Flowchart
A Smart system that can help detect criminal activities using existing security cameras. This system will use advanced Artificial Intelligence (AI) and Machine Learning Algorithms to spot potential crimes as they happen and send alerts to the authorities via a mobile app, allowing faster response from authorities during times of disaster/ preventing a disaster.
Our proposed smart system that can detect criminal activities using existing security cameras is a promising solution for enhancing public safety and preventing disasters. By leveraging the power of advanced Artificial Intelligence (AI) and Machine Learning Algorithms, the system can proactively detect and respond to criminal activities in real-time, allowing for swift action by authorities during emergencies.
The system can be seamlessly integrated with existing security cameras, which can identify potential crimes as they occur and send alerts to the authorities through a mobile app. This ensures rapid response during emergencies and the prevention of disasters, making it an essential asset for law enforcement and security agencies.
While AI and machine learning algorithms can be effective in detecting criminal activities, they are not perfect and can sometimes produce false positives. Therefore, it is important to use these technologies in conjunction with human intelligence (Human Validation Mechanism) and expertise to ensure the best possible outcomes. proposed smart system has the potential to be a game-changer in enhancing security, safeguarding communities, and improving overall safety in various settings.
The proposed solution is an AI-driven crime detection system that utilizes the existing CCTV network footage along with cutting-edge machine learning frameworks to identify criminal activity in real time and alert the authorities about potential criminal incidents through a Mobile Utility
Machine Learning Architecture that includes a pre-trained 3D CNN for feature extraction, followed by a Multiple Instance Learning model and a Video Transformer (ViViT/BERT) model along with MIL for Human Validation. Once the model detects Crime. the incident report is stored in a database and Alerts are pushed to the Authorities through the mobile utility.
Light-weight Machine Learning Algorithms including CNN for Feature Extraction and LSTM to detect crime on a Low-End Edge Device like Raspberry Pi, Along with MIL for Human Validation allowing faster inference in a Cost Efficient Infrastructure. Once the model detects Crime. the incident report is stored in a crime database and the Alerts are pushed to the Authorities through the mobile utility.
Prioritizing measures to detect and prevent criminal activities, safeguarding passengers, staff, and critical assets across airports, metros, railways, and other public spaces.
Enhancing traveler comfort and support throughout their journey across airports, metros, railways, and other public places, aiming to provide a seamless and enjoyable experience for passengers.
