Research Article
Energy Consumption and Data Amount Reduction Using Object Detection on Embedded Platform
@INPROCEEDINGS{10.1007/978-3-319-61563-9_10, author={Boris Snajder and Zoran Kalafatic and Vedran Bilas}, title={Energy Consumption and Data Amount Reduction Using Object Detection on Embedded Platform}, proceedings={Sensor Systems and Software. 7th International Conference, S-Cube 2016, Sophia Antipolis, Nice, France, December 1-2, 2016, Revised Selected Papers}, proceedings_a={S-CUBE}, year={2017}, month={7}, keywords={Wireless sensor networks Energy efficiency Image processing Object detection Data amount reduction}, doi={10.1007/978-3-319-61563-9_10} }- Boris Snajder
Zoran Kalafatic
Vedran Bilas
Year: 2017
Energy Consumption and Data Amount Reduction Using Object Detection on Embedded Platform
S-CUBE
Springer
DOI: 10.1007/978-3-319-61563-9_10
Abstract
High resolution image handling often results with high energy burden for battery-powered devices, such as sensor nodes in WSN. Motivation for this study is assessment of energy consumption of the sensor node with high-resolution camera, featuring image processing. We present a selection of object detection algorithms and evaluate their efficiency. To verify applicability of those algorithms, we acquired image sequence that correspond to applications of pests detection in agriculture. We verified considered algorithms’ performances: recall, precision and expected reduction of the data amount. Energy required to execute considered algorithms was measured on ARM processor based platform. Our results show that object extraction on a node can provide reduction of the data amount by up to three orders of magnitude. While simple algorithms can lead to lower overall energy consumption of the node, the more complex algorithm provides better performances, but at a cost of prohibitively high energy consumption.
