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

• Main Authors: Pérez, David, Villaverde, Monica, Moreno, Felix, Nogar, Noemi, Ezcurra, Felix, Aznar, Ekaitz
• Format: Conference Proceeding
• Language: English
• Subjects: artificial intelligence; Cities and towns; Classification algorithms; classification tree; Classification tree analysis; Correlation; expert system; green cities; Lighting; machine learning; Object recognition; Radar; radar target identification; smart cities; street lighting
• ISSN: 1935-4576; 2378-363X
• DOI: 10.1109/INDIN.2014.6945483

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.