Paper Info
Title
Three Methods for Energy-Efficient Context Recognition
Abstract
Context recognition is a process where (usually wearable) sensors are used to determine the context (location, activity, etc.) of users wearing them. A major problems of such context- recognition systems is the high energy cost of collecting and processing sensor data. This paper summarizes a doctoral thesis that focuses on solving this problem by proposing a general methodology for increasing the energyefficiency of context-recognition systems. The thesis proposes and combines three different methods that can adapt a system's sensing settings based on the last recognized context and last seen sensor readings.
Year
DOI
Venue
2021
10.31449/inf.v45i2.3509
INFORMATICA-AN INTERNATIONAL JOURNAL OF COMPUTING AND INFORMATICS
Keywords
DocType
Volume
context recognition, optimization, energy efficiency, Markov chains, duty-cycling, decision trees
Journal
45
Issue
ISSN
Citations 
2
0350-5596
0
PageRank 
References 
Authors
0.34
0
1
Name
Order
Citations
PageRank
Vito Janko1158.34