Understanding Datapoints
Datapoint is a unique time series data represented as a time stamped key- value pair, and is available for assets, devices, and locations in the Zoho IoT application. It is the source of data for other features in the application and is vital in creating dashboards, reports, and alarm rules.
Gateway devices and smart sensors gather information using various peripherals and transmit them as payload to the application. Datapoints extract data from these messages and store them, "as received", or "as computed data" using user-defined expressions in the corresponding managed entity.
Datapoint values stored in the datapoints are used to:
- Visualize time series data using highly customisable widgets, dashboards, and reports.
- Utilize data to generate alarms, include in dataflow, and custom functions.
The data received and stored in a datapoint can be a string, numeric, enum, boolean, or location.
Datapoint Types
Zoho IoT Application has two types of datapoints.
- Realtime Datapoints
- KPI Scheduled Datapoints
Realtime Datapoints
Realtime datapoints extract, store, and relay the immediate value identified from the key value pairs from the received message from a device.
For example, consider the climate monitoring of a room using a smart device. Every minute, the room temperature is measured by the device and sent to the application. For this, a realtime datapoint called Temperature can be created with respective key. This datapoint will continuously store the temperature data every minute as received and the datapoint value will be used in providing the live status of the room's temperature.
We can also compute values received and store as computed realtime datapoints. For example, if the temperature received is in Celsius but you wish to store it in as a new datapoint, you can compute the value using the expression [parsing_key + 273].
This computed value is then stored as Celsius.
This expression used to compute a value is created using the expression builder when setting up a data point.
Learn more about expression builder.Scheduled KPI Datapoints
Scheduled KPI Datapoints are values computed based on expressions executed at defined intervals.
For example, data about temperature of the room is sent every minute by a smart temperature device and is maintained by a realtime datapoint called "Room Temperature" in the Zoho IoT application. To calculate and store the average temperature every hour, a scheduled KPI datapoint called "Average Room Temperature" can be created. The scheduled KPI datapoint can be used to create an expression to calculate aggregate the Room Temperature datapoint values using the AVG function over the timeline period, Last 1 Hour. The scheduled KPI datapoint will now store and output the average temperature of the room the every hour.
Learn more about Schedule KPI Datapoints.Importing a Datapoint Template
Datapoints can be imported as templates in a device model, asset model, or location model from datapoint groups available in the application gallery. When a device, asset, or location based on their corresponding model is created, a datapoint based on the template is created in the instance. A custom datapoint template is added for the following reasons
Learn how to import a datapoint template in the end application or import to a model in the developer application.Creating a Custom Datapoint Template
A custom datapoint template is added for the following reasons:
- A datapoint to measure the required metric is not available in the datapoint groups imported from the application gallery
- You need a realtime datapoint with computation
- You need to add a scheduled KPI datapoint
Source and Related Datapoints
Datapoints created from templates in the model based on which the instance is created, come under source datapoints.
For example, consider a device instance labelled EM 1001, based on the Energy Meter device model. The model includes datapoint templates such as Energy, Frequency, Current, and Voltage. Therefore, the datapoints in the EM 1001 instance will include Energy, Frequency, Current, and Voltage, as the source datapoints.
Datapoints of other instances related to the current instance through look up fields come under related datapoints.
Continuing with the example, let's say the energy meter EM 1001 is linked to a location instance named Classroom IA through a lookup field called "Energy Meter". The Classroom IA instance includes two datapoints, Temperature and Humidity. As EM 1001 is associated with Classroom IA, the Energy, Frequency, Voltage, and Current datapoints become the related datapoints for Classroom IA.
With this, the related datapoints can be used while configuring KPI scheduled datapoints.
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