A master thesis from Aalborg University
Energy Measurement and Optimization of Continuous Gesture Recognition
[Energi Måling og Optimering af Kontinuerlig Gestus Genkendelse]
Author(s)
Term
4. term
Education
Publication year
2016
Submitted on
2016-06-07
Pages
37 pages
Abstract
Energy consumption of software is becoming increasingly important as wearables, such as fitness trackers and other small battery-powered devices, are becoming a large part of our lives. These devices are typically controlled by a low-power CPU and powered by a small battery, and are thus very resource constrained. This thesis proposes a simple yet accurate method for developers to measure the energy consumption of their software. We demonstrate this method by implementing two continuous gesture recognition algorithms, and measuring their energy consumption. Furthermore we propose optimizations for these algorithms and gain up to 22 % energy reduction with no loss of accuracy, and up to 92.36 % energy reduction with 11 % loss of accuracy.
Keywords
Documents
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