A Surveillance with a Geographic Information System to count crowd in real-time using a Deep Convolution Neural Network with Drone Technology

Le résumé fourni par la source

Advanced urbanization processes and the growing scale of public events suggest the need for fast and accurate crowd monitoring and density assessment tools to provide safety, manage resources, and respond to emergency situations.This work presents an advanced approach that utilizes GIS with DCNN and drones to present a real-time solution for crowd monitoring and surveillance.Using the feature extraction ability of CNNs, the system achieves correct density map generation from aerial imagery of drones capturing noisy density maps, thus enhancing the reliability of crowd monitoring even in cases with occlusion and varying illumination.This is supported by the GIS platform which provides map-based analysis and visualization tools, for real-time decision-making and interventions.All the deep learning frameworks are tested with four architectures namely, CNN, InceptionResNetV2, MobileNet, and highest performing EfficientNetB0 to determine the architecture suitable for real-time applications.The experimental outcomes show that CNN models yield lower MAE and MSE values than the other models, and MobileNet and EfficientNetB0 can be considered as solution-efficient lightweight models.The integration of drones guarantees more coverage and effective movement in spatial terms making the system much flexible with high mobility in various sectors like smart city, disaster response and management, and event surveillance.Furthermore, real-time GIS-based mapping and Image overlay enable the integration of aerial data whereby stakeholders are assisted in identifying areas with density and possible risk areas.Three important issues that the proposed system would solve include data fusion, variability in the environment as well as resource limitation, making the proposed system a portable, flexible, intelligent system that would fit the needs of contemporary crowds management.

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