Enhancing Urban Safety: The Role of Object Detection in Smart City Surveillance Systems
Abstract
Urban safety is a critical concern in the development and management of smart cities. This article explores the transformative role of object detection technology in enhancing surveillance systems within these urban environments. Object detection, a subset of computer vision, enables the automated identification and tracking of various objects, such as vehicles, pedestrians, and unusual activities, in real-time. By integrating advanced object detection algorithms with existing surveillance infrastructures, smart cities can significantly improve public safety and response times. This paper reviews the current state of object detection technologies, their applications in urban surveillance, and the benefits they offer, including increased situational awareness, crime prevention, and efficient emergency management. Additionally, the article discusses challenges and future directions for research and development in this field, emphasizing the importance of ethical considerations and data privacy in the deployment of these technologies. Through case studies and practical examples, we illustrate how object detection is reshaping urban safety and contributing to the creation of more secure and resilient smart cities.
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