Smart City Gnosys

Smart city article details

Title	Transforming Public Safety And Qol In Smart Cities: Automated Event Detection And Response Generation With Ai And Iot
ID_Doc	58829
Authors	Kashyap Pargi M.; Abraham A.; Chandra Nagavarapu S.
Year	2025
Published	Lecture Notes in Intelligent Transportation and Infrastructure, Part F99
DOI	http://dx.doi.org/10.1007/978-3-031-72959-1_12
Abstract	The convergence of the Internet of Things (IoT) and Computer Vision (CV) technologies is revolutionizing public safety and Quality of Life (QoL) in smart cities. This chapter explores how data-driven event detection and dispatch management powered by Artificial Intelligence (AI) and optimization can transform public safety. Moving beyond traditional methods like manual reporting, we propose a data-driven approach utilizing IoT sensors (i.e. optical cameras) to capture real-time data. This data feeds into advanced AI models capable of identifying and anticipating potential events, ranging from security threat detection to traffic management. Upon event detection, a robust dispatch management system integrated with AI utilizes optimization algorithms to efficiently allocate resources and route first responders. An example of a specific Automated Event Detection and Dispatch Management System (AEDDMS), known as Remote Area Management Systems (ReAMS), is presented to demonstrate the concept. ReAMS employs AI to monitor remote areas for security threats. While focusing on this example, the chapter emphasizes the broader applicability of this approach to various smart city domains. The chapter also acknowledges the challenges, future work, and societal considerations like infrastructure planning, safety, ethics, and privacy surrounding these smart city solutions. This chapter paves the way for a data and AI-driven future where technology empowers us to build safer, more resilient communities. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Author Keywords

Similar Articles

Id	Similarity	Authors	Title	Published
44380	0.884	Pati A.; Praharaj A.; Swain K.; Lenka M.R.	Real-Time Incident Monitoring For Smart Cities Using Iot	ESIC 2024 - 4th International Conference on Emerging Systems and Intelligent Computing, Proceedings (2024)
8857	0.883	Rangel E.O.; Costa D.G.; Peixoto M.M.L.	An Optimization Approach For Emergency Vehicles Dispatching And Traffic Lights Adjustments In Response To Emergencies In Smart Cities	Brazilian Symposium on Computing System Engineering, SBESC, 2021-November (2021)
24039	0.88	Salunke S.J.; Bang S.S.	Enhancing Traffic Incident Management And Regulatory Compliance Using Iot And Itms: A Mumbai Traffic Police Case Study	TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 (2024)
7092	0.88	Gautam V.; Sunidhi S.; Prasad S.	Ai-Powered Surveillance For Smart Cities	Lecture Notes in Intelligent Transportation and Infrastructure, Part F99 (2025)
60473	0.877	Ye J.; Masseran N.B.	Using Ai And Machine Learning To Realize Information System Engineering Of Smart Cities: Accurate Weather Forecasting And Emergency Response	Journal of Machine and Computing, 5, 1 (2025)
22735	0.876	Thota M.K.; Prathibhava; Gujja S.; Venugopal D.R.	Emergency Vehicle Detection Using Iot In Smart Cities	2023 International Conference on Sustainable Emerging Innovations in Engineering and Technology, ICSEIET 2023 (2023)
23586	0.875	Poredi N.; Chen Y.; Li X.; Blasch E.	Enhance Public Safety Surveillance In Smart Cities By Fusing Optical And Thermal Cameras	2023 26th International Conference on Information Fusion, FUSION 2023 (2023)
56587	0.873	Ebadinezhad S.; Abdalkarim M.S.M.; Deen Z.; Kiminou Nsimba F.M.	The Role Of Iot In Enhancing Public Safety In Smart Cities	7th International Conference on Inventive Computation Technologies, ICICT 2024 (2024)
11455	0.868	Al Maqousi A.; Basu K.; Aldweesh A.; Alkasassbeh M.	Autonomous Cyber Defense In Smart Cities: An Ai-Driven Framework For Integrated Urban Infrastructure Protection	AI-Driven Security Systems and Intelligent Threat Response Using Autonomous Cyber Defense (2025)
16541	0.868	Nwebonyi F.N.; Du X.; Gladyshev P.	Crime And Incident Watch For Smart Cities: A Sensor-Based Approach	Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, 508 LNICST (2023)