(logFailure(er,outerMap))                     }                 } else {                     logger.info(logFailure(fileInfoResult, outerMap))                 }                } else {                 outerMap.bytesAvail = "No bytes found to upload"             }         } else {             outerMap.imagetype = "Extension $fileext is not a supported image file type."         }     filesList << outerMap     // return the JSONBuilder contents     // we specify the content type, and any object as the return (even an outputstream!)     return ["Content-Type": contentType,"Content":JSONArray.fromObject(filesList).toString(2)]     // alternately you may just want to serial an Object as JSON:     // return ["Content-Type": contentType,"Content":JSONArray.fromObject(invertedMessages).toString(2)] } catch (Exception e) {     // I knew you were exceptional!     // we'll capture the output of the stack trace and return it in JSON     json.Exception(             description: "Execution Failed!!! An Exception was caught...",             stack: ExceptionUtils.getFullStackTrace(e)     )     // return the output     return ["Content-Type": contentType, "Content": json.toPrettyString()] } def doScale(image, width, height, ratio, fileext){     if (image){     ByteArrayOutputStream baos = new ByteArrayOutputStream();     def bytes      def scaledImg = new BufferedImage( width, height, BufferedImage.TYPE_INT_RGB )        Graphics2D g = scaledImg.createGraphics();         g.setRenderingHint(RenderingHints.KEY_INTERPOLATION, RenderingHints.VALUE_INTERPOLATION_BILINEAR);         g.scale(ratio,ratio)         g.drawImage(image, null, null);         g.dispose();              ImageIO.write( scaledImg, fileext, baos )       baos.flush()       bytes = baos.toByteArray()       baos.close()     }     else {         logger.info("image to be scaled is null")         return false     }   return bytes   } private void logFailure(ExecutionResult fileInfoResult, LinkedHashMap outerMap) {     outerMap.message = fileInfoResult.failures.getAt(0)?.message     outerMap.source = fileInfoResult.failures.getAt(0)?.sourceOfFailure     outerMap.details = fileInfoResult.failures.getAt(0)?.details?.toString()     outerMap.fileInfoSave = "false" } The next example makes use of the jQuery framework to upload an image to this script via an http POST. Note: This snippet is available as a jsFiddle at http://jsfiddle.net/LrxWF/18/ With HTML5 button: <input type="file" id="fileinput" value="Upload" /> var PLATFORM_HOST = document.URL.split('/apps/')[0]; // this is how you would retrieve the host on an Axeda instance var SESSION_ID = null // usually retrieved from login function included below /*** * Depends on jQuery 1.7+ and HTML5, assumes an HTML5 element such as the following: * <input type="file" id="fileinput" value="Upload" /> * **/ $("#fileinput").off("click.filein").on("click.filein", function () {     fileUpload() }) var fileUpload = function () {     $("#fileinput").off('change.fileinput')     $("#fileinput").on('change.fileinput', function (event) {         if (this.files && this.files.length > 0) {             handleFiles("http://" + PLATFORM_HOST, this.files)         }     }) } var handleFiles = function (host, files) {     $.each(files, function (index, file) {         var formData = new FormData();         var filename = file.name         formData.append(filename, file)         var url = host + '/services/v1/rest/Scripto/execute/StoreScaledImage?filelabel=' + filename + "&tag=myimg"         url = setSessionId(url)         jQuery.ajax(url, {             beforeSend: function (xhr) {                 xhr.setRequestHeader('Content-Disposition', filename);             },             cache: false,             cache: false,             processData: false,             type: 'POST',             contentType: false,             data: formData,             success: function (json) {                 refreshPage(json)                 console.log(json)             }         });     }) } var setSessionId = function (url) {     // you would already have this from logging in     return url + "&sessionid=" + SESSION_ID } var refreshPage = function (json) {     // here you would refresh your page with the returned JSON     return } /*** *  The following functions are not used in this demonstration, however they are necessary for a complete app and are found in axeda.js  http://gist.github.com/axeda/4340789 ***/     function login(username, password, success, failure) {         var reqUrl = host + SERVICES_PATH + 'Auth/login';         localStorage.clear()         return $.get(reqUrl, {             'principal.username': username,                 'password': password         }, function (xml) {             var sessionId = $(xml).find("ns1\\:sessionId, sessionId").text()             // var sessionId = $(xml).find("[nodeName='ns1:sessionId']").text(); - no longer works past jquery 1.7             if (sessionId) {                 // set the username and password vars for future logins.                         storeSession(sessionId);                 success(SESSION_ID); // return the freshly stored contents of SESSION_ID             } else {                 failure($(xml).find("faultstring").text());             }         }).error(function () {             $('#loginerror').html('Login Failed, please try again')         });     }; function storeSession(sessionId) {     var date = new Date();     date.setTime(date.getTime() + SESSION_EXPIRATION);     SESSION_ID = sessionId     document.cookie = APP_NAME + '_sessionId=' + SESSION_ID + '; expires=' + date.toGMTString() + '; path=/';     return true; }; The return JSON includes a URL that you can use as the source for images: [{   "byteCount": 14863,   "fileInfoSave": "File Info Saved",   "sessionId": "File Upload SessionID: 01234",   "fileInfoId": "FileInfo ID: 12345",   "url": "http://yourdomain.axeda.com/services/v1/rest/Scripto/execute/DownloadFile?fileId=12345" }] The DownloadFile Custom Object looks like the following: import static com.axeda.sdk.v2.dsl.Bridges.* import javax.activation.MimetypesFileTypeMap import com.axeda.services.v2.* import com.axeda.sdk.v2.exception.* import com.axeda.drm.sdk.scripto.Request def knowntypes = [          [png: 'image/png']         ,[gif: 'image/gif']         ,[jpg: 'image/jpeg']     ] def params = Request.parameters.size() > 0 ? Request.parameters : parameters def response = fileInfoBridge.getFileData(params.fileId) def fileinfo = fileInfoBridge.findById(params.fileId) def type = fileinfo.filename.substring(fileinfo.filename.indexOf('.') + 1,fileinfo.filename.size()) type = returnType(knowntypes, type) def contentType = params.type ?: (type ?: 'image/jpg') return ['Content': response, 'Content-Disposition': contentType, 'Content-Type':contentType] def returnType(knowntypes, ext){     return knowntypes.find{ it.containsKey(ext) }?."$ext" } Make sure to append a valid session id to the end of the URL when using it as the source for an image. The techniques discussed above can be applied to any type of binary file output with consideration for the type of file being processed. A Word on Streaming Content streaming such as streaming of video or audio files over UDP is not currently supported by the Axeda Platform.

Slides used during the What's New in ThingWorx Manufacturing Apps 8.1 update training webinar held Nov. 15, 2017

Video Author:                     Polina Osipvoa Original Post Date:            June 10, 2016 Applicable Releases:        ThingWorx   Description: This is a video tutorial on creating a Media Entity, and importing and displaying an image.      

This post adds to my previous post: Deploying H2 Docker versions quickly   In addition to configuring the basic Docker Images and Containers, it's also possible to deploy them with a TLS / SSL certificate and access the instances via HTTPS protocol.   For this a valid certificate is required inside a .jks keystore. I'm using a self-signed certificate, but commercial ones are even better! The certificate must be in the name of the machine which runs Docker and which is accessed by the users via browser. In my case this is "mne-docker". The password for the keystore and the private key must be the same - this is a Tomcat limitation. In my case it's super secret and "Password123456".   I have the following directory structure on my Operating System   /home/ts/docker/ certificates mne-docker.jks twx.8.2.x.h2 Dockerfile settings platform-settings.json <license_file> storage Thingworx.war   The Recipe File   In the Recipe File I make sure that I create a new Connector on port 8443, removing the old one on port 8080. I do this by just replacing via the sed command - also introducing options for content compression. I'm only replacing the first line of the xml node as it holds all the information I need to change.   Changes to the original version I posted are in green   FROM tomcat:latest MAINTAINER mneumann@ptc.com LABEL version = "8.2.0" LABEL database = "H2" RUN mkdir -p /cert RUN mkdir -p /ThingworxPlatform RUN mkdir -p /ThingworxStorage RUN mkdir -p /ThingworxBackupStorage ENV LANG=C.UTF-8 ENV JAVA_OPTS="-server -d64 -Djava.awt.headless=true -Djava.net.preferIPv4Stack=true -Dfile.encoding=UTF-8 -Duser.timezone=GMT -XX:+UseNUMA -XX:+UseG1GC -Djava.library.path=/usr/local/tomcat/webapps/Thingworx/WEB-INF/extensions RUN sed -i 's/<Connector port="8080" protocol="HTTP\/1.1"/<Connector port="8443" protocol="org.apache.coyote.http11.Http11NioProtocol" maxThreads="150" SSLEnabled="true" scheme="https" secure="true" clientAuth="false" sslProtocol="TLS" enableLookups="false" keystoreFile="\/cert\/mne-docker.jks" keystorePass="Password123456" ciphers="TLS_DHE_RSA_WITH_3DES_EDE_CBC_SHA, TLS_DHE_RSA_WITH_AES_128_CBC_SHA, TLS_DHE_RSA_WITH_AES_128_CBC_SHA256, TLS_DHE_RSA_WITH_AES_128_GCM_SHA256, TLS_DHE_RSA_WITH_AES_256_CBC_SHA, TLS_DHE_RSA_WITH_AES_256_CBC_SHA256, TLS_DHE_RSA_WITH_AES_256_GCM_SHA384, TLS_ECDHE_RSA_WITH_3DES_EDE_CBC_SHA, TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA, TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256, TLS_ECDHE_RSA_WITH_AES_128_GCM_SHA256, TLS_ECDHE_RSA_WITH_AES_256_CBC_SHA, TLS_ECDHE_RSA_WITH_AES_256_CBC_SHA384, TLS_ECDHE_RSA_WITH_AES_256_GCM_SHA384, TLS_RSA_WITH_AES_256_CBC_SHA, TLS_RSA_WITH_AES_128_CBC_SHA" compression="on" compressableMimeType="text\/html,text\/xml,text\/plain,text\/css,text\/javascript,application\/javascript,application\/json"/g' /usr/local/tomcat/conf/server.xml COPY Thingworx.war /usr/local/tomcat/webapps VOLUME ["/ThingworxPlatform", "/ThingworxStorage", "/cert"] EXPOSE 8443   Note that I also map the /cert directory to the outside, so all of my Containers can access the same certificate. I will access it read-only.   Deploying     sudo docker build -t twx.8.2.x.h2 . sudo docker run -d --name=twx.8.2.x.h2 -p 88:8443 -v /home/ts/docker/twx.8.2.x.h2/storage:/ThingworxStorage -v /home/ts/docker/twx.8.2.x.h2/settings:/ThingworxPlatform -v /home/ts/docker/certificates:/cert:ro twx.8.2.x.h2   Mapping to the 8443 port ensures to only allow HTTPS connections. The :ro in the directory mapping ensures read-only access.   What next   Go ahead! Only secure stuff is kind of secure 😉 For more information on how to import the certificate into a the Windows Certificate Manager so browsers recognize it, see also the Trusting the Root CA chapter in Trust & Encryption - Hands On