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Mr. Vaibhao V. Maind is an Assistant Professor in the Department of Civil Engineering at G. H. Raisoni College of Engineering and Management, Nagpur, Maharashtra, India. He is involved in teaching and academic activities in civil engineering. His contribution examines the use of intelligent technologies for urban monitoring and smart city infrastructure.
Intelligent surveillance and monitoring systems are essential for smart cities to enhance public safety, regulate traffic, safeguard infrastructure, and respond to emergencies. Conventional surveillance systems predominantly rely on video cameras and human oversight, which may restrict their capacity to identify intricate events, comprehend contextual data, and adapt to swiftly evolving urban environments. This section introduces a multimodal artificial intelligence system for surveillance and anomaly detection in smart cities, encompassing data collection, preprocessing, feature extraction, cross-modal integration, anomaly scoring, event categorisation, and alert creation. Advanced methodologies in deep learning, including convolutional neural networks, visual Transformers, recurrent neural networks, audio encoders, and multimodal attention mechanisms, are examined for urban surveillance applications. The section additionally explores privacy safeguarding, algorithmic prejudice, erroneous alerts, data protection, clarity, and ethical implementation. A proposed evaluation methodology incorporates event-detection metrics, false-alarm rates, detection delay, and cross-location generalisation.