Telemetry data collection

The Journey of Data: Telemetry Data Collection and Management

Telemetry is the automated process of collecting data from remote sources (sensors, machines, vehicles, or software) and transmitting it wirelessly or via wire to a central system for monitoring, analysis, or control. In modern industry, telemetry means more than just reading data; it involves tracking the "health status" of a system in real-time.

1. The Telemetry Data Flow Process

A telemetry system fundamentally consists of three main stages:

1. Data Generation (Collection at Source): Sensors (measuring temperature, pressure, speed) or PLC/SCADA systems generate raw data.

2. Data Transmission: Data is transported via Wi-Fi, 4G/5G, LoRaWAN, or Ethernet using protocols such as MQTT, OPC UA, HTTP, or Modbus.

3. Data Processing and Visualization: Collected data is saved to a database (InfluxDB, SQL) and converted into meaningful charts on a Dashboard (Grafana, Hubbox Cloud).

2. Types of Telemetry Data

Telemetry data collected in an industrial facility generally falls into three categories:

• Status Data: Is the device on? Is there an error? (Boolean/Binary).

• Measurement Data: Analog values, energy consumption, flow rate (Continuous variables).

• Event and Alarm Data: Unexpected downtimes, threshold violation warnings.

3. Key Technologies Used in Telemetry Collection

Several critical technologies enhance efficiency in modern telemetry architectures:

• MQTT (Message Queuing Telemetry Transport): The standard telemetry protocol of the IoT world, based on a "Publish/Subscribe" model that uses low bandwidth.

• Edge Computing: The process of local processing on devices like Hubbox to select and send only changed or critical data, rather than sending everything to the cloud.

• Time Series Databases (TSDB): Since telemetry data is time-stamped (e.g., "Temperature was 25 degrees at 10:00:01"), specialized databases that process this data at high speeds are used.

4. Telemetry Solutions with Hubbox

Hubbox Connect devices act as an "Intelligent Gateway" during the collection and transmission of telemetry data:

• Protocol Conversion: It converts data from various field languages (Modbus, S7, BACnet) into a unified telemetry format (JSON/MQTT).

• Secure Transmission: It sends data to the cloud using TLS encryption, ensuring your data cannot be intercepted in transit.

• Offline Data Buffering: If the internet connection is lost, it stores telemetry data in its local memory and resumes sending it to the center once the connection is restored.

5. Advantages of Data Collection

• Predictive Maintenance: By tracking machine vibration data, it allows you to intervene before a failure occurs.

• Efficiency Tracking (OEE): You can analyze hidden losses in production lines using telemetry data.

• Remote Diagnosis: When a problem arises, you can find the cause by examining historical telemetry records without needing to go to the site.