Final published version
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
| Publication date | 31/01/2021 |
|---|---|
| Host publication | Ad Hoc Networks - 12th EAI International Conference, ADHOCNETS 2020, Proceedings |
| Editors | Luca Foschini, Mohamed El Kamili |
| Place of Publication | Cham |
| Publisher | Springer |
| Pages | 191-200 |
| Number of pages | 10 |
| ISBN (electronic) | 9783030673697 |
| ISBN (print) | 9783030673680 |
| <mark>Original language</mark> | English |
| Name | Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST |
|---|---|
| Volume | 345 |
| ISSN (Print) | 1867-8211 |
| ISSN (electronic) | 1867-822X |
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%.