Modeling an Intelligent System for Effective Community Policing

Duke Oghorodi, Igwe Christian Uzoma, Chukwuemeka Nwankwo, Paschal Uchenna Chinedu, Wilson Nwankwo

Abstract


The Nigerian Law Enforcement landscape faces myriad challenges ranging from inadequate resources to new crime patterns. In response to these challenges, this paper proposes an intelligent system tailored for effective policing. Drawing from emerging advancements in AI, data analytics, and smart technology, the pro-posed system aims to revolutionize traditional policing approaches by enhancing proactive crime prevention, and efficient resource allocation. The paper adopts the object-oriented methodology. The proposed system would integrate various com-ponents, including predictive analytics and citizen reporting platforms, to create an integrated system for law enforcement agencies. Predictive algorithms analyze historical crime data to identify crime hotspots and predict future incidents, enabling law enforcement agencies to deploy resources strategically. Mobile and web frontends will empower citizens to report crimes, share information, and communicate with law enforcement authorities, fostering collaboration between the police and the community. The effectiveness of the proposed system will be evaluated through pilot implementations in selected regions of Nigeria, demonstrating its potential to reduce crime rates, improve response times, and enhance public trust in law enforcement.


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References


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