Real-Time Sensor Fusion for Loss Detection
Deploy sensor fusion technology for loss detection at self-checkout and enable a more seamless experience. Use machine learning to connect different sensors such as point-of-sale systems, weight scale sensors, cameras, and RFIDs to accurately detect checkout items.
|Target Operating System||Ubuntu* 16.04 LTS or 18.04 LTS|
|Time to Complete||Approximately 7.5 hours|
|Software Used||EdgeX Foundry*
Intel® Video Analytics API (Intel® VA API)
Intel® RFID Sensor Platform SW Toolkit (Intel® RSP SW Toolkit)
Learn how different sensor devices can use the common open-middleware framework, EdgeX Foundry, to optimize retail operations, and detect loss at checkout. The sensor fusion is implemented using a modular approach, combining point-of-sale systems, computer vision, RFID, and scale as microservices.
Gain insight into:
- EdgeX Foundry and how data flows through it
- Microservices architecture
- Benefits of edge compute in IoT
- Benefits of sensor fusion
- Loss detection
- Item verification
- Improving customer experiences
Learn to build and run an application with these capabilities:
Recognize and trigger an event on the EdgeX bus when a product has entered and exited the field of vision within a checkout area.
Use the EdgeX extensible framework for add-on services and sensors.
Use multiple edge sensors to accurately recognize items, detect discrepancies, and record a real-time transaction log (RTTL).