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The rapid growth of urban populations and large public gatherings has increased the need for efficient and real-time crowd monitoring systems. Traditional methods such as manual observation and fixed cameras are limited in coverage and mobility. To overcome these issues, this project proposes a solar-powered AI-based drone system for accurate people counting. The drone uses a mounted camera to capture aerial video, providing a wide field of view for better surveillance. The captured frames are processed using the SSD (Single Shot Detector) algorithm for real-time human detection and counting. An ESP32-CAM module is used for live video streaming and data acquisition. The integration of solar panels and a battery system helps extend flight time and reduce dependence on conventional power sources. The system also includes a real-time processing pipeline with image capture, pre-processing, detection, and counting. Its quadcopter design ensures stable flight and efficient performance. Overall, the system offers a scalable, energy-efficient, and intelligent solution for applications such as public safety, event management, and urban planning.
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Sirisha et al. (2026) studied this question.
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