This demo paper presents AirTOWN, 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 Index (AQI) 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 AQI data from sensor networks in cities such as Bari, Italy, and Cork, UK. In areas with sparse sensor coverage, interpolation techniques approximate AQI values, ensuring broad applicability. This system offers a poromsing, health-oriented POI recommendation solution that adapts dynamically to current urban air quality conditions while safeguarding user privacy.

AirTOWN: A Privacy-Preserving Mobile App for Real-Time Pollution-Aware POI Suggestion / Fasano, Giuseppe; Deldjoo, Yashar; Di Noia, Tommaso. - 15576 LNCS:(2025), pp. 35-40. ( 47th European Conference on Information Retrieval, ECIR 2025 ita 2025) [10.1007/978-3-031-88720-8_7].

AirTOWN: A Privacy-Preserving Mobile App for Real-Time Pollution-Aware POI Suggestion

Fasano, Giuseppe;Deldjoo, Yashar;Di Noia, Tommaso
2025

Abstract

This demo paper presents AirTOWN, 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 Index (AQI) 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 AQI data from sensor networks in cities such as Bari, Italy, and Cork, UK. In areas with sparse sensor coverage, interpolation techniques approximate AQI values, ensuring broad applicability. This system offers a poromsing, health-oriented POI recommendation solution that adapts dynamically to current urban air quality conditions while safeguarding user privacy.
2025
47th European Conference on Information Retrieval, ECIR 2025
9783031887192
9783031887208
AirTOWN: A Privacy-Preserving Mobile App for Real-Time Pollution-Aware POI Suggestion / Fasano, Giuseppe; Deldjoo, Yashar; Di Noia, Tommaso. - 15576 LNCS:(2025), pp. 35-40. ( 47th European Conference on Information Retrieval, ECIR 2025 ita 2025) [10.1007/978-3-031-88720-8_7].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/292021
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