Paper Info
Title
A spectrum-based adaptive sampling algorithm for smart sensing
Abstract
The ever-increasing diffusion of smart pervasive systems has brought to attention the need to optimally manage available energy as well as the request for more general intelligent functionalities. In this direction the paper presents a novel spectrum-based change detection test (CDT) designed to be executed on low-power embedded devices. By exploiting the energy-based features extracted from spectral sub-bands the CDT detects changes in time variance in the incoming signal (reactions to the change might follow) as well as disambiguates between changes and aliasing phenomena. When aliasing is detected an adaptation mechanism is activated to adapt the sampling frequency to the real needs of the signal under inspection (so as to reduce energy consumption). This algorithm enhances the state-of-the-art of adaptive sampling by offering an efficient alternative to complete spectral investigation. The effectiveness of the proposed solution has been assessed on synthetic and real datasets.
Year
DOI
Venue
2017
10.1109/UIC-ATC.2017.8397444
2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)
Keywords
Field
DocType
smart systems,adaptive sampling,change detection
Change detection,Computer science,Adaptive sampling,Sampling (signal processing),Algorithm,Feature extraction,Aliasing,Time–frequency analysis,Time variance,Energy consumption
Conference
ISBN
Citations 
PageRank 
978-1-5386-1591-1
0
0.34
References 
Authors
11
3
Name
Order
Citations
PageRank
Ilaria Scarabottolo192.39
Cesare Alippi21040115.84
Manuel Roveri327230.19