Use of Air Quality Sensor Network Data for Real-time Pollution-Aware POI Suggestion

• URL: http://arxiv.org/abs/2502.09155v1
• Date: Thu, 13 Feb 2025 10:36:17 GMT
• Title: Use of Air Quality Sensor Network Data for Real-time Pollution-Aware POI Suggestion
• Authors: Giuseppe Fasano, Yashar Deldjoo, Tommaso di Noia, Bianca Lau, Sina Adham-Khiabani, Eric Morris, Xia Liu, Ganga Chinna Rao Devarapu, Liam O'Faolain,
• Abstract summary: AirSense-R is a mobile application that provides real-time, pollution-aware recommendations for points of interest (POIs) in urban environments. The proposed system aims to help users make health-conscious decisions about the locations they visit.
• Score: 10.782779065468558
• License:
• Abstract: This demo paper presents AirSense-R, a privacy-preserving mobile application that provides real-time, pollution-aware recommendations for points of interest (POIs) in urban environments. By combining real-time air quality monitoring data with user preferences, the proposed system aims to help users make health-conscious decisions about the locations they visit. The application utilizes collaborative filtering for personalized suggestions, and federated learning for privacy protection, and integrates air pollutant readings from AirSENCE sensor networks in cities such as Bari, Italy, and Cork, Ireland. Additionally, the AirSENCE prediction engine can be employed to detect anomaly readings and interpolate for air quality readings in areas with sparse sensor coverage. This system offers a promising, health-oriented POI recommendation solution that adapts dynamically to current urban air quality conditions while safeguarding user privacy. The code of AirTOWN and a demonstration video is made available at the following repo: https://github.com/AirtownApp/Airtown-Application.git.

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