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This 57-minute EDGE AI FOUNDATION talk explores a breakthrough research in IoT-based indoor asset tracking for manufacturing environments. Learn about the comparative analysis between Raspberry Pi Pico W (Wi-Fi) and Arduino Nano 33 BLE Sense (Bluetooth Low Energy) microcontroller platforms for real-time asset location and status monitoring. Discover why the Arduino Nano 33 BLE Sense with TinyML capabilities proves to be the superior solution for tracking manufacturing assets through beacons and tags, overcoming traditional tracking limitations while integrating seamlessly with Industry 4.0 frameworks. Understand how this innovative technology can boost productivity, reduce asset loss, optimize workflows, and provide unprecedented visibility into production environments through cost-effective IoT implementation.
