HARNESSING VISUAL ANALYTICS TO SUPPORT SMART CITIES DECISION MAKING

The management of urban environments within smart cities requires addressing significant environmental challenges, such as air pollution, which are crucial for public health and sustainability. This proposal will discuss integrating real life data from air quality monitoring stations and meteorological sensors to establish a comprehensive analytical framework. This research will explore how data management, advanced data analytics, and visual analytics utilizing this aggregated data, can effectively monitor pollution levels and anticipate future air quality problems and challenges. Such capabilities are expected to enable decision makers (city planners), to identify potential trends and patterns that occur in highly polluted areas and to implement timely advisories and preemptive actions. Additionally, the research will involve an investigation of the use of machine learning models to not only enhance the prediction but also the historical data analytics. A critical aspect of this research is the incorporation of humans as part of the loop. While automated systems provide essential capabilities for predicting trends and patterns, integrating human judgment and experience provides invaluable insights that will enhance the overall decision making process. This hybrid approach aims to improve decision making processes, enabling more proactive and preventive measures in urban management, thus reducing disruptions and enhancing urban resilience. By leveraging visual analytics and utilizing data management, advanced data analytics techniques and integrating human expertise and judgment, this research will demonstrate how smart cities decision makers can enhance the process of their decisions, which allow them to optimize resource utilization, and mitigate environmental impacts, thereby more effectively adapting to the needs of their residents.

MAJOR ADVISOR: Mike Bailey
COMMITTEE: Eduardo Jose Cotilla‐Sanchez
COMMITTEE: Bella Bose
COMMITTEE: Raffaele De Amicis
GCR: William Warnes