Online Human Daily Activity Recognition with Rechargeable Wearable Sensors

Abstract

This paper describes an online human physical activity (PA) recognition system based on machine learning, using rechargeable wireless wearable sensors with body-energy harvesting. The entire system is introduced and described, including the wireless wearable sensor network with a control center (smartphone), a body-energy harvesting module as the power supply for the sensors, and a PA recognition model based on the random forest algorithm. Hardware design, software design, and algorithm design are described in detail. For the hardware design, there are two main parts: the low-power wireless wearable sensors using Bluetooth 4.0 BLE, and the energy harvesting module. Two experiments were carried out to validate the design. One was an energy harvesting and consumption experiment on the wearable sensors, which determined that harvesting human body energy to supply the wearable sensors is feasible. The other was online human PA recognition based on the rechargeable wearable sensors. According to the results, the body-energy harvesting module has almost no influence on the recognition accuracy, and using the human body movement energy harvesting system for online human PA recognition is practical.

Fabrication of Solidified Ionic Liquid with 3D Microstructures and Its Application to Vibration Energy Harvester

“…As an alternative solution to the issues, energy harvesting, which obtains electric power from external energy sources, has attracted considerable attention. (3)(4)(5)(6)(7) Among energy sources, vibration is potentially a more extractable energy than other sources such as sunlight, radio waves, and heat. (3) In addition, as vibration sources exist everywhere, there are various applications of vibration energy harvesting, e.g., wearable devices, maintenance for buildings and gas pipelines, and automotive sensors.…”