From Data to Action: Exploring AI and IoT-driven Solutions for Smarter Cities

Autor:	Dias, Tiago, Fonseca, Tiago, Vitorino, João, Martins, Andreia, Malpique, Sofia, Praça, Isabel
Rok vydání:	2023
Předmět:	Computer Science - Machine Learning Computer Science - Computer Vision and Pattern Recognition Electrical Engineering and Systems Science - Systems and Control
Druh dokumentu:	Working Paper
DOI:	10.1007/978-3-031-38333-5_5
Popis:	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. Comment: 10 pages, 8 Figures, accepted for DCAI2023
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2306.04653 Zobrazit plný text záznamu View this record from Arxiv