Abstract
We propose a general-purpose scalable distributed wireless load-sensing platform that serves as infrastructure for applications that necessitate the collaboration among multiple load-sensing units. The load-sensing platform consists of a host subsystem and a node subsystem. A node subsystem comprises one or multiple nodes that perform load-sensing, i.e., weight measurement, and transmit the data to the host via BLE (Bluetooth Low Energy). The host subsystem performs computation for data analysis. We demonstrate the generality of our proposed platform by building a weight scale application and a user-identification application. For the weight application, experimental results show that a four-node collaborative weight scale achieves a lower average absolute error of 0.586 grams than individual nodes, whose absolute errors range from 0.452 to 3.147 grams. In the user-identification application, which uses a kNN model for identifying a person among a small group of people based on the gait, results show the accuracy of up to 98.33%. The results confirm the mobility, flexibility, scalability, and versatility of our proposed load-sensing platform.