Abstract
Crowd monitoring and analysis has become increasingly used for unmanned aerial vehicle applications. From preventing stampede in high concentration crowds to estimating crowd density and to surveilling crowd movements, crowd monitoring and analysis have long been employed in the past by authorities and regulatory bodies to tackle challenges posed by large crowds. Conventional methods of crowd analysis using static cameras are limited due to their low coverage area and non-flexible perspectives and features. Unmanned aerial vehicles have tremendously increased the quality of images obtained for crowd analysis reasons, relieving the relevant authorities of the venues’ inadequacies and of concerns of inaccessible locations and situation. This paper reviews existing literature sources regarding the use of aerial vehicles for crowd monitoring and analysis purposes. Vehicle specifications, onboard sensors, power management, and an analysis algorithm are critically reviewed and discussed. In addition, ethical and privacy issues surrounding the use of this technology are presented.
Highlights
Crowd monitoring and analysis have been becoming vital from public security and safety viewpoints because crowd participants may show abnormal behavior
The probability of risks multiplies when coupled with strict spatiotemporal constraints, such as those exercised in religious gatherings [1,2]
Some architectures have been developed with the focus of getting connected using resourceless or resource-constrained connectivity such as drone-assisted vehicular networks (DAVN) or flying ad-hoc networks (FANET) for Internet of Things (IoT)-enabled scenarios [41,42], giving rise to the concept of internet of drones (IoD) [43,44]
Summary
Crowd monitoring and analysis have been becoming vital from public security and safety viewpoints because crowd participants may show abnormal behavior. The probability of risks multiplies when coupled with strict spatiotemporal constraints, such as those exercised in religious gatherings [1,2] In such mass gatherings, potential public health threats are even more severe, ranging from transmission of infectious diseases, thermal disorders, the possibility of terrorism incidents, and violent crowd behaviors resulting from alcohol consumption and/or substance abuse [3]. This includes emerging algorithms for crowd analysis, as well as recent advancements in crowd prediction.
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