AirTOWN: A Privacy-Preserving Mobile App for Real-time Pollution-Aware POI Suggestion
January 23, 2025 Β· Declared Dead Β· π European Conference on Information Retrieval
"No code URL or promise found in abstract"
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Authors
Giuseppe Fasano, Yashar Deldjoo, Tommaso Di Noia
arXiv ID
2501.13608
Category
cs.IR: Information Retrieval
Citations
0
Venue
European Conference on Information Retrieval
Last Checked
4 months ago
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.
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