Slide 1: Enhancing School Security with AI-driven Systems

• Overview of current school security challenges
• Importance of addressing these challenges for student and staff safety.

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Slide 2: Objectives

• Project's Objectives: Outline clear objectives.
• Need for AI-driven security systems.
• Focus on proactive threat detection and safe learning environments.

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Slide 3: Hardware

• Motherboard
• Camera
• Night Vision
• Battery Backup
• Microphone
• Exterior Shell

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Slide 4: Entrance Monitoring and Facial Recognition

• Demo: Video and pictures.
• Code Review: Brief overview of the code.
• Speed & Range Optimization
• Light Issue
• AI Model Focus: Entrance monitoring with facial recognition.

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Slide 5: Gunshot Recognition Algorithm

• Custom-developed gunshot recognition algorithm.
• Audio Data Analysis: Identifying distinct acoustic patterns.
• Alert Triggering: Immediate alerts to school administration and law enforcement.

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Slide 6: Shooter Characteristics Research

• Ongoing research on shooter characteristics.
• Importance of understanding shooter behavior and appearance.
• Enhancing threat detection.

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main.py

• Haar Cascade Classifier for face detection.
• Face Recognition: Utilizing face_recognition library.
• Real-time Verification: Detecting authorized and unauthorized faces.

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EncodeGenerator.py

• Face Encodings: Generated from student images.
• Image Processing: Handling RGB conversion and face encoding extraction.
• Error Handling: Skips problematic images.
• Storage: Encodings saved in EncodeFile.p.

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Database Integration

• Firebase Admin SDK: Setup and connectivity.
• Firebase Realtime Database: Adding new person data.
• Firebase Storage Service: Image storage and retrieval.

Slide 7: Project Timeline and Current Issues