SmartTag: An Ultra Low Power Asset Tracking and Usage Analysis IoT Device with Embedded ML Capabilities

Abstract

Assessing power tools usage helps to prolong their life cycle, as well as indicate targeted maintenance interventions after a particular series of events, e.g. drops. In this work, we propose a low power multi-sensors hardware-software co-design for extremely long shelf life, and a long operating lifecycle. The designed device is based on a Bluetooth Low Energy (BLE) system on chip (SoC) to exchange data with a gateway. NFC has been chosen to wake up the device without adding any additional power consumption. The system on a chip includes an ARM Cortex-M4F core to further process the information achieving low latency and high energy efficiency. The device hosts a temperature and humidity sensor used to monitor the storage conditions, and an accelerometer is used for condition and activity monitoring. This paper provides a proof-of-concept approach to continuously assess the usage of a power tool and detect potential mis-usages, e.g., drops. The architecture, thought to be flexible, can host both traditional signal processing and novel tiny machine learning workloads, offering a future-proof platform for several application scenarios. Experimental results highlight the advanced processing capabilities at low power consumption enabling a long lifetime of up to 4 years with a small coin battery.