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Growing apprehensions surrounding public safety have captured the attentionof numerous governments and security agencies across the globe. These entitiesare increasingly acknowledging the imperative need for reliable and securecrowd-monitoring systems to address these concerns. Effectively managing humangatherings necessitates proactive measures to prevent unforeseen events orcomplications, ensuring a safe and well-coordinated environment. The scarcityof research focusing on crowd monitoring systems and their securityimplications has given rise to a burgeoning area of investigation, exploringpotential approaches to safeguard human congregations effectively. Crowdmonitoring systems depend on a bifurcated approach, encompassing vision-basedand non-vision-based technologies. An in-depth analysis of these twomethodologies will be conducted in this research. The efficacy of theseapproaches is contingent upon the specific environment and temporal context inwhich they are deployed, as they each offer distinct advantages. This paperendeavors to present an in-depth analysis of the recent incorporation ofartificial intelligence (AI) algorithms and models into automated systems,emphasizing their contemporary applications and effectiveness in variouscontexts.

Advancements In Crowd-Monitoring System: A Comprehensive Analysis of Systematic Approaches and Automation Algorithms: State-of-The-Art