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IoT & Connectivity Tips

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Content Configuring ThingWorx C SDK Configuring C SDK client example for Tunneling Accepting Self Signed certificate Installing and configuring VNC Extension on ThingWorx Platform Configuring Tunnel Subsystem Configuring Remote Access & WebSocket tunnel widgets in a Mashup Setting up Federated ThingWorx   NOTE : For sake of brevity I'll divide this blog in sub blogs and will link them where ever needed.   Configuring ThingWorx C SDK   Pre-requisite Ensure that following two utilities are installed Cmake Make For linux platform both will likely be pre-installed Have ThingWorx configured with self-signed certificate (optional), refer to this article ThingWorx setup SSL / HTTPS on Tomcat with Self-Signed Certificate Create a Thing to which you want to bind to from the csdk example, e.g. create SteamSensor2 with ThingTemplate RemoteThingWithTunnels (below screenshot shows ThingTemplate RemoteThingWithTunnelsAndFileTransfer - this is not must for this blog we just need RemoteThingWithTunnels as we want to have our thing connected to receive property updates and also do tunneling)   Create an Application key with user that has sufficient access rights to work with remote entities Install and configure VNC server for tunneling using this blog Tunneling with ThingWorx and an Edge Device Note : Above mentioned blog is done using ThingWorx Edge Microserver, however we are only interested in installation and configuration related to the VNC server. You don't need to configure the edge device for tunneling from the above mentioned blog as we will do this later in this blog for C SDK.   Installing, configuring and launching the C SDK based client on Linux platform   To begin with ensure that you have downloaded the ThingWorx C SDK from PTC Marketplace or PTC Software Download page. Let's configure the CSDK 1. Navigate to the C SDK root directory and create a directory e.g. /csdk/cmake 2. Change directory into cmake/ 3. Check for the available compilers on the platform, with command cmake -G list   4. Choose as per your requirement, for our example here 'll pick "Unix Makefiles" Note : I'm compiling on Ubuntu 16 OS 5. Execute following command from csdk/cmake/ , eg. cmake -G "Unix Makefiles" ..   This will result in following compilation details : 6. Cmake folder now have some build files created  7. Configure the example SteamSensor for tunneling and for accepting self-signed certificate, as my ThingWorx is currently configured with HTTPS 8. Navigate to root directory and edit the main.c for SteamSensor, e.g. sudo gedit main.c Note: Feel free to use any editor of your choice, I'm using gedit Add following to enable tunneling and accepting self-signed certificates     #define ENABLE_TUNNELING 1 void twApi_SetSelfSignedOK();   9. Save the file and close 10. Make the solution to create executable out of the example SteamSensor we edited 11. Navigate to the SteamSensor example under the cmake e.g. 12. Key in command make and press enter, e.g. ~/csdk/cmake/examples/SteamSensor$ make This will build the solution and once finished it will put some new files and an executable file in the /csdk/cmake/examples/SteamSensor       Once the build is finished,    Great! now then, let's crack on with the SteamSensor executable.   13. To launch the executable it requires following syntax ./SteamSensor <hostname> <port> <appKey> <thingname> , e.g. ./SteamSensor tw802neo 443 11c784ab-dde7-400f-b244-fd7c4b217869 SteamSensor2 14. Once launched & if its successfully connected you can check the remote entity created in ThingWorx Composer, as we can see below entity as connected. Notice that in below screenshot there are some sample properties that are being pushed from the C SDK based client. You may not have them at first   15. In case you see isConnected as true but no property listed for your Thing, edit the Thing and click on Manage Bindings     Click on Remote tab to see which properties are pushed, then you have the option to either click on Add All Above Properties on the right side, which will automatically create properties under the Thing, or you can drag and drop properties on the right to bind with if you are using properties with different name. Ensure that the data type matches with the remote properties.     Done and Save.   So far C SDK installed and configured VNC server installed A Thing created with RemoteThingWithTunnel ThingTemplate An Application key to connect C SDK based client to RemoteThing in ThingWorx Bound remote properties from the C SDK client built above to the Remote Thing on ThingWorx Up Next Installing and configuring Web Socket Tunnel Extension on ThingWorx Platform Configuring ThingWorx Federation
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The .NET Framework versions 3.5 and 4.5 are required external dependencies. The ThingWorx Manufacturing Apps installer will prompt you to install these. For more information on the System requirements and External dependencies, see: Not authorized to view the specified document 3992 If you are a previous ThingWorx user, and are not using the full ThingWorx Manufacturing Apps installer, you will need to add these framework versions to the Windows operating system. An installer is available from the PTC App store for this purpose, or this can be done manually by following the instructions below. Note: both the .NET 3.5 and .NET 4.5 Frameworks are required. Do not install the .NET 3.5 Framework alone. Manually add the .NET 3.5/4.5 Framework to Windows: 1. Open the Windows Control Panel | select Programs and Features. 2. Select the option to "Turn Windows features on or off" 3. In Windows 7 (or other Standard editions), you can select the .NET framework from the list and follow the steps for installation. 4. In Windows Server 2012 (and other Server editions), select the option to "Add roles and features," then Next. For Installation type, select "Role-based or feature-based installation," then Next. Choose your server from the Server Selection menu, then Next. Then choose the framework versions and complete the install.
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Presentation associated with Recording of the Friday, November 17, 2017 ThingWorx Manufacturing Tips & Tricks Web Session. Agenda: - Overview & Application Demo - Aron Semle - Architecture Overview - Varathan Ranganathan - Q&A
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Hi Community,   Although we have reference architectures and integration paths for connecting devices to ThingWorx through Azure IoT; no one has ever written anything about doing the same from one ThingWorx to another.  I thought I’d change that and put some ideas out there around how one might go about doing this.  Although this is not officially supported or recommended by PTC; I have consulted with a number of leading SMEs on the subject, which have participated in forming the basis of my thinking outlined here.   Components Required (in order of communication path): On-premise ThingWorx Platform Protocol Adapter Toolkit* (CXS) - MQTT Azure IoT Edge Azure IoT Hub ThingWorx Azure IoT Hub Connector (CXS) Azure Cloud-hosted ThingWorx Platform   PAT (2) with codec to encode MQTT messages publishes to on-premise IoT Edge MQTT endpoint which handles store-and-forward of messages to IoT Hub.  An Azure IoT device would exist for each Thing you wish to represent on the ThingWorx servers.  The Azure IoT Hub Connector would pick-up the incoming messages and pass them on to the cloud ThingWorx which would decode the MQTT payload and map to Thing property updates.   The only part that I presently don’t like about this approach is that you’ll need to decode the MQTT messages on the ThingWorx platform in the cloud when they are received from the IoT Hub, and this mechanism will need to also need to handle encoding and publishing back to the IoT Hub if C2D (Cloud-to-Device) messages are to be implemented (aka bi-directional).  This is required as ThingWorx only supports AlwaysOn as an application level protocol so some form of mapping needs to be done.   * Another approach would be to replace the PAT with a custom agent which implements both the ThingWorx Edge SDK and the Azure IoT device SDK   Regards,   Greg Eva
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About This is the third 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 setup the ThingBerry for encrypted communication and trust via certificates. We will create a custom Root and Intermediate Certificate Authority as well as a server specific certificate. More information on the theory of Trust & Encryption can be found here: Trust &amp; Encryption - Theory As the ThingBerry is a highly unsupported environment for ThingWorx, please see this blog post for all related warnings. Preparing the environment To get started and keep all the working materials safe and secure within the scope of the pi user account, let's start creating a workspace directory and then install the openssl package cd ~ mkdir certs chmod 700 certs cd certs sudo apt-get install openssl Troubleshooting Tips Keytool To look at a specific certificate use the keytool and specify the .crt file to look at keytool -printcert -file rootca.crt This will show information on the certificate's configuration, such as signing authority or validity. Timestamps It's important, that the Chain of Trust follows a timely fashion. The Root CA has the longest expiration date. Within its validity the Intermediate CA must be valid. The server specific certificate must be valid in the timeframe of the Intermediate CA validity. As the validity is calculated based on seconds of the current (signing) action, I'm using valid days of Root CA 999 days Intermediate CA 888 days Server specific certificate 777 days Any other times, that make sense can be used, as long as the time constraints are followed. Otherwise the certificate will not be recognized as valid and will therefore not be trusted. Creating a Chain of Trust For this example we'll create a Root and Intermediate Certificate Authority (CA) as well as the server specific certificate. In a first step we can create all of the required keys. openssl genrsa -des3 -out rootca.key 4096 openssl genrsa -out intermediateca.key 4096 openssl genrsa -out server.key 4096 The -des3 option for the rootca will store a password and encrypt it within the key for more secure access. This tightens up security, so that the key for the rootca is not easily corrupted or exposed. Root Certificate Authority Having the keys, we now create the Root CA itself openssl req -new -x509 -sha256 -days 999 -key rootca.key -reqexts v3_req -extensions v3_ca -out rootca.crt Enter the information, starting with the password for the Root CA key. Use a easy to identify name for the Common Name (CN), e.g. "My Root CA" Intermediate Certificate Authority As the Intermediate CA needs to be signed / approved by the Root CA, we need a Certficiate Signing Request (CSR) openssl req -new -key intermediateca.key -reqexts v3_req -extensions v3_ca -out intermediateca.csr The v3_ca extension will mark this certificate as CA itself. This means that we can use the intermediate CA to sign other certificates as well. The CSR will be signed with the Root CA's key and certificate. For this the CSR must be sent to the whoever own the Root CA. In our case, we're the owner ourselves and have everything in the same directory, so no need to send it off to Let's Encrypt, Google or VeriSign. For signing the Intermediate CA as an actual CA, the Root CA must have a specific configuration to allow the v3_ca extension. This needs to be created via nano v3_ca.ext Into this new file, copy & paste the following: basicConstraints        = CA:TRUE subjectKeyIdentifier    = hash authorityKeyIdentifier  = keyid:always,issuer:always keyUsage                = cRLSign, dataEncipherment, digitalSignature, keyCertSign, keyEncipherment, nonRepudiation Save and exit. Finally, the Root CA is signing the Intermediate CA, using the v3_ca extension via: openssl x509 -req -in intermediateca.csr -CA rootca.crt -CAkey rootca.key -CAcreateserial -CAserial intermediateca.srl -extfile v3_ca.ext -days 888 -sha256 -out intermediateca.crt Certificate Authority Chain Having now two CAs, they need to be chained together. This is required for later to create the keystore used in Tomcat. Creating the Chain is probably the easiest part of this blog: cat intermediateca.crt rootca.crt > cachain.crt Server Specific Certificate The server specific certificate has to be signed and obtained by the Intermediate CA; for this a CSR is required. openssl req -new -key server.key -out server.csr The request is then signed with the Intermediate CA's key and certificate. For commerical certificates this signing process will be done by publicly trusted CAs, like Let's Encrypt, VeriSign or Google. In our case, we're the Intermediate CA ourselves and can sign the CSR. openssl x509 -req -in server.csr -CA intermediateca.crt -CAkey intermediateca.key -CAcreateserial -CAserial server.srl -days 777 -sha256 -out server.crt Creating Keystores For the keystore as used in Tomcat we need the CA Chain as well as the server specific certificate and the corresponding key. To generate a keystore that can be used in Tomcat, we first need to create a PKCS12 type keystore with openssl openssl pkcs12 -export -certfile cachain.crt -in server.crt -inkey server.key -out server.p12 This PKCS12 keystore can now be transformed into a JKS keystore, by importing the PKCS12 information into a new JKS keystore keytool -importkeystore -srckeystore server.p12 -srcstoretype PKCS12 -destkeystore keystore.jks -deststoretype JKS Important: the passwords for the PKCS12 keystore and the JKS keystore must match! Tomcat requires those passwords to be same - in case they are different, the configuration will not work and ThingWorx cannot be accessed through a secure connection. Configuring ThingWorx For ThingWorx, only the keystore is required. It can be copied over e.g. to certificates area in the storage directory. sudo cp keystore.jks /thingworx/storage/certificates sudo chmod 640 /thingworx/storage/certificates/keystore.jks sudo chown tomcat:tomcat /thingworx/storage/certificates/keystore.jks To enable it, Tomcat's server.xml needs to be updated. sudo nano $CATALINA_HOME/conf/server.xml Find the connector for port 80 and add a new connector after the port 80 connector: <Connector port="443" protocol="org.apache.coyote.http11.Http11NioProtocol"            maxThreads="150" connectionTimeout="20000"  redirectPort="8443"            SSLEnabled="true" scheme="https" secure="true" clientAuth="false" sslProtocol="TLSv1.2" enableLookups="false"            keystoreFile="/thingworx/storage/certificates/keystore.jks" keystorePass="<keystorePass>" /> Don't forget to update the password. Stop Tomcat sudo service tomcat stop Ensure Tomcat is actually down with ps -ef | grep tomcat If it's still running, just sudo kill it and start Tomcat again to activate the new configuration sudo service tomcat start And now? Congratulations! ThingWorx is now running on your ThingBerry using a secure channel. Access it via https://<thingberry>/Thingworx As HTTPS is automatically using port 443, you will automatically connect to the port configured in the server.xml Classic HTTP connections on port 80 can still be used. For more information about setting up ThingWorx with (self-signed) certificates also see https://support.ptc.com/appserver/cs/view/solution.jsp?n=CS193947 - there's also a note on forwarding all HTTP traffic to HTTPS. See also https://support.ptc.com/appserver/cs/view/solution.jsp?n=CS246292 for more information about using specific SSL protocols or cipher suites.
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Thingworx Analytics is offered through the User interface called Analytics Builder with some pre-configured functionality. However, should you want to create your own jobs and mashups, all features from Analytics Builder and some more are available through the Thingworx Services.  Running most functionality requires that you provide some data to run the Analytics Services. This is where the datasetRef parameter is required.        Data uploaded through Analytics Builder Any dataset uploaded through builder will require have a datasetUri as shown in the image above and format will be parquet (all small letters) datasetUri can be obtained from the list of datasets in builder Passing data as an in-body Dataset If data isn't uploaded through Analytics Builder, data can be supplied as an Infotable in the data parameter of the datasetRef. Metadata will also need to be supplied if a new dataset is being created (create Job of the AnalyticsServer_DataThing) If this data is being supplied for a scoring job, as long as the column names match up to what the model is expecting, TWX Analytics will inference them appropriately. The filter parameter is for parquet datasets already uploaded into TWXA and will take an ANSI SQL statement format to add conditions to reduce number of rows. Exclusions is an single column infotable list of the columns you wish to remove from the job you are trying to submit Example: If you want Profiles to only run on 5 out of 10 columns, you would give a list of 5 columns that you don't want to include in this exclusions infotable. Data may also be supplied as a csv file in the file repo in some cases, in which case you would give the dataseturi parameter the location of the file on the TWX File repo (of the format thingworx://UseCaseFileRepo/tempdata.csv) and the format which would be csv
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Video Author:                     Christophe Morfin Original Post Date:            March 31, 2017 Applicable Releases:        ThingWorx Analytics 7.4 to 8.1   Description: This video walks you through the use of Analysis Replay to execute analysis events on historical data.    
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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 and demo of the MFG Apps - Aron Semle, Solution Manager - Licensing Options - Serge Romano, VP Manufacturing -Installation Options and configuration of the apps - Varathan Ranganathan, SME - Q&A  
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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.
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This Zip file contains the Axeda patch (axeda-jms-plugin-<version>-machine-streams) required for proper installation and configuration of an Apache ActiveMQ server to use with the Axeda Machine Streams service (which is supported for Axeda Platform v6.8 and later). Note: Information about the Axeda Machine Streams feature is provided in the Axeda Features Guide available from the Axeda Support site, http://help.axeda.com. This patch overlay needs to be applied to the v5.8.0 ActiveMQ server installed as the Axeda Machine Streams endpoint broker, so that Axeda Platform can send streamed content to that server endpoint. Complete instructions for installing and configuring an Apache ActiveMQ server for Axeda Machine Streams are provided in the reference, Axeda® Machine Streams: A Guide to Setting Up Broker Endpoints. This guide is available with all Axeda product documentation from the PTC Support site.
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The RabbitMQ Management plugin provides a web-based interface into the inner workings of the messaging bus behind ThingWorx Flow. It is installed by the Flow installers but is an HTTP service by default and is a totally different web server than the NGINX used to front-end ThingWorx Flow. This will describe how to integrate it into the NGINX on your ThingWorx Flow server. This is necessitated by some recent browser behavior changes that make it very hard to get to the http port once you've used an https service on the same machine from the same browser.   First - let's find the user name and password for the RabbitMQ Management plugin. On a Linux server, the file /etc/rabbitmq/definitions.json will hold the name and password for the plugin's UI:         "users": [{                 "name": "flowuser",                 "password": "1780edc6b8628ace2ace72465cdc7b048c88",                 "tags": "administrator"         }],   On a Windows server, the definitions.json file can be found under [flow install location]\modules\RabbitMQ.   Of course, access to these directories should be limited.   Second - let's integrate the plugin into NGINX The best way to integrate the plugin into Flow is to let NGINX reverse proxy to the other http server running the UI for the plugin, which is exactly what happens for Thingworx itself. That way, only NGINX has to be configured for https and no other ports need to be opened to allow access to the plugin.   You need to find the file vhost-flow.conf on your system. On Linux, this will be /etc/nginx/conf.d/vhost-flow.conf. On Windows, it will be at C:\Program Files\nginx-[version]\conf\conf.d\vhost-flow.conf by default. Add the following fragment after the last location xxx {…} segment in the file:       # deal with the rabbitMQ admin tool     location ~* /rabbitmq/api/(.*?)/(.*) {         proxy_pass http://127.0.0.1:15672/api/$1/%2F/$2?$query_string;         proxy_buffering                    off;         proxy_set_header Host              $http_host;         proxy_set_header X-Real-IP         $remote_addr;         proxy_set_header X-Forwarded-For   $proxy_add_x_forwarded_for;         proxy_set_header X-Forwarded-Proto $scheme;     }       location /rabbitmq {         rewrite ^/rabbitmq$ /rabbitmq/ permanent;      }       location ~* /rabbitmq/(.*) {         rewrite ^/rabbitmq/(.*)$ /$1 break;         proxy_pass http://127.0.0.1:15672;         proxy_buffering                    off;         proxy_set_header Host              $http_host;         proxy_set_header X-Real-IP         $remote_addr;         proxy_set_header X-Forwarded-For   $proxy_add_x_forwarded_for;         proxy_set_header X-Forwarded-Proto $scheme;     }   This makes the request for /rabbitmq get pushed over to the web server at port 15672 on the Flow server.   Test the updated config file with (nginx may not exist in your normal path): nginx -t   Restart the NGINX service: Linux (one of these will work depending upon your Linux version): systemctl restart nginx service nginx restart Windows: Net stop ThingWorxOrchestrationNginx Net start ThingWorxOrchestrationNginx -or- use the Services app to restart the service   Thanks to https://groups.google.com/forum/#!topic/rabbitmq-users/l_IxtiXeZC8 for the needed config changes.   You can now use https://yourserver/rabbitmq to get to the login page for the management plugin. Login with the user and password from the definitions.json file on your system and you can now monitor the behavior of your RabbitMQ environment.
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Steps Get the IP address of the ThingWorx Analytics Server Type ip a Put that IP address into the desired web browser Your IP address may be different from the one in the picture above Add the port number of the server to the end of the IP address The Default  port number is 8080 Make sure to put a colon " : " between the end of the IP address and the start of the port number The port number could be different in some cases, depending if it was configured differently during installation Hit Enter and the main page will load.
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This script illustrates how to call a Groovy script as an external web service.  This example also applies to calling any external web service that relies on a username and password. Parameters: external_username external_password script_name import com.axeda.drm.sdk.Context import com.axeda.drm.sdk.device.DeviceFinder import com.axeda.drm.sdk.data.CurrentDataFinder import com.axeda.drm.sdk.device.Device import com.axeda.drm.sdk.data.HistoricalDataFinder import com.axeda.drm.sdk.device.DataItem import net.sf.json.JSONObject import com.axeda.drm.sdk.device.ModelFinder import groovyx.net.http.* import static groovyx.net.http.ContentType.* import static groovyx.net.http.Method.* /** * CallScriptoAsExternalWebService.groovy * * This script illustrates how to call a Groovy script as an external web service. * * @param external_username       -   (REQ):Str Username for the external web service. * @param external_password       -   (REQ):Str Password for the external web service. * @param script_name             -   (REQ):Str Script Name to call. * * */ def result try { validateParameters(actual: parameters, expected: ["external_username", "external_password", "script_name"]) // authentication tokens (username + password) def auth_tokens = [username: parameters.external_username, password: parameters.external_password] http = new HTTPBuilder( 'http://platform.axeda.com/services/v1/rest/Scripto/execute/'+parameters.script_name ) // pass in dummy parameters to the script for illustration def parammap = [key1: "val1", key2: "val2"] // Call the script     http.request (GET, JSON) {       uri.query = auth_tokens + parammap       response.success = { resp, json ->         // traverse the wrapped json response     result = json.wsScriptoExecuteResponse.content.$          }       response.failure = { resp ->         result = response.failure       }      } } catch (Throwable any) {     logger.error any.localizedMessage } return ['Content-Type': 'application/json', 'Content': result] static def validateParameters(Map args) {     if (!args.containsKey("actual")) {         throw new Exception("validateParameters(args) requires 'actual' key.")     }     if (!args.containsKey("expected")) {         throw new Exception("validateParameters(args) requires 'expected' key.")     }     def config = [             require_username: false     ]     Map actualParameters = args.actual.clone() as Map     List expectedParameters = args.expected     config.each { key, value ->         if (args.options?.containsKey(key)) {             config[key] = args.options[key]         }     }     if (!config.require_username) { actualParameters.remove("username") }     expectedParameters.each { paramName ->         if (!actualParameters.containsKey(paramName) || !actualParameters[paramName]) {             throw new IllegalArgumentException(                     "Parameter '${paramName}' was not found in the query; '${paramName}' is a reqd. parameter.")         }     } }
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ThingWorx community,   As part of a continuous re-evaluation of our third-party software requirements, we regularly add and remove support for versions of operating systems, persistence providers, and web browsers.   On this note, we are planning to end support for Ubuntu 18.04 beginning with the ThingWorx release targeted for mid-CY2022. Per its release cycle, Ubuntu will move version 18.04 into Extended Security Maintenance at this point, meaning it will no longer receive regular maintenance updates.   PTC will continue to support Ubuntu 20.04 for the immediate future and will consider supporting Ubuntu 22.04 once it becomes Generally Available (GA).   Please let me know if you have any questions or concerns.   Regards,   Walter Haydock ThingWorx Product Management
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This post is part of the series Forced Root Cause Monitoring via Mashups and Modal Popups To not feel lost or out of context, it's recommended to read the main post first. Create the Main Mashup Create a new Mashup called "rcp_MashupMain" as Page and Responsive Save and switch to the Design tab Design Add a Layout with two Columns In the right Column add another Layout (vertical) with a Header and one Row Add a Grid to the Row Add a Panel to the Header Add a Panel into the Panel (we will use a Panel-In-Panel technique for a better design experience) Set "Width" to 200 Set "Height" to 50 Set "Horizontal Anchor" to "Center" Set "Vertical Anchor" to "Middle" Delete its current "Style" and add a new custom style - all values to default (this will create a transparent border around the panel) Add a Label to the inner Panel Set "Text" to "Historic data of what went wrong" Set "Alignment" to "Center Aligned" Set "Width" to 200 Set "Top" to 14 Add a Panel to the left Column Add a Navigation Widget to the Panel This will call the Popup Window when its Navigate service is invoked (by a Validator) Set "MashupName" to "rcp_MashupPopup" Set "TargetWindow" to "Modal Popup" Set "ShowCloseButton" to false Set "ModalPopupOpacity" to 0.8 (to make the background darker and give more visual focus to the popup) Set "FixedPopupWidth" to 500 Set "FixedPopupHeight" to 300 Set "PopupScrolling" to "Off" Set "Visible" to false, so it will not be shown to the user during runtime Add a Textbox to the Panel This will show the numeric value corresponding to the State selected in the modal popup This will just be used for displaying with no other functionality - so that we can verify the actual values chosen Set "Read Only" to true Set "Label" to "Selected Reason (numeric value)" Add a Checkbox to the Panel This will be used an input for the Validator to determine if an error state is present or not Set "Prompt" to "Set this box to 'true' to trigger the popup. Set the value via the Thing to simulate a service. Once the value is set, the trigger is set to 'false' as the popup has been dealt with. A new historic entry will be created." Set "Disabled" to true Set "Width" to 250 Add a Validator to the Panel This will determine if the checkbox (based on the trigger / error state) is true or false. If the checkbox switches to true then the validator will call the Navigate service on the Navigation Widget. Otherwise it will do nothing. Click on Configure Validator Add Parameter Name: "Input" Base Type: BOOLEAN Click Done Set "Expression" to "Input" (the Parameter we just created) Set "AutoEvaluate" to true Save the Mashup Data In the Data panel on the right hand side, click on Add entity Choose the "rcp_AlertThing" and select the following services GetProperties (execute when Mashup is loaded) SetProperties QueryPropertyHistory (execute when Mashup is loaded) clearTrigger Click Done and the services will appear in the Data panel Connections After configuring the UI elements and the Data Sources we now have to connect them to implement the logic we decided on earlier GetProperties service Drag and drop the trigger property to the Checkbox and bind it to State Set the Automatically update values when able to true SetProperties service From the Navigation Widget drag and drop the selectedState property and bind it to the SetProperties service selectedReason property From the Navigation Widget drag and drop the PopupClosed event and bind it to the SetProperties service From the SetProperties service drag and drop the ServiceInvokeCompleted event and bind it to the clearTrigger service From the SetProperties service drag and drop the ServiceInvokeCompleted event and bind it to the QueryPropertyHistory service QueryPropertyHistory service Drag and drop the Returned Data's All Data to the Grid and bind it to Data On the Grid click on Configure Grid Columns Switch the position of the timestamp and selectedReason fields with their drag and drop handles For the selectedReason Set the "Column Title" to "Reason for Outage" Switch to the Column Renderer & State Formatting tab Change the format from "0.00" to "0" (as we're only using Integer values anyway) Choose the State-based Formatting Set "Dependent Field" to "selectedReason" Set "State Definition" to "rcp_AlertStateDefinition" Click Done clearTrigger service There's nothing more to configure for this service As the properties will automatically be pushed via the GetProperties service, there's no special action required after the service invoke for the clearTrigger service has been completed Validator Widget Drag and drop the Validator's TRUE event to the Navigation Widget and bind it to the Navigate service Drag and drop the Checkbox State to the Validator and bind it to the Input parameter Navigation Widget Drag and drop the Navigation Widget's selectedState to the Textbox and bind it to the Text property Save the Mashup
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This example shows how a file can be retrieved via Scripto and then displayed on a Web page. Precondition is that an asset has an uploaded file. This script assumes the file is there and that it is not extremely large (under 1 megabyte). This example uses base64 encoding to convert the file into a string. Future versions of Scripto will support other data streams so that base64 encoding will not be necessary. import com.axeda.drm.sdk.Context import com.axeda.drm.sdk.data.UploadedFile import com.axeda.drm.sdk.data.UploadedFileFinder import com.axeda.drm.sdk.device.Device import com.axeda.drm.sdk.device.DeviceFinder // This script requires parameter "id" Context ctx = Context.create(parameters.username); def response = '' try {     DeviceFinder deviceFinder = new DeviceFinder(ctx, new Identifier(parameters.id as Integer));     Device device = deviceFinder.find();     UploadedFileFinder uff = new UploadedFileFinder(ctx)     uff.device = device     uff.hint = 'photo'     def ufiles = uff.findAll()     UploadedFile ufile     if (ufiles.size() > 0) {         ufile = ufiles[0]         File f = ufile.extractFile()         response = getBytes(f).encodeBase64(false).toString()     } } catch (Exception e) {     logger.info(e.message);     response = [             faultcode: 'Groovy Exception',             faultstring: e.message     ]; } return ['Content-Type': 'data:image/png;base64', 'Content': response]; static byte[] getBytes(File file) throws IOException {     return getBytes(new FileInputStream(file)); } static byte[] getBytes(InputStream is) throws IOException {     ByteArrayOutputStream answer = new ByteArrayOutputStream(); // reading the content of the file within a byte buffer     byte[] byteBuffer = new byte[8192];     int nbByteRead /* = 0*/;     try {         while ((nbByteRead = is.read(byteBuffer)) != -1) { // appends buffer             answer.write(byteBuffer, 0, nbByteRead);         }     } finally {         is.close()     }     return answer.toByteArray(); }
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Time series prediction uses a model to predict future values based on previously observed values. Time series data differs somewhat from non-time series data in both the formatting of the data and the training of predictive models. This article will highlight several important considerations when dealing with time series data. Preparing Time Series Data: The data must contain exactly one field with Op Type “TEMPORAL” and one field with Op Type “ENTITY_ID”, which defines the identifier for an entity, such as a machine serial number. The ENTITY_ID field should remain the same as long as there are no missing timestamps and it is within the same asset but should be different for different assets or asset runs in order to accurately assign history during model training and scoring.     The TEMPORAL field is a numeric field indicating the order of the data rows for a specific entity . One should also ensure that data is formatted such that the timestamps are equally spaced (for example, one data point every minute) and that no gaps exist in the sequence of numbers.   If there are gaps in the time series data, it is recommended to restart the series after the gap as a new entity. Alternatively, if the gap is small enough (few data points), linear interpolation based on the gap endpoint values within the same entity is generally acceptable.   Model Creation in Time Series: When creating a timeseries model in Analytics Builder, you will be asked to specify a lookback size and lookahead parameter. The lookback size determines how many historical datapoints (including the current row) will be used in the model. The lookahead indicates how many time steps ahead to predict.  If the value of the goal variable is not known at time of scoring, unchecking Use Goal History will use the goal column during training but not its history during scoring.   Time Series models can also be created in Services using the Training Thing. The lookback size and lookahead parameter are specified in the CreateJob service. The virtualSensor field is used to indicate if the model should be trained to predict values for a field that will not be available during scoring. For example, one can train a time series model to predict Volume using evolving Temperature and Pressure, based on sensor data for these three variables over a period of time. However, the Volume sensor may be removed from further assets in order to reduce costs, and the predictive model can be used instead.   Two important considerations: ThingWorx Analytics will expand historical data in the time series into new columns. This process creates new features using the values of the previous time steps. Additionally, low order derivatives, together with average and standard deviation features are computed over small contiguous subgroups of the historical data.   The expansion process can make the dataset exceptionally wide, so time series training is generally significantly slower compared to training with no history on the same dataset. This gets exacerbated when lookback size = 0 (auto-windowing, a process where the system is trying to find the optimal lookback). If there are columns that are not changing or change infrequently (such as a device serial number or zip code of the device’s location), these should be marked as Static when importing the data. Any columns labeled Static will not be expanded to create new features. Care also needs to be taken to exclude any features that are known to not be relevant to the prediction. Using a large lookback can eliminate how many examples / entities the model has available to train. For example, if a lookback of 8 is used, then any entities that have less than 8 examples will not be used in training. For the same reason, scoring for time series produces less results than the number of rows provided as input: if 10 rows are provided and lookback is 6, then only 5 predictions will be produced.
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This Groovy script is called from an Expression Rule of type Location. For example, in an Expression rule ExecuteCustomObject("SendTweetWithLocation","user","password","Asset is on the move")   calls the script "SendTweetWithLocation" with the parameters in order. The twitterStatus is the text to send to twitter. Use the user/password for an actual twitter account.  Also, the script uses the implicit objects context and mobileLocation. Parameters Variable Name      Display Name twitterUser                twitterUser twitterPassword      twitterPassword twitterStatus            twitterStatus import groovyx.net.http.RESTClient import static groovyx.net.http.ContentType.* import com.axeda.drm.sdk.geofence.Geofence twitter = new RESTClient('http://twitter.com/statuses/') twitter.auth.basic parameters.twitterUser, parameters.twitterPassword twitter.client.params.setBooleanParameter 'http.protocol.expect-continue', false def statusText = "'${parameters.twitterStatus}' for device: ${context.device.serialNumber} on ${new Date()}" resp = twitter.post(path: 'update.xml',         requestContentType: URLENC,         body: [status: statusText, lat: mobileLocation.lat, long: mobileLocation.lng]) logger.info resp.status logger.info "Posted update $statusText"  
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  Hello, everyone!   With the release of ThingWorx 8.5, we’ve incorporated a lot of new functionality into our manufacturing and service apps. To cover a few, I’ve included the list below. We created a manufacturing common layer extension to bundle all the PTC-offered IoT apps (Operator Advisor, Asset Advisor, Production KPIs and Controls Advisor) into one extension to enable you to use them even more quickly. We added a UI to Operator Advisor to strengthen your development of work instructions. We introduced new shift and crew data models and user interfaces to standardize how to track workers’ shifts and crew availability. We also introduced Flexible KPIs to help you more rapidly develop apps to calculate common metrics. We enhanced the Operator Advisor MPMLink connector to allow users to access navigation criteria for filtering parameters based on required criteria with support for standard processes. We incorporated multiple context supports for assets—like different business units, separating maintenance views from production views or segmenting sites by location—to allow segmentation based on role and responsibility, showing the power of ThingWorx networks and permissions.   Today, I’d like to highlight one of these areas in particular: flexible KPI calculations.   I spoke with one of product managers, Ward (who you may recognize from this post) to learn more about what this new feature does and the value it brings the business. Here’s what he said:   Kaya: Why did we create flexible KPIs? What was the challenge users were facing that led us to create them? Ward: While there is an industry standard for KPIs such as OEE, availability, productivity and quality, many customers choose to customize the calculations slightly and use their own specific versions in their decision-making process or production monitoring.    Kaya: What do the flexible KPIs do? Can you provide an example? Ward: KPIs can now be customized by ThingTemplate; this allows users to calculate KPIs differently for different “classes” of things. Imagine you have a group of CNC machines and a group of pumps. You want to calculate the availability of each group, but the availability calculation for the CNC machines may differ slightly from the same availability calculations for pumps. With our new flexible KPIs, you’re able to customize the availability calculation to make slight tweaks or changes based on differences in machines or devices. So, you can calculate the availability for both your CNC machines and for your pumps using your customized availability calculations. You can also create your own KPIs to calculate metrics like safety incidents or waste.   Kaya: Let’s dive a little deeper there. If I want to create a quality station for my robot with custom KPIs, how exactly would I do that? Ward: Let’s consider OEE. We have an OEE ThingShape applied to our ISA95 physical ThingTemplate. This shape has services to perform the OEE calculation. You’re able to customize the service on this template, so you have the flexibility to change the way you perform OEE calculations. Now, let’s say you want to add a new KPI like mean time between repair (MTBR). To do so, you would create a MTBR ThingShape and add it to the ThingTemplates where you want OEE calculated. Then, you would update the KPI manager service GetKPINames to add your ThingShape to the list of KPIs to be executed each iteration. The SCO apps will then execute your MTBR service along with the other KPIs.   Kaya: What are their use cases? How does they improve the business? Ward: Customers can have their cells roll up OEE based on the worse performing asset and have their operations roll up on a different criterion.  If the customer wants to use a modified OEE on a machine that includes the size of the crew operating it, they can now do so on that one machine, on classes of machines or on all machines.   Kaya: Wow. You were certainly busy with 8.5 with all these new features. Can you tell me what you’re most excited about for 9.0? Ward: I’m most looking forward to High Availability. The ability to have multiple servers in an active-active mode allows me to do more processing in ThingWorx and provide a level of reliability to my customers. (Look out for info on this exciting new functionality in the future!)   Ready to get started using the flexible KPIs yourself? Check out the ThingWorx Apps Customization Guide! While you’re at it, be sure to also check out the other new features in 8.5 listed above!   Reach out with any questions and stay connected! Kaya
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This is the Second Part of Getting Started wth ThingWorx Analytics. In this video,we would be using Postman.   During this video you will learn:   -Creating a Dataset -Entering the Dataset configuration -Uploading the CSV data File to TWA Server   Updated Link for access to this video:  Getting Started with ThingWorx Analytics Part-2
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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
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