Published Online:July 2024
Product Name:The IUP Journal of Computer Sciences
Product Type:Article
Product Code:
Author Name:S Mohamed Fahad and S Nirmala Sugirtha Rajini
Availability:YES
Subject/Domain:Engineering
Download Format:PDF
Pages:10
In recent years, a rise in missing person cases has posed challenges for law enforcement. This paper explores the various issues surrounding many unresolved cases and aims to uncover the contributing factors. Using a detailed analysis of police records, the study identifies patterns and challenges in resolving missing person cases. By understanding these dynamics, law enforcement agencies can refine strategies to enhance the likelihood of resolution, emphasizing the critical need for effective measures in addressing the growing issue of missing persons. Additionally, the paper proposes an innovative approach to locating missing persons using machine learning (ML) algorithms, specifically support vector machine (SVM) and K-nearest neighbors (KNN). Utilizing facial expressions as the basis for model training, the system swiftly and accurately identifies known individuals. The system, fed with a missing person dataset from Kaggle, outputs the person’s identity based on features like gender, age and location. The results are then communicated to the police for further investigation. This streamlined approach enhances the efficiency of the search and identification process, contributing to more effective resolutions of missing person cases. The proposed system serves as a valuable tool for law enforcement in expediting investigations and addressing the critical issue of missing persons in a timely and efficient manner.
Machine learning (ML) algorithms are increasingly being used for missing person search and rescue operations. These algorithms can be utilized to analyze large datasets and identify correlations and patterns, particularly in the analysis of behavioral patterns of missing persons prior to their disappearance. The vanishing of individuals is a complex issue with various implications, impacting both public safety and law enforcement resources. It also imposes emotional distress on the families of the missing individuals.