AI-Driven Autonomous Drone Ecosystem for Smart Cities: Applications in Emergency Response, Road Monitoring, and Healthcare
Keywords:
AI, Image Processing, Infrastructure, Intelligent Drones, Smart Surveillance, UAVAbstract
Artificial Intelligence (AI) has been rapidly developing as one of the leading technologies in infrastructure surveillance and healthcare frameworks, with pavement distress recognition, pothole detection, and the provision of medical services being prominent. The desire to have the proper power of this or that road network monitoring and effective healthcare support devices has prompted the use of innovative digital technologies, and specifically drone technology. Safety, precision, and efficiency in the construction setting and medical practice are increasingly becoming a critical issue. The latest advancements in computer vision which have been facilitated by the large-scale image and video analytics have made a major contribution to automated monitoring processes. Nonetheless, the shortcomings of on-ground data collection solutions have promoted the application of UAVs in an extensive coverage of the area, real-time monitoring, and extensive data gathering. This literature review explores the aspect of the application of AI integrated drone systems in smart monitoring in a systematic manner. It commences by looking at image acquiring instruments and sensors technologies, their functionality benefits, and technical limitations. The paper then examines the weaknesses and problems of pavement condition assessment methods that employ computer vision applications. New research methods for determining surface texture changes, structural cracks, potholes, wear and tear of joints, thermal effects, and rutting are discussed. Besides that, the growing use of AI-driven drones in healthcare is discussed, and their involvement in medical monitoring, logistics, and service delivery is mentioned. The future directions of research are the establishment of real-time distress detection applications on busy highways and city roads and intelligent cost-saving models to improve healthcare systems efficiency and affordability.
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