Asset Tracking Is Easy Until You Have to Do Something With the Data

Asset tracking appears straightforward at first glance - attach a tracker to an item and view its location on a map. However, the real challenge lies in extracting actionable insights from that data. Each tracking scenario requires a unique approach. The first step should be understanding what is being tracked and where it normally operates - indoors, outdoors, or both.

The desired frequency of location updates also plays a crucial role. Additional factors to consider include whether the condition of the asset matters, how long data must be retained, and the appropriate response when issues arise.

GPS is ideal for tracking assets over large geographies like fleet vehicles, trailers, or construction equipment. The GPS data pipeline typically involves transmitting the device's GPS location to a cellular network, then to a tracking platform which processes the data to generate location information and alerts. However, GPS alone does not provide actionable insights. Instead, the goal is to determine if the vehicle entered or exited a designated area, stayed idle for too long, or moved to an unauthorized location.

Radio Frequency Identification (RFID) tags offer a different approach. Instead of continuously broadcasting location data, RFID tags communicate presence to a reader when they pass by. This method is particularly effective in controlled environments like warehouses or factories where items pass through designated checkpoints. The RFID data pipeline includes the RFID tag, the reader, the event generated by the reader, and the update to the asset or inventory platform.

Bluetooth Low Energy (BLE) technology is an alternative for indoor tracking scenarios where GPS is unreliable. BLE tags and gateways provide location information based on the number of beacons in the vicinity. However, BLE accuracy is highly dependent on factors such as building layout, gateway placement, interference, battery life, and the required precision.

Incorporating sensors can provide additional context to the asset tracking system. Sensors can measure parameters like temperature, humidity, vibration, shock, door status, motion, or battery levels. This extra information becomes critical when the asset's condition is a concern. A comprehensive data model should capture both location and asset condition details, for example:

Asset:

- Location:

- Temperature:

- Movement:

- Battery:

The real challenge comes in integrating data from multiple sources. Each tracking technology generates data in its own format, requiring a normalization layer to convert all data into a consistent event format. This enables downstream analytics and alerting capabilities without worrying about the source of the data.

When an asset leaves an approved area, the system can trigger a geofence event. Based on the asset's status, a rule can be applied to determine if an alert should be generated and who should be notified. The alerting mechanism should be designed to minimize false positives, focusing on events that truly require human intervention.

Designing the system for scalability from the outset is crucial. Considerations should include device provisioning, unique asset IDs, data ingestion, database architecture, authentication, battery management, connectivity monitoring, and handling late or duplicate events. The dashboard should be seen as a tool for data visualization rather than the ultimate goal. Effective asset tracking systems are built to handle vast amounts of data reliably and provide actionable insights in real-time.