cancel
Showing results for 
Search instead for 
Did you mean: 
cancel
Showing results for 
Search instead for 
Did you mean: 

ThingWorx Navigate is now Windchill Navigate Learn More

IoT & Connectivity Tips

Sort by:
This Expert Session goes over ways to identify and develop a successful use case for ThingWorx Analytics. The example use case presented here is on employee retention in a fictional company with the goal of maximizing employee retention . This presentation will provide you with all the fundamentals you need to develop your own ThingWorx Analytics use cases from the ground up.     For full-sized viewing, click on the YouTube link in the player controls.   Visit the Online Success Guide to access our Expert Session videos at any time as well as additional information about ThingWorx training and services.
View full tip
This Expert Session reviews the concept of “Decision Trees” and the functionality that is available in ThingWorx Analytics Builder. First, you will learn how to create and upload a dataset in ThingWorx Analytics Builder.  After that, it shows you how to train a model and score on the model that was just generated. It then goes into detail on how the prediction learner "Decision Tree" operates and classifies inputs.     For full-sized viewing, click on the YouTube link in the player controls.   Visit the Online Success Guide to access our Expert Session videos at any time as well as additional information about ThingWorx training and services.
View full tip
ThingWorx's JDBC extensions - Relational Database Management System and the JDBC Extensions allow ThingWorx to connect to variety of different databases. With that comes a natural question how and what sort of SQL statements could be executed via these extensions? Note: ​​Importing the JDBC extensions i.e. the RDBMS and JDBC Extensions, creates a Database Template for that particular database. If you are working with RDBMS extension then Template of corresponding Database will be created with similar name e.g. importing the RDBMS Extension for Oracle 12 will create Template named OracleDBServer12. While importing the JDBC driver using the JDBC extension will create Template name based on the JDBC driver used or a custom name could be given. Following examples and SQL statements are adhering to Oracle's SQL*Plus standard, however these can be easily adapted to the type of RDBMS you intend to work with. Topics How to create SQL Service in ThingWorx entity Types of SQL Statements Examples on SQL Service usage and some extended use cases / examples How to create SQL Service in ThingWorx Navigate to the Thing implementing the Database Template, e.g. OracleDBServer12         2. Click on the Services section under the Entity Information and click on Add My Service         3. A new service creation section will come up, change the Service type of JavaScript (this is default selection) to either SQL (Query) or SQL (Command) depending on the type of SQL you are to create under this particular service                       4. Here's quick example on creating SQL (Query) service which takes name as input for a select *  sql … Statement, i.e. it returns complete set of rows and columns from any given table on which the user has the access to perform Select                   Note: BaseType defaults to Infotable when creating SQL (Query) service and the returned number of rows are restricted to 500. Therefore, if table contains rows more than 500, ensure to change the Max Rows parameters         5. Example on creating SQL (Command) service that delete all the rows from the database table               Note: The Base Type defaults to Number when using SQL (Command)     Additional information:     When creating a SQL service, apart from providing changing the Service Info and  Inputs /Outputs, 3rd section Tables/Columns allows users to explore the Tables and their respective columns as part of that particular user's schema - meaning the objects on which the user has select rights in his schema in the database.     Types of SQLs This is not an exhaustive list, rather contains most commonly used types of SQL statements     1. Data Definition Language (DDL)           a. Create, Alter and drop schema objects           b. Grant and Revoke privileges and roles     2. Data Manipulation Language (DML)           a. Insert           b. Delete           c. Select Examples for SQL Service usage and some extended use cases / examples     1. Data Definition Language (DDL)           a. Create statement                       b. Alter statements                         c. Drop statement                         d. Flashback statements (Oracle specific)                         e. Grant statement                     f. Rename statement                 2. Data Manipulation Language (DML)           a. Insert statement                     b. Delete statement                     c. Select statements           Use cases - Case 1 : Backing up DataTable DataTable objects in ThingWorx are for quick lookup of data and they are most performant till ~100K rows. Exceeding rows over 100K in a DataTable makes it highly susceptible to performance issues in terms of querying or writing to it. Unless, there's sharding​ on the persistence provider or multiple persistence providers used - JDBC connectivity to external data stores like RDBMS systems could help in keeping up with growing number of rows in DataTables. RDBMS tables are more than capable of storing very large amount of rows without being taxed over the performance. JDBC extension could be used to do just that in a use case requiring backing up DataTable or any Data Storage objects from ThingWorx for that matter. Here's one quick example using one of the Insert SQL service shown above to back up the entire DataTable to the Oracle's DB table. Following ThingWorx JavaScript service wraps the InsertIntoBULKDATAINSERTDT SQL service: // result: INTEGER // getting total row count in the DataTable var totalCount = Things["BulkInsertDT"].GetDataTableEntryCount(); var params = { maxItems: totalCount /* NUMBER */ }; // result: INFOTABLE // DataTable service to fetch all the rows from it var allData = Things["BulkInsertDT"].GetDataTableEntries(params); // looping over the result fetched above to get all the rows for insertion     for (var i = 0; i<totalCount; i++) {         var result = allData.getRow(i); // mapping the data for insert     var params = {         LongCol3: result.LongCol3 /* LONG */,         numcol1: result.NumCol1 /* NUMBER */,         StringCol2: result.StringCol2 /* STRING */,         IntCol4: result.IntCol4 /* INTEGER */     }; try { // result: NUMBER // calling the SQL Service InsertIntoBULKDATAINSERTDT created under a DB Thing called OracleDBThingNew     var result = Things["OracleDBThingNew"].InsertIntoBULKDATAINSERTDT(params); } catch (err) {      Logger.info ("Failed to insert the values" + err) }     }
View full tip
In the last while I've seen a few things which got me thinking about how value is created or unlocked from connected data.  Multiple components are required to create, send, store and manage the data created by edge devices, doing these things enables value to be unlocked, but what does it take to unlock the value? It was this ​article which first got me interested in considering this question.  In particular it was a section near the bottom of the article where the author describes a number of creative business use cases for car manufacturers which could be enabled by connected data.  If this author could come up with several creative and potentially valuable use case examples for one industry I started to wonder what other sorts of use cases could exist in other industries?  Could there be a series of use of use cases which a little variation be applied to different industries? The second article which further sparked my interest in where the value originates from, is this one​ on using a cryptocurrency with IOT.  While the idea of using a blockchain like technology with IOT is intriguing, it was the second image in the article (below) which resonated with me on value.  This image is a graphical representation of the connection between the key components of a connected system and it makes it clear that each component has a critical role to play and the whole system and missing anyone of the parts and the system doesn't function.  This image make it clear that it's the "Analyze" phase which drives the action to do something, and it's taking an action which is the reason the systems reason for existing.    Which brings me to the third and final article describing Industry 4.0.  Like the other two articles, it wasn't the main point of the article I found most interesting, rather it was the image below, and in particular the side bar 'Value Creation through' which brought me back to the question of where value comes from.  The idea that in a manufacturing setting, value can be created through product or process innovations as well as through new business models is intriguing.  I think a fourth idea missing from this list, is one were network effects from getting more and more proprietary data creating a compounding effect, like with Facebook or LinkedIn.  If there are at least four modes of value creation, maybe there others? While these articles caused me to ask some questions, none of them really answered the question of where the value is unlocked. To answer the question I decided to restate the question to be "how is value unlocked from data" making the assumption the value is derived from the data.  This question is a little easier to address.  The best visual representation of the answer I've seen is the data value road map (below) from the Creating a Data-Driven Organization book which was released a couple of years ago.  While I think the author is probably missing at least two boxes above 'optimization' ("new business models" and "data driven network effects") I think the graphic does a good job communicating that as the value created from data increases, the complexity of the analytic task also increases; suggesting the value is unlocked by the analytics.  For me, the value from a system of connected devices is unlocked from the "analysis" phase as seen in the first image. But in order to perform the "analysis" I think requires two things.  First asking the right high value questions of the data (product managers/beginning with the end in mind/use cases) and then using the right set of technologies to address those questions which in many instances means Artificial Intelligence of some sort.  Interestingly although artificial intelligence is required for many high value use cases, both parts of the analysis require distinctly human skills (the right use cases & controlling the technology) to create externalized intelligence and generate value. Creating a Data-Driven Organization: Practical Advice from the Trenches 1, Carl Anderson, eBook - Amazon.com
View full tip
Key Functional Highlights ThingWorx 8.1 covers the following areas of the product portfolio: ThingWorx Analytics, ThingWorx Utilities and ThingWorx Foundation which includes Core, Connection Server and Edge capabilities. Highlights of the release include: ThingWorx Foundation Next Generation Composer: Embedded Mashup Builder enables codeless development of web visualization. New ability to manage and push configurations for KEPServerEX Notifications: Create SMS and Email notifications natively in Next Generation Composer Support for localized and dynamic content with tokens Protocol Adapter Toolkit: Encrypted communication between edge devices and the Connector over HTTPS or WSS. Encrypted communication between the Connector and ThingWorx Core (WSS). Ability to define a mapping of outbound messages from ThingWorx Core using a Codec to an edge-bound message. Authentication of edge devices 3 rd Party Platform Connectivity: Azure IoT Connector v2.0 § Model data from Azure IoT using the Thing Model § Utilize data from Azure IoT as properties in the Thing Model § Utilize services and events through Azure IoT § Utilize Azure file storage ThingWorx for Predix v1.0 § Synchronize data from Predix to ThingWorx § Enable SSO between Predix & ThingWorx C SDK: Framework for custom functionality to be added to C SDK-based applications at runtime License Management: Simple, automated, licensing system for collection, storage, reporting, management and auditing of licensing entitlements. Deprecated the SQUEAL functionality ThingWorx Analytics Categorical and Ordinal Goals: Adds use of unordered text (categorical) and ordered text (ordinal) goals to predictive analytics.  Create and score models with the new goal types. Virtual Sensor: Adds support for time-series predictions when historical data is not available.  Allows machine learning predictions to take the place of physical sensors and simplifies predictions like time to failure and probability of failure. Tighter platform integration: Analytics Server is more tightly integrated with ThingWorx Core, providing native control and access to analytics programming interfaces. New, simplified API: The new Analytics Server 2.0 API pattern is simpler, more modern, and easier to use. Microservices-based Architecture: Conversion to microservices sets the stage for High Availability and improved distributed installations. Native Linux installer: Docker is no longer required to run on Linux-based systems. Analytics Manager: Several enhancements, including: Simulation-driven data framework allows external providers to send data as if they were a physical Thing. Time Series Data Inputs improves the ability to share time series data with external providers. Thing Connect / Disconnect makes it easier to connect specific Things with external providers. Analytics Builder: Ease of use enhancements including: New UI support for time series models. Easier access to / use of Signals and Profiles. Simplified models for Boolean goals. Easier installation, no longer requires UploadThing. ThingWorx Utilities Software Content Management (SCM): Define package dependencies where the deployment of a package requires the presence of one or more other packages. ThingWorx Trial Edition ThingWorx Trial Edition will be available to internal PTC resources at launch and will be made available externally on the Developer Portal shortly after launch. Developer Enablement: Enhancements have been made to the Trial Edition installation tool, providing a native installation process of the ThingWorx platform including: ThingWorx Foundation ThingWorx Utilities ThingWorx Analytics ThingWorx Industrial Connectivity Documentation ThingWorx 8.1 Reference Documents ThingWorx Analytics 8.1 Reference Documents ThingWorx Core 8.1 Release Notes ThingWorx Core Help Center ThingWorx Edge SDKs and WebSocket-based Edge MicroServer Help Center ThingWorx Connection Services Help Center ThingWorx Industrial Connectivity Help Center ThingWorx Utilities Help Center ThingWorx Utilities Installation Guide ThingWorx Analytics Help Center ThingWorx Trial Edition User Guide Additional information ThingWorx eSupport Portal ThingWorx Developer Portal ThingWorx Marketplace Download The following items are available for download from the PTC Software Download site. ThingWorx Platform – Select Release 8.1 ThingWorx Utilities – Select Release 8.1 ThingWorx Analytics – Select Release 8.1
View full tip
This video covers the new features of ThingWorx Analytics Builder 8.1   Updated Link for access to this video: What's New in ThingWorx Analytics Builder 8.1
View full tip
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.
View full tip
Parquet Data Format used in ThingWorx Analytics   Starting ThingWorx Analytics Version 8.1 Data storage will no longer require the installation of a PostgreSQL database. Instead, uploaded CSV data is converted to the optimized  Apache Parquet format and stored directly in the file system. This Blog explains some the features of Apache Parquet justifying this transition in ThingWorx Analytics Data Storage. features What is Apache Parquet: Apache Parquet is a column-oriented data store of the Apache Hadoop ecosystem. It is compatible with most of the data processing frameworks in the Hadoop environment. It provides efficient data compression and encoding schemes with enhanced performance to handle complex data in bulk. Below is an illustration of the Columnar Storage model: Apache Parquet Features and Benefits: Apache Parquet is implemented using the record shredding and assembly algorithm taking into account the complex data structures that can be used to store the data. Apache Parquet stores data where the values in each column are physically stored in contiguous memory locations.  Due to the columnar storage, Apache Parquet provides the following benefits: Column-wise compression is efficient and saves storage space Compression techniques specific to a type can be applied as the column values tend to be of the same type Queries that fetch specific column values need not read the entire row data thus improving performance Different encoding techniques can be applied to different columns Some advantages of using Parquet for ThingWorx Analytics: Apart from the above benefits of using Parquet which amount to higher efficiency and increased performance, below are some advantages that apply specifically to ThingWorx Analytics This change in ThingWorx Analytics from using a Database to using Parquet removes the limitations on the number of data columns the system can handle. It also allows for streamlining the dataset creation process. Since the data is converted to a Parquet format, there is no need to separately optimize the dataset. Even when new data is appended to an existing dataset, a new partition is added and re-optimization is optional but not required. Data could be appended easily so there is no longer a need to re-load the full Dataset when new Data values are added The illustration below shows the transition from Row-based Data Storage model VS the columnar based Storage of Parquet
View full tip
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
View full tip
In this video we are going through a few steps to ensure the installation process went fine.   Updated Link for access to this video:  Validating a ThingWorx Analytics Server 8.1 Installation
View full tip
In this video we are walking through the installation steps of ThingWorx Analytics Server 8.1. This cover the Native Linux installation though the steps will be similar for a docker installation on Windows or Linux.   Updated Link for access to this video:  Installing ThingWorx Analytics Server 8.1 - Native Linux
View full tip
Updates: App Keys defaults - Now stored in secure keystore - Newly created app keys stored automatically - On upgrated existing app keys are migrated to secure keystore Change the app key default expiration time to 1 day - Changed from 100 years - UI date picker - If date not picked now defaults to 1 day Best Practice: - Carefully consider expiration - Set to desired value at time of creation - Scripts should carefully choose time -Knowledge base article in the works Edge SSL updates C SDK TLS/SSL: C-SDK support for OpenSSL: - Version 1.0.2 that supports tls  1.2. - Tomcat 8 compatible ciphers - EMS will follow soon BYO SSL - Abstraction layer &Documentation - Path to building any SSL for supported environments - Porting - Different version of open ssl: straight forward - Other SSL: some expertise required - Enables other SSL providers: - Burden to validate on SDK developer Possibilities: -AxTLS -WolfSSL -Mocana EMS improvements SafeInt Library -C++ library -Helps prevent integer overflows Better certificate loading support -EMS and LUA script resource can authenticate -Bidirectional EMS's HTTP server now defaults to requiring authentication for LSR Overall theme: secure by default Q: If appkey expired in 1 day, does a new one get automatically created? A: Automatic one is not created, change the expiration date when creating the app key. When it expires - have to create a new one.
View full tip
Excited to announce ThingWorx 8.1 is officially available in our Support Portal. Please find the release notes below. The following feature enhancements and bug fixes exist in ThingWorx 8.1.0: Enhancements Platform: • Metrics Reporting is enabled by default, which allows usage, performance, and diagnostics data to be sent to a PTC server daily. For more information about this setting, see Platform Subsystem. • You can add and configure Notifications in New Composer. For more information, see Adding Notifications. • License files are now instance specific.. • Security for application keys has been enhanced. The defualt expiration date has been changed to 24 hours if it is not explictly set. • Additional capability has been added to New Composer. • Improvements to anomaly detection accuracy have been added. As a result, data collection restart is no longer necessary after a long gap and the H2 database that installs with the Training Microservice is stored in memory, not as a persisted file. For more information, see Anomaly Detection. • You can now load configuration/project files from KEPServerEX instances Bug Fixes Platform • Fixed an issue where Tomcat failed to start when using SAP HANA. TW-22191 • Fixed an issue that was preventing ThingWorx from starting after the File Transfer Subsystem was disabled. TW-22177 • Fixed an issue where the change history of a Mashup was automatically updated even if no changes were made. TW-22114 • Fixed an issue that was preventing the ServiceInvokeCompleted event from working after performing an in-place upgrade. TW-21784 • Fixed an issue where alert notifications were not being sent to recipients after removing a recipient. TW-21585 • Fixed an issue where the Add button in the Services page did not display after creating a Data Table. TW-21518 • Fixed an issue with alert notifications for entities containing periods in the name. TW-21347 • Fixed an issue that was causing connected assets to display as disconnected in ThingWorx Utilities. UTL-4698 • Fixed an issue where data bind was lost after changing Read-Only settings to Read/Write in Composer. TW-23506 • Fixed an issue that was causing a MetricsReportingTask error after enabling ThingWorx Performance Advisor. TW-21141 • Fixed an issue with the ThingWorx authentication window when specifying the site while using FF and IE. TW-21271 Mashup Builder • Fixed an issue with the List widget that was causing incorrect tooltips to display. TW-24012 TW-23961 TW-23038 • Fixed an issue where Chrome was automatically retrying Remote Service calls when a timeout occurred. TW-23828 • Fixed an issue after restarting the ThingWorx web app where the Runtime or Composer’s index.html were missing. TW-23984 • Fixed an issue where closing a modal dialogue did not remove the disabled state from an element. TW-11217 • Fixed an issue when creating a popup with the Navigation widget. The tab sequence of the popup was dependent on the original mashup. TW-11151 • Fixed an issue with localized values of data columns when using the Data Filter widget. TW-11059 Extensions  • Fixed an issue where CSV parser extension import failed if the text file that was being imported did not include a new line character at the end of the last line of text. TW-21863 • Fixed an issue with the Advanced Grid widget where the Reset button was not localized. TW-21457 • Fixed an issue with the jQuery library used by the WebSocketTunnel_ExtensionPackage widget. Note If you are using the WebSocketTunnel_ ExtensionPackage, you will need to upgrade to version 3.0.2 if you are upgrading to ThingWorx 8.1.0. To upgrade the extension, go to the Web Sockets Tunnel Widget and Library page of the ThingWorx Marketplace. TW-24465 End of Life Information SQUEAL functionality has been discontinued in 8.1. System requirements: http://support.ptc.com/WCMS/files/173583/en/ThingWorx_Core_8.1_System_Requirements_1.0.pdf Installation guide: http://support.ptc.com/WCMS/files/173600/en/Installing_ThingWorx_8.1_1.0_.pdf ThingWorx 8.1 Cross Platform Highlights: Security ThingWorx 8.1 Cross Platform Highlights and Q&amp;A: Licensing
View full tip
If you've installed and used version 8.0.0 of the Manufacturing Apps and would like to extend your usage beyond the trial expiration time, we invite you to use the new version of the Apps (8.0.1), which now includes Production Advisor.   You will need to uninstall and reinstall the application to begin this process.  You will be able to preserve your configuration data by exporting it, but you will only be able to import it in the commercial version of the Application.  To export your configuration: navigate to the hamburger menu at the top right of the screen and select "Export Configuration and Data" To move to the latest release of the free edition of the application (8.0.1): 1. Uninstall the applications.  Navigate to the Start Menu > ThingWorx Manufacturing Apps > Uninstall. 2. Download the latest version: https://www.ptc.com/en/thingworx/manufacturing-apps/Dashboard/Download-Apps 3. Run the installer.   If you have any questions or concerns, feel free to post a question in the manufacturing apps community, or in response to this post; we will be happy to assist you!   - The PTC Manufacturing Team
View full tip
I had tested this on a Raspberry Pi 3 which was working fine. I'm not sure if there's any resource limitation on the Pi 2 that would cause potential issues. I however had some performance issues when using the H2 version, therefore I stuck to the Neo4J version. As there were some changes introduced in ThingWorx 7.4 I would also stick to 7.2 or 7.3. If the Tomcat folder exists in the webapps, that means that initial deployment has been successful. I'd recommend checking the Tomcat logs and the ThingWorx ApplicationLog / ConfigurationLog for any potential issues.
View full tip
    About   This is part of a ThingBerry related blog post series.         ThingBerry is ThingWorx installed on a RaspBerry Pi, which can be used for portable demonstrations without the need of utilizing e.g. customer networks. Instead the ThingBerry provides its own custom WIFI hotspot and allows Things to connect and send / receive demo data on a small scale.   In this particual blog post we'll discuss on how to connect a ESP8266 module to the ThingBerry WIFI hotspot and send data from a DHT-11 sensor via the MQTT protocol.   As the ThingBerry is a highly unsupported environment for ThingWorx, please see this blog post for all related warnings.   Install MQTT broker on the ThingBerry     To install mosquitto as a MQTT broker, log in to the ThingBerry and run     sudo apt-get install mosquitto   This will provide a basic broker installation, which is good enough for this example. MQTT clients (including ThingWorx) will connect to this broker to exchange messages. There will be no added security like encrypted traffic shown in this example, it's however good practise to secure MQTT broker / client connections.   While the ESP8266 module is publishing information, ThingWorx will subscribe to the corresponding topics to update its internal property values with what is sent by the ESP8266 module.   For more information on MQTT, how to configure it for ThingWorx or more security relevant information also see   https://community.thingworx.com/message/5063#5063 https://community.thingworx.com/community/developers/blog/2016/08/08/securing-mqtt-connection-to-thingworx-platform?sr=tcontent   Configure the ESP8266     There are too many instructions on the web already on how to initially setup the ESP8266 and use it with the Arduino IDE. I'll therefore just refer to Google which covers the topic more extensively than I ever could.   All coding in this example is done in the Arduino IDE and is pushed to the ESP8266 (NodeMCU) via USB. For this you might need to install a CH340g USB driver for the NodeMCU.   In the Arduino IDE under Tools, I have set my environment to   Board: NodeMCU 1.0 (ESP-12E Module) CPU Frequency: 80 MHz Flash Size: 4M (3M SPIFFS) Upload Speed: 115200 Port: COM3   Under Sketch > Include Library > Manage Libraries add / install the following libraries:   DHT sensor library by Adafruit Adafruit Unified Sensor by Adafruit PubSubClient by Nick O'Leary   These bring the libraries necessary to read data from the DHT-11 sensor and to configure the ESP8266 as MQTT client.     Wiring the DHT-11 sensor     The following image shows the PINs on the ESP8266     I'm using a DHT-11 sensor with cables included and already fixed to a board with 3 PINs. In case you're using a different version, there might be additional components and wiring required, like a resistor etc. Google might help here as well.     Ensure that neither board nor sensor are plugged in, and the ESP8266 is powered off.   To hook the sensor up to the ESP8266, join   ( - ) to GND ( + ) to 3.3V (out) to D3   After all the connections are made, connect the ESP8266 via USB to a computer / laptop with the Arudino IDE configured.   Coding   In the Arduino IDE use the following code - adjust the WIFI settings and the MQTT broker configuration. Ensure to rename the ESP_xx name / topic to something more meaningful, e.g. a specific device name (or just leave it as is if in doubt).   Use the ssid and wpa_passphrase from the hostapd.conf used to configure the ThingBerry as WIFI hotspot.   Copy&paste the code below into the Arduino IDE, verify it and upload it to the ESP8266.     If searching for a WIFI connection, the device's blue LED will blink. A successful connection to the broker and publishing the values will result in a static blue LED. In case the LED is off, the connection to the broker is lost or messages cannot be published.   For troubleshooting, use the Serial Monitor function (at 115200 baud) in the Arduino IDE. In case sensor data cannot be read but the wiring is correct and the code addressing the correct PIN verify the sensor is indeed working. It took me a long time to figure out that the first sensor I used was a defective device.   The current configuration sends updates every 10 seconds - longer intervals might make more sense, but can trigger a timeout for the MQTT broker. In this case the program will re-connect automatically and log corresponding messages in the Serial Monitor. This might seem like an error, but is indeed intended behavior by the code and the MQTT broker.     Configure MQTT Thing in ThingWorx     Create a new Thing in ThingWorx based on the MQTT Template. Add two properties:   temperature humidity   Both set to persistent and logged and Data Change Type to ALWAYS. Also configure a Value Stream to log a history of values.   In the configuration, add two more subscriptions. Activate the "subscribe" checkbox and map name (local property) to topic (MQTT topic), e.g.   name = temperature; topic = ESP_xx/temp name = humidity; topic = ESP_xx/hum   Ensure the correct servernames, ports etc. are configured (an empty servername will use the localhost).   Save the configuration. Property values should now be updated from the MQTT broker, depending on what the device is sending.   Code #include "DHT.h" #include "PubSubClient.h" #include "ESP8266WiFi.h" /* * * Configure parameters for sensor and network / MQTT connections * */ // setup DHT 11 pin and sensor #define DHTPin D3 #define DHTTYPE DHT11 // setup WiFi credentials #define WLAN_SSID "mySSID" #define WLAN_PASS "WIFIpassword" // setup MQTT #define MQTTBROKER "mqttbrokerhostname" #define MQTTPORT 1883 // setup built-in blue LED #define LED 2 /* * ============================================================ * * DO NOT CHANGE ANYTHING BELOW * (unless you know what you're doing) * */ // initiate DHT DHT dht(DHTPin, DHTTYPE); // initiate MQTT client WiFiClient wifiClient; PubSubClient client(MQTTBROKER, MQTTPORT, wifiClient); /* * setup */ void setup() { // switch off internal LED pinMode(LED, OUTPUT); digitalWrite(LED, HIGH); // start serial monitor Serial.begin(115200); // start DHT dht.begin(); // start WiFi WiFi.begin(WLAN_SSID, WLAN_PASS); } /* * the loop */ void loop() { // while not connected to WiFi, print "." // after connection exit the loop // blink LED while having no WiFi signal boolean wifiReconnect = false; while (WiFi.status() != WL_CONNECTED) { digitalWrite(LED, LOW); delay(200); Serial.print("."); digitalWrite(LED, HIGH); delay(300); wifiReconnect = true; } // if WiFi has reconnected, print new connection information and turn on LED if (wifiReconnect == true) { // print connection information and local IP address, mac address Serial.println(); Serial.println("WiFi connected"); Serial.println(WiFi.localIP()); Serial.println(WiFi.macAddress()); Serial.println(); // turn on built-in LED to indiciate successful WiFi connection digitalWrite(LED, LOW); } // if MQTT client is not connected, connect again // turn on built-in LED to indicate a successful connection if (!client.connected()) { Serial.println("Disconnected from MQTT server... trying to connect"); if (client.connect("ESP_xx")) { Serial.println("Connected to MQTT server"); Serial.println("Topic = ESP_xx"); digitalWrite(LED, LOW); } else { Serial.println("MQTT connection failed"); digitalWrite(LED, HIGH); } Serial.println(); } // read temperature and humidity from sensor float t = dht.readTemperature(); float h = dht.readHumidity(); if (isnan(t) || isnan(h)) { // if temperature or humidity is not a number, print error Serial.println("Failed retrieving data from DHT sensor"); } else { // print temperature and humidity Serial.print(t); Serial.print("° - "); Serial.print(h); Serial.print("%"); Serial.println(); // only send values to MQTT broker, if client is connected if (client.connected()) { // boolean to check for errors during payload transfer bool isError = false; // create payload and publish values via MQTT client // use buffer to convert float to char* char buffer[10]; dtostrf(t, 0, 0, buffer); if (client.publish("ESP_xx/temp", buffer)) { Serial.print(" published /temp "); } else { Serial.print(" failed /temp "); isError = true; } dtostrf(h, 0, 0, buffer); if (client.publish("ESP_xx/hum", buffer)) { Serial.print(" published /hum "); } else { Serial.print(" failed /hum "); isError = true; } Serial.println(); // on error, turn off LED if (isError == true) { digitalWrite(LED, HIGH); } else { digitalWrite(LED, LOW); } } } // sleep for 10 seconds // if sleep > default mosquitto timeout : a reconnect is forced for each update-cycle delay(10000); }
View full tip
How to enable ThingWorx Performance Advisor Applies To ThingWorx 7.2+ Description How to enable ThingWorx Performance Advisor Resolution In the ThingWorx Composer, go to Systems > Subsystems, select the PlatformSubsystem and choose Configuration In the Metrics Reporting Service Configuration Select the "Enable Metrics Reporting" checkbox to activate Performance Advisor reporting Enter your current PTC credentials (username and password) for either the customer support portal or the developer portal After providing those details, use the Request button to request an Authorization Key. Customer Number and Name will be filled automatically and an Authorization Key is generated which allows the server identifying itself to the PTC environment. Those fields are read-only. ThingWorx is now ready to send Performance Advisor data and metrics to PTC Related FAQ - Performance Advisor for ThingWorx | PTC https://community.thingworx.com/community/developers/blog/2017/05/22/performance-advisor-for-thingworx-explore-configure…
View full tip
It’s critical for us to configure all correct parameters while running your application in Production environment or even in development env. While GUI makes it very user-friendly and easy to set up the right values in the right fields, it's useful to know how to do the same programmatically/without the "Configure Tomcat" utility. One way, if you're using Tomcat as a Windows service, you can adjust the JVM options by going to the bin dir and running: tomcat8 //US//MYSERVICENAME ++JvmOptions=-Dexample.license.directory="C:\Program Files\example" Turn the service off before you do this and restart it when you finish. cd $CATALINA_HOME .\bin\service.bat install tomcat .\bin\tomcat8.exe //US//tomcat8 --JvmMs=512 --JvmMx=1024 --JvmSs=1024 Setting the --JvmXX parameters may not be enough. You may also need to specify the JVM memory values explicitly. From the command line it may look like this: bin\tomcat8w.exe //US//tomcat8 --JavaOptions=-Xmx=1024;-Xms=512;.. Be careful not to override the other JavaOptions. But the best and recommended way is to use setenv.sh/setenv.bat (Linux/Windows respectively). It isn't in the as-downloaded Tomcat. But if you look in catalina.sh/catalina.bat, there's a check for a file called setenv. If it's there, it's run. That's where you set JAVA_OPTS, CATALINA_OPTS, etc. We use it to set JAVA_HOME, JAVA_OPTS, CATALINA_OPTS and JPDA_ADDR. Putting all your environment variables into this file is ideal because then you don't have to change the stock startup scripts. Then when monitoring the log we can see the parameters taken:
View full tip
This video shows the commands to execute to deploy the training and results microservices as docker container. This is based on Docker Toolbox to highlight the specific settings required on Toolbox.   Updated Link for access to this video:  Deploying Training & Result Microservices via Docker Containers for Anomaly Detection
View full tip
This Expert Session will walk you through the Components involved in the ThingWorx Studio Augmented Reality Environment, a detailed Architecture, supported devices, and exploring the resources. The session shall provide great insight into the working and the technicalities involved in the ThingWorx Studio.   For full-sized viewing, click on the YouTube link in the player controls.   Visit the Online Success Guide to access our Expert Session videos at any time as well as additional information about ThingWorx training and services.
View full tip
This Expert Session is designed to help beginners get up and running with ThingWorx Analytics. It covers basic concepts like: What are APIs, how to configure the metadata file, and a live Demo that shows you how to interact and use ThingWorx Analytics in real time. This Expert Session would also be useful for experienced users who need a refresher course.   For full-sized viewing, click on the YouTube link in the player controls.   Visit the Online Success Guide to access our Expert Session videos at any time as well as additional information about ThingWorx training and services.
View full tip
Announcements