Intelligent Occupancy and Security Monitoring System for Smart Buildings

This project creates a smart occupancy and security monitoring system that enhances safety and energy efficiency in buildings. By detecting the presence and counting occupants in real-time, this system adjusts lighting, HVAC, and security measures based on usage patterns. Utilizing IoT technology, the system continuously monitors occupancy levels, detects unauthorized access, and ensures optimal building resource usage in real-time. Integrated with sensors such as motion detectors, cameras, and environmental sensors, the system sends data to a cloud platform for remote monitoring and storage.

Machine learning algorithms analyze the data to identify patterns, detect anomalies, and predict occupancy trends. The system provides actionable insights on building utilization, security threats, and energy-saving opportunities. It is particularly beneficial for facility managers, security teams, and businesses looking to enhance building management while optimizing resource consumption and preventing unauthorized access.

The mobile app provides live updates, alerts on security breaches, and suggestions for energy optimization, offering building managers full control and insight into their properties.

Key Features:

• Real-time occupancy and security monitoring using IoT-enabled devices.
• ML-powered anomaly detection, security breach alerts, and occupancy trend prediction.
• Cloud-based data storage for long-term monitoring, reporting, and analysis.
• Mobile app with live updates, alerts, and energy optimization suggestions.

This project includes source code, complete hardware setup, detailed analysis, and a 200-page project report in soft copy, making it an excellent choice for students exploring IoT and AI applications in smart buildings and security.