Transform method concepts
FairCom Edge data transformation concepts for software developers
FairCom Edge can receive source data from sensors, equipment, and software over a variety of protocols including MQTT, OPC UA, Modbus, SQL, and JSON DB API. FairCom Edge's IoT connectors automatically collect binary data and transform it into JSON because JSON is the universal data format of the Internet.
Each transform type enhances data by reformatting, reshaping, and enriching incoming data.
FairCom provides transform types that receive incoming data in one format, and transform it to a different data format. Using the JSON Hub API, you can configure a series of transform processes that will automatically run in sequence on incoming data or on existing stored data.
Any type of data can come into FairCom Edge in any format. Transform processes can convert data to and from JSON. For example, Siemens binary UDT data can be automatically converted into JSON objects when it is received. You can then have a transform process extract property values from the JSON object and store those values as fields in the same or another table for easy querying by SQL and for delivery to services such as ThingWorx.
"jsonToDifferentTableFields"This transform type takes a JSON object in an integration table record, identifies field values in the object, and stores them in separate columns in another table record. The destination table is specified using the
"databaseName","ownerName", and"tableName"properties."tableFieldsToJson"This transform type reads specific columns from an integration table record, converts them into a JSON object, and stores the object in a specified column in the same table.
"siemensUDT2JSON"This transform type takes the Siemens UDT binary data, transforms it into a JSON object, and stores it in a column in an integration table record.
"jsonToTableFields"This transform type takes a JSON object in an integration table record, identifies field values in the object, and stores them in another field in the same table.
Transform processes are extensible using a plugin system. With custom plugins, a transform process can use AI, machine learning, or other techniques to generate and store enhanced data.