DocumentCode
271957
Title
Low-cost radar-based target identification prototype using an expert system
Author
PeÌrez, David ; Villaverde, Monica ; Moreno, Felix ; Nogar, Noemi ; Ezcurra, Felix ; Aznar, Ekaitz
Author_Institution
ETSII, Centro de Electron. Ind., Univ. Politec. de Madrid, Madrid, Spain
fYear
2014
fDate
27-30 July 2014
Firstpage
54
Lastpage
59
Abstract
Smart and green cities are hot topics in current research because people are becoming more conscious about their impact on the environment and the sustainability of their cities as the population increases. Many researchers are searching for mechanisms that can reduce power consumption and pollution in the city environment. This paper addresses the issue of public lighting and how it can be improved in order to achieve a more energy efficient city. This work is focused on making the process of turning the streetlights on and off more intelligent so that they consume less power and cause less light pollution. The proposed solution is comprised of a radar device and an expert system implemented on a low-cost platform based on a DSP. By analyzing the radar echo in both the frequency and time domains, the system is able to detect and identify objects moving in front of it. This information is used to decide whether or not the streetlight should be turned on. Experimental results show that the proposed system can provide hit rates over 80% promising a good performance. In addition, the proposed solution could be useful in kind of other applications such as intelligent security and surveillance systems and home automation.
Keywords
digital signal processing chips; expert systems; green computing; object detection; power aware computing; radar computing; radar cross-sections; radar detection; street lighting; time-frequency analysis; DSP; energy efficient city; expert system; green cities; moving object identification; pollution reduction; power consumption reduction; public lighting; radar device; radar echo analysis; smart cities; street lighting; time-frequency analysis; Cities and towns; Classification algorithms; Classification tree analysis; Correlation; Lighting; Object recognition; Radar; artificial intelligence; classification tree; expert system; green cities; machine learning; radar target identification; smart cities; street lighting;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Informatics (INDIN), 2014 12th IEEE International Conference on
Conference_Location
Porto Alegre
Type
conf
DOI
10.1109/INDIN.2014.6945483
Filename
6945483
Link To Document