From Data to Action: Exploring AI and IoT-driven Solutions for Smarter Cities
This work addresses urban management challenges for city planners and residents, but it is incremental as it applies existing AI and IoT methods to smart city data.
The paper tackles the problem of managing smart cities by introducing an AI and IoT-driven system to analyze traffic, energy consumption, and maintenance issues, with a case study in Aveiro City demonstrating effectiveness in enhancing security, efficiency, and sustainability.
The emergence of smart cities demands harnessing advanced technologies like the Internet of Things (IoT) and Artificial Intelligence (AI) and promises to unlock cities' potential to become more sustainable, efficient, and ultimately livable for their inhabitants. This work introduces an intelligent city management system that provides a data-driven approach to three use cases: (i) analyze traffic information to reduce the risk of traffic collisions and improve driver and pedestrian safety, (ii) identify when and where energy consumption can be reduced to improve cost savings, and (iii) detect maintenance issues like potholes in the city's roads and sidewalks, as well as the beginning of hazards like floods and fires. A case study in Aveiro City demonstrates the system's effectiveness in generating actionable insights that enhance security, energy efficiency, and sustainability, while highlighting the potential of AI and IoT-driven solutions for smart city development.