Law Enforcement Companion
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Date
2022
Journal Title
Journal ISSN
Volume Title
Publisher
NHCE
Abstract
Finding fugitive offenders after they have committed a crime or an illegal act takes time and effort. It is challenging for law enforcement authorities to complete this work on their own given the rising population density and the size of any nation's landmass. This cycle is both times and works seriously. In this paper, we tried to suggest a different framework for criminal Distinguishing & Recognition using Deep learning and Heroku Cloud, i.e., Cloud Computing, which, assuming it is used by our Crime Control Organizations, would help them catch criminals from CCTV images or images uploaded by the public if seen anywhere. This system is in place to assist in capturing criminals and anyone who can upload information indicating that they saw the relevant individual at a specific location and time. In India, where conditions are always changing due to things like light, weather, and specific directions, existing solutions use conventional face acknowledgement computations, which might be problematic because there is no open public contribution. Our research paper employs LBPH, Deep Learning, and Heroku Cloud technologies to construct the system. This application can be used by law enforcement agencies to investigate crime scenes. It is now much quicker, simpler, and more effective to discover the criminal's past behaviour and movements.
This makes it easier to comprehend the motives and ideas behind criminal behaviour. Law enforcement agencies get fresh knowledge from these circumstances and are better equipped to act quickly. The opening up of this to the public may facilitate a quicker transfer of information to the agencies. As a result, this approach is more cost- and time-effective. The decision to create the paper as a website rather than an application is driven by the need for greater accessibility and discoverability.