Use of Air Quality Sensor Network Data for Real-time Pollution-Aware POI Suggestion
Journal:
arXiv
Published Date:
Feb 13, 2025
Abstract
This demo paper introduces AirSense-R, a privacy-preserving mobile
application that delivers real-time, pollution-aware recommendations for urban
points of interest (POIs). By merging live air quality data from AirSENCE
sensor networks in Bari (Italy) and Cork (Ireland) with user preferences, the
system enables health-conscious decision-making. It employs collaborative
filtering for personalization, federated learning for privacy, and a prediction
engine to detect anomalies and interpolate sparse sensor data. The proposed
solution adapts dynamically to urban air quality while safeguarding user
privacy. The code and demonstration video are available at
https://github.com/AirtownApp/Airtown-Application.git.
