• DocumentCode
    271957
  • Title

    Low-cost radar-based target identification prototype using an expert system

  • Author

    Pérez, 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