Metering Scenario Examples¶

This page introduces some common scenarios of the metering process for OU messages.

Scenario 1: Messages from Directly Connected Devices and Gateway Devices¶

A building has installed 5 air conditioning devices, including 2 smart devices and 3 non-smart devices. Now it is necessary to transmit the temperature, humidity, and operating status of these air conditioning devices to EnOS Cloud for centralized management. At the same time, users need to send control commands to these devices through EnOS Cloud to remotely turn on or off the devices and adjust the working mode and temperature value.

The solution is to create air conditioning devices and Edge gateway devices in the EnOS Device Connectivity & Management Service. Smart devices connect directly to the cloud based on the MQTT protocol, while gateway devices connect non-smart devices to the cloud based on the MQTT protocol. Users can view real-time measurement point data and send service invocation commands to devices through the Device Connectivity & Management Service.

Assumption¶

In this scenario, there are input operations from devices to the Device Connectivity & Management Service, as well as output operations from the Device Connectivity & Management Service to devices:

Input operations:
- 2 Smart devices:
  - Each device reports measurement point data once every 6 minutes on average, i.e., 10 times per device per hour, totaling 20 times per hour.
  - Each device has 6 measurement points, with an average data size of 20 bytes per measurement point, which means each device reports 120 bytes per report, totaling 2,400 bytes.
- 3 Non-smart devices: 1 gateway device connects these 3 sub-devices.
  - The gateway device collects measurement point data every 5 minutes, which means the gateway device collects data 12 times per hour.
  - Each device has 6 measurement points, which means the gateway device’s message contains 18 measurement points. The average data size of each measurement point is 20 bytes, which means the gateway device reports 360 bytes per report.
Output operations: 2 call command is issued to each air conditioning unit every day, i.e., 6 times per day. The average data size of each command is 100 bytes, i.e., 600 bytes per day.

Metering Results¶

Number of input messages per day = (20 operations/hour × 2,400 bytes/operation × 24 hours/day ÷ 512 bytes/message) + (12 operations/hour × 360 bytes/operation × 24 hours/day ÷ 512 bytes/message) ≈ 5 messages
Number of output messages per day = 600 bytes/day ÷ 512 bytes/message ≈ 2 messages
Total number of messages per day = 5 + 2 = 7 messages

Scenario 2: Messages from Third-Party System¶

Real-time data from electric meter devices are uploaded to a third-party system and now needs to be integrated and transferred to the Azure IoT Hub via the EnOS Device Data Integration Service.

The solution is to create 2 flows in Device Data Integration Service. In one flow, you can create an HTTP client to extract data from the third-party system every 1 minute, and process the extracted data. Another flow can be used to send the data to Azure IoT Hub every 5 minutes.

Assumption¶

In this scenario, there are input operations from the third-party system to the Device Data Integration Service, as well as output operations from the Device Data Integration Service to Azure IoT Hub:

Input operation: Extract device data from the third-party system every 1 minute, which is 60 operations per hour.The average data size per operation is 20 bytes, i.e., 1,200 bytes per hour, counted as 3 EnOS standard messages.
Output operations: Send data to Azure IoT Hub every 5 minutes, which is 12 operations per hour. The average data size per operation is 50 bytes, i.e., 600 bytes per hour, counted as 2 EnOS standard message.

Metering Results¶

Number of input messages per day = 3 messages/hour × 24 hour/day = 72 messages
Number of output messages per day = 2 messages/hour × 24 hour/day = 48 messages
Total number of messages per day = 72 + 48 = 120 messages