Pedestrian characterisation in urban environments combining WiFi and AI
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Ingeniería TelemáticaÁrea de conocimiento
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This work was supported by DGT Ministerio del Interior (Spain) under Project SPIP2017-02230; by the AEI/FEDER EU project grant TEC2016-76465-C2-1-R (AIM), and by a pre-doctoral grant 20740/FPI/18. Fundación Séneca. Región de Murcia (Spain).Fecha de publicación
2021-01-28Editorial
INDERSCIENCE PublisherCita bibliográfica
Guillen Perez, A, Cano, M-D. Pedestrian Characterization in Urban Environments Combining WiFi and AI. International Journal of Sensor Networks. 2021; vol. 37, nº 1. https://dx.doi.org/10.1504/IJSNET.2021.117964Revisión por pares
siPalabras clave
Artificial intelligenceIntelligent transportation systems
People counting
Sensor systems
Smart cities
WiFi
Resumen
Knowing how many people there are in a given scenario offers new possibilities for the development of intelligent services. With this goal in mind, the use of sensors and Radio Frequency (RF)
signals is becoming an interesting alternative to other classic methods such as image processing for counting people. In this paper we present a novel method for counting, characterizing, and localizing pedestrians in outdoor environments, called iPCW (intelligent Pedestrian Characterization using WiFi). iPCW is a passive, device-based sensor system that incorporates artificial intelligence techniques, more specifically, machine
learning techniques. Performance evaluation using intensive computer simulations shows that iPCW
achieves excellent results, with moving and static pedestrian detection accuracy above 98% and positioning
accuracy above 92%.
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