IndustryXpert:

Know the developers:

TEAM: Data Dazzlers
Mohammad Sufyan (@sufyan_55) - Ai/Ml and Backend.
Navya Choudhary (@navya_55) - Ai/Ml and UI/UX
Pratik Singh (@Pratikks)- Frontend.

The need of the project..

In commercial settings, prioritizing equipment safety and compliance with safety protocols is critical to prevent accidents and uphold productiveness. However, traditional strategies for equipment inspection, emergency alert systems, and safety enforcement often fall short in phrases of performance and effectiveness. This inadequacy regularly effects in injuries and the lack of precious resources. It's clear that there may be a pressing want for revolutionary answers that could deal with these demanding situations head-on, ensuring a safer and more secure operating environment for all.

Our Project

Industrial workspaces inherently pose risks to both machinery and personnel. In recognition of this, our project is dedicated to mitigating these risks by developing a cutting-edge web-based application. Through the seamless integration of advanced technology, we aim to establish a safer and more secure industrial environment.

Key Features:

• Motion Amplification: One of our flagship features, motion amplification, revolutionizes equipment inspection processes. By processing videos of working machinery, this tool unveils subtle movements that are often imperceptible to the naked eye. By exposing critical zones for maintenance, it enables proactive measures to be taken, minimizing the risk of unexpected breakdowns and accidents.
• Emergency Alert System: In times of crisis, swift action is imperative. Our emergency alert system allows individuals to signal for help with ease. By simply making an alert pose (L pose with hands) in front of the nearest camera, an alert is raised, ensuring prompt assistance and minimizing response times in emergency situations.
• Restricted Zone Enforcement: Maintaining the integrity of restricted areas is essential for ensuring workplace safety. Through the utilization of live CCTV feeds, our platform detects unauthorized access to restricted zones. Any violations are promptly flagged, allowing for timely intervention and enforcement of safety protocols.
• Fire and Safety Gear Detection: Safety gear and fire hazards are paramount concerns in any industrial setting. Our platform addresses these concerns by employing advanced machine learning algorithms trained on custom datasets. By accurately identifying safety gear and detecting potential fire risks in real-time, we uphold the highest standards of safety and compliance.

Motion Amplification:

• Video Upload: The user will record a video of the running machine and then upload it to the platform.
• Video Processing: Our platform processes videos captured during equipment inspections, extracting crucial data.
• Pixel Intensity Comparison: We compare pixel intensity in each frame with the moving average of previous frames. This allows us to identify subtle movements indicative of potential issues.
• Amplification Algorithm: Subtle movements are amplified using advanced algorithms, making them more visible and enabling technicians to identify critical maintenance zones.
• Video Out: The amplified video is returned to the user to download as an output

Benefits

Early Detection: By amplifying subtle movements, our platform enables early detection of potential issues, preventing unexpected breakdowns and minimizing downtime.
Enhanced Maintenance: Technicians can pinpoint critical maintenance zones with precision, allowing for targeted repairs and optimization of equipment performance.
Cost Savings: Proactive maintenance reduces the need for costly emergency repairs and extends the lifespan of machinery, resulting in significant cost savings for organizations.

Emergency Alert System:

Implementation Details:

• Camera Integration: Our platform integrates with existing CCTV cameras deployed throughout the industrial facility.
• Gesture Recognition: Using YoloV8n for detection and Mediapipe for pose estimation, our system recognizes specific gestures as a signal for help.
• Real-time Alerting: When a gesture is detected, an alert is raised in real-time.

Restricted Zone Enforcement

Implementation Details:

• Live CCTV Feeds: Our platform continuously monitors live CCTV feeds from cameras positioned at entry points to restricted zones.
• Object Detection: Using YoloV8n, our system detects individuals attempting to enter restricted areas without authorization.
• Alert Generation: When unauthorized access is detected, an alert is generated, notifying designated personnel of the security breach.

Fire and Safety Gear Detection

Implementation Details:

• Custom Dataset Training: Our machine learning models are trained on a custom dataset comprising images of safety gear, such as helmets, vests, as well as fire hazards.
• Object Detection: Using YoloV8n, our system identifies safety gear worn by personnel within the facility and detects potential fire hazards through image analysis and pattern recognition.
• Alert Generation: When any of this is detected, an alert is generated.

What a user can do in the app ?

• Add cameras and apply detection models to them.
• Monitor all the camera feeds.
• View all the alerts in the dashboard.
• Share a form in their organization to collect complaints.
• View all the complaints received.

Tech Stack / Technologies Used:

• Frontend: React, Bootstrap, HTML, CSS, JavaScript
• Backend: Flask
• Database: Sqlalchemy
• Machine Learning: YOLOv8, MediaPipe
• Others: OpenCV

Project Demo:

video

Github:

link