Authors: Antonio Guillen-Perez; Maria-Dolores Cano
Addresses: Department of Information and Communication Technologies, Universidad Politécnica de Cartagena, Cartagena, 30202, Spain ' Department of Information and Communication Technologies, Universidad Politécnica de Cartagena, Cartagena, 30202, Spain
Abstract: 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, characterising, and localising pedestrians in outdoor environments, called intelligent pedestrian characterisation using WiFi (iPCW). 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%.
Keywords: artificial intelligence; intelligent transportation systems; people counting; sensor systems; smart cities; WiFi.
International Journal of Sensor Networks, 2021 Vol.37 No.1, pp.48 - 60
Received: 28 Jan 2021
Accepted: 28 Jan 2021
Published online: 22 Sep 2021 *