Active Alert | Devpost

Inspiration

The Active Alert system was inspired by the need to prevent crimes before they occur. By leveraging advanced technologies like artificial intelligence and machine learning, we aimed to create a proactive solution that detects anomalies and alerts authorities in real-time, enabling swift action to prevent potential crimes.

What it does

Active Alert is a comprehensive crime anomaly detection system that uses AI-powered sensors and machine learning algorithms to detect and prevent potential crimes. The system performs the following functions:

•⁠ ⁠Weapon Detection: Identifies weapons such as guns, knives, and explosives using AI-powered sensors and computer vision algorithms. ⁠Real-time Alerts: Sends immediate alerts to authorities via a mobile app, enabling prompt response and prevention of potential crimes. ⁠Incident Reporting: Allows authorities to report incidents and provide additional context, enhancing the system's learning and improvement. •⁠ ⁠Integration with Existing Systems: Seamlessly integrates with existing security infrastructure, such as CCTV cameras and alarm systems, to enhance overall security.

How we built it

Active Alert was built using:

•⁠ ⁠Python for data processing •⁠ ⁠Deep learning framework YOLO •⁠ ⁠Deep learning model CNN (Convolutional neural network)

Challenges we ran into

During development, we faced several challenges, including:

•⁠ ⁠Ensuring high accuracy in weapon detection •⁠ ⁠Addressing false positives and false negatives •⁠ ⁠Integrating with existing law enforcement systems and infrastructure •⁠ ⁠Ensuring scalability and reliability

Accomplishments that we're proud of

we are proud that our application can detect various weapons with 92% accuracy

What's next for Untitled

Our future plans include:

•⁠ ⁠Expanding Active Alert to more cities and countries •⁠ ⁠Integrating with additional data sources, such as social media and surveillance cameras •⁠ ⁠Enhancing the system to detect other types of anomalies, such as suspicious behavior