AirTOWN: A Privacy-Preserving Mobile App for Real-time Pollution-Aware POI Suggestion
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
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| _version_ | 1866916579574284288 |
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| author | Fasano, Giuseppe Deldjoo, Yashar Di Noia, Tommaso |
| author_facet | Fasano, Giuseppe Deldjoo, Yashar Di Noia, Tommaso |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_13608 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | AirTOWN: A Privacy-Preserving Mobile App for Real-time Pollution-Aware POI Suggestion Fasano, Giuseppe Deldjoo, Yashar Di Noia, Tommaso Information Retrieval 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. |
| title | AirTOWN: A Privacy-Preserving Mobile App for Real-time Pollution-Aware POI Suggestion |
| topic | Information Retrieval |
| url | https://arxiv.org/abs/2501.13608 |