The ever accelerating process of globalization enables more than half the population to live in cities. Thus, the air quality in cities exerts critical influence on the health status of more and more urban residents. In this article, based on urban air quality data collected through meteorological sites, mobile crowdsourcing, and IoT sensing, along with users' body signals, we propose an urban healthcare big data system named UH-BigDataSys. In this article, we first introduce a method of integrating multi-source air quality data for the data preparation of artificial-intelligence-based smart urban services. Then a testbed of UH-BigDataSys is set up with the deployment of air-quality-aware healthcare applications. Finally, we provide health guidance for urban residents in aspects of respiratory diseases, outdoor travel, sleep quality, and so on. The ultimate goal of UH-BigDataSys is for urban residents to lead healthier lives.
Toward enabling the data analytics in smart cities, a big data system is proposed for improved urban healthcare through mobile crowdsourcing and IoT sensing, along with users' body signals REF .
Urban Healthcare Big Data System Based on Crowdsourced and Cloud-Based Air Quality Indicators
IEEE Communications Magazine
IEEE Communications Magazine
Computer Science