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Artificial Intelligence facial recognition technology has great promise for speeding up and improving the accuracy of missing person searches. The method uses artificial intelligence algorithms to compare the faces of individuals who go missing with live footage captured by security cameras. This article proposes a method for discovering individuals who have vanished using facial recognition technology in video surveillance systems. People using video surveillance systems' facial recognition technology. The approach entails gathering information about the missing individual, compiling a database of face photos, and then utilising AI algorithms to match those photographs with real-time camera footage. A subfield of computer science called artificial intelligence (AI) aims to build intelligent computers that are able to do tasks that would typically need human intelligence. Included are speech recognition, visual perception, decision-making, and language translation. Artificial Intelligence (AI) systems are designed to learn from data and improve with time through the application of machine learning techniques. Deep learning, a type of machine learning, has developed as a strong approach for training multilayered artificial neural networks, allowing AI systems to recognise complicated patterns and make accurate predictions. The tool can be used to quickly identify and locate missing persons in public places like train stations and airports. The proposed method may accelerate and improve the precision of missing person searches, increasing the likelihood of fruitful reunions. Using the Convolutional Neural Network (CNN) algorithm in conjunction with facial recognition is a popular approach that has shown encouraging outcomes for missing person detection. CNN is a popular deep learning technique for picture identification and classification, which makes it a strong contender for facial recognition applications.
Musthafa et al. (Fri,) studied this question.