Ezzini, Saad and Berrada, Ismail (2021) Energy Efficient Adaptive GPS Sampling Using Accelerometer Data. In: Ad Hoc Networks - 12th EAI International Conference, ADHOCNETS 2020, Proceedings :. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST . Springer, Cham, pp. 191-200. ISBN 9783030673680
Full text not available from this repository.Abstract
Internet of Things (IoT) is a major component of the connected world. With billions of battery-powered devices connected to the internet, energy and bandwidth consumption become significant issues. Embedding intelligence/cognition in the apparatus is recognized as one of the solutions to mitigate these issues. Global Positioning System (GPS) is recognized as one of the most energy-consuming mobile sensors in smart vehicles/systems. This paper proposes a smart adaptive sampling method for GPS sensors using the accelerometer data. Our approach adapts the sampling frequency of the GPS sensor according to the data stream of the accelerometer, without causing significant distortions to the data. In our experiment, we could reduce the GPS sensing by 78% while preserving an accuracy of 91.4%.