SAFECITY PLATFORM: ONLINE CRIME AND MISSING PERSONS REPORTING SYSTEM POWERED BY ML

Abstract

The increasing number of crime incidents and
missing person cases has created a significant
challenge for law enforcement agencies and
society. Traditional reporting systems rely heavily
on manual processes such as visiting police stations
and maintaining paper-based records, which leads
to delays, inefficiencies, and reduced chances of
timely intervention. To address these issues, this
project proposes the SafeCity Platform, an online
crime and missing person reporting system
powered by machine learning techniques. The
platform provides a user-friendly interface where
citizens can register, log in, and submit reports by
uploading images and relevant details. The system
ensures secure data storage using centralized
databases such as MySQL or SQLite, improving
accessibility and reliability. A key feature of the
system is its machine learning-based face
recognition module, which uses real-time camera
input to identify missing persons by comparing
captured facial data with stored records. When a
match is detected, the system automatically records
the event details and sends instant email
notifications to authorities, enabling faster
response. The platform also incorporates role-based
access control, allowing administrators to verify
and manage reports effectively. By integrating
modern technologies such as Python, Django,
OpenCV, and web-based interfaces, the SafeCity
Platform enhances transparency, reduces response
time, and improves public participation in safety
systems. Overall, the proposed system offers a
scalable, efficient, and intelligent solution for crime
reporting and missing person identification.