Lightweight things-server interaction using acoustic signal distortion detection in IoT applications
Seongseop Kim, Kiho Choi, Jeonghun Cho, Daejin Park · 2017
All IoT(internet of things) devices can establish the relationship by connecting the network between other things. Also things can catch human behaviors and analyze them to predict a person's next action from data based on the cumulative behavior patterns of people. After analyzing, things can provide services to people derived from their analysis of individualized peoples behavior patterns. The proposed research will present the initial effort of the things-server interaction between IoT devices to provide user intent service using acoustic signal event detection. Acoustic signal events can be detected whenever people touch things. By collecting and sharing events between things and things, users patterns will be created server side and provide user intent event to people. In the experiments, the piezo transducers are used to detect users touch events by vibrating on the things surface using acoustic waves. Wireless connection, specifically based TCP/IP connection, is used to implement things-server interaction. Through data calculation perspective, thing-things interaction is implemented for pre-process pattern analysis to reduce the calculation amount. With these interactions, users can be provided with their intended services for individualized pattern analysis with cumulated event data at server side.