2019/05/16 by Paolo Galluzzi, Edoardo Longo, Galluzzi, Paolo +5
Engineering · #FOS: Computer and information sciences #FOS: Electrical engineering #Indoor and Outdoor Localization Technologies #IoT-based Smart Home Systems #Networking and Internet Architecture (cs.NI) #Signal Processing (eess.SP) #Smart Grid Energy Management #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1905.06809
openalex publication_date 2019/05/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Real-time measurements on the occupancy status of indoor and outdoor spaces can be exploited in many scenarios (HVAC and lighting system control, building energy optimization, allocation and reservation of spaces, etc.). Traditional systems for occupancy estimation rely on environmental sensors (CO2, temperature, humidity) or video cameras. In this paper, we depart from such traditional approaches and propose a novel occupancy estimation system which is based on the capture of Wi-Fi management packets from users' devices. The system, implemented on a low-cost ESP8266 microcontroller, leverages a supervised learning model to adapt to different spaces and transmits occupancy information through the MQTT protocol to a web-based dashboard. Experimental results demonstrate the validity of the proposed solution in four different indoor university spaces.