Urban Well-being: Leveraging Multi source Data for Informed Decision-Making

Our research endeavors to explore methodologies for understanding the relationship between urban data sources and citizen well-being. It seeks to identify determinants, establish effective assessment techniques, and explore solutions to share gained knowledge both within and across cities. Ultimately, we aim to assess the practicality of these approaches in addressing well-being challenges and their integration into urban planning and decision-making. The initial phase focuses on quantitatively assessing well-being, harnessing diverse data sources such as geospatial data, wearable technologies, sensor data, social media content, and surveys. AI algorithms are crucial in extracting meaningful insights, enhancing our well-being dataset. In the subsequent phase, we intend to explore whether transfer learning techniques could be useful for sharing the gained knowledge between cities. This step promises to enhance the scalability and adaptability of our findings. The final phase is dedicated to evaluating the feasibility and effectiveness of these methodologies in addressing well-being challenges. It involves the development of real-world prototypes in the context of citizens' well-being, with collaborative support from the OuluHealth ecosystem and other University of Oulu departments.