Predictive Policing and Enhancing Security Performance through Artificial Intelligence Applications

Authors : Bensalem Kheira

Pages : 444-454

Doi:10.30622/tarr.1464788

View : 120 | Download : 141

Publication Date : 2024-12-30

Article Type : Research Paper

Abstract :The digital transformation era has revolutionized the global landscape, urging countries to modernize their infrastructures to integrate artificial intelligence (AI) applications effectively. With continuous advancements in science and technology, societies now possess unprecedented capabilities to predict and address complex phenomena. This paper explores the transformative potential of AI in disaster management and law enforcement, emphasizing its critical role in anticipating and mitigating challenges. By leveraging comprehensive data analysis and machine learning, AI enables proactive responses to both natural disasters and the globalization of crime. In disaster management, predictive AI models analyze extensive datasets, including seismic activity, geological patterns, and environmental variables, to forecast events such as earthquakes. These models empower authorities to issue early warnings, develop contingency plans, and reduce potential casualties and economic losses. The ability to anticipate disasters reflects the broader utility of AI in enhancing societal resilience and preparedness. The integration of predictive technologies not only addresses immediate challenges but also strengthens long-term strategies for sustainable development. In parallel, the globalization of crime presents unique challenges for law enforcement, requiring innovative solutions that transcend traditional methodologies. Predictive policing has emerged as a forward-looking approach that harnesses AI-driven analytics to combat the complexities of modern crime. By examining historical crime data, behavioral patterns, and environmental factors, predictive policing systems identify potential hotspots, forecast criminal activities, and allocate resources more strategically. This methodology not only enhances operational efficiency but also aligns with the principles of justice by preventing crimes before they occur. The application of AI in predictive policing extends beyond pattern recognition. Advanced algorithms adapt to the dynamic nature of criminal activities, addressing evolving trends and innovative methodologies employed by offenders. This adaptability is critical in an era where crime has become increasingly sophisticated and transnational. Furthermore, predictive policing contributes to building safer communities by fostering collaboration between law enforcement agencies and the public. By integrating technology with social engagement, these systems strengthen trust and cooperation, essential components of effective policing. This study accentuates the dual significance of predictive AI in disaster management and law enforcement. In both domains, AI transforms reactive strategies into proactive frameworks, minimizing risks and enhancing societal well-being. The use of predictive models exemplifies the potential of AI to address global challenges holistically, ensuring a future characterized by innovation, safety, and resilience. While the integration of AI presents ethical and operational considerations, its benefits in mitigating natural disasters and combating crime far outweigh potential drawbacks. In conclusion, the integration of AI into critical systems represents a valuable advancement in addressing contemporary challenges. From forecasting natural disasters to preventing criminal activities, AI applications provide innovative solutions that reshape societal responses. This paper stress the importance of leveraging predictive technologies to foster preparedness, resilience, and security in an increasingly interconnected world. By modernizing infrastructures and embracing AI-driven strategies, nations can navigate the complexities of the digital era effectively, paving the way for sustainable progress and global stability.
Keywords : Yapay zeka, Öngörücü polislik, Sorgulama, Dijital dönüşüm, Teknolojik ilerleme