Research Article
Energy Efficient Adaptive GPS Sampling Using Accelerometer Data
@INPROCEEDINGS{10.1007/978-3-030-67369-7_14, author={Saad Ezzini and Ismail Berrada}, title={Energy Efficient Adaptive GPS Sampling Using Accelerometer Data}, proceedings={Ad Hoc Networks. 12th EAI International Conference, ADHOCNETS 2020, Paris, France, November 17, 2020, Proceedings}, proceedings_a={ADHOCNETS}, year={2021}, month={1}, keywords={Internet of Things Cognitive IoT Adaptive sampling GPS Accelerometer}, doi={10.1007/978-3-030-67369-7_14} }- Saad Ezzini
Ismail Berrada
Year: 2021
Energy Efficient Adaptive GPS Sampling Using Accelerometer Data
ADHOCNETS
Springer
DOI: 10.1007/978-3-030-67369-7_14
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%.
