Design a multi-level, smart car parking system that integrates edge-based IoT sensing, computer vision for vehicle
detection, and cloud-driven predictive analytics to optimize parking space usage in real time. The system must
dynamically allocate slots based on vehicle type, and priority rules while enabling secure user authentication and
payment integration.
Technical Constraints:
- Slot Capacity & Sensing:.System must simulate a minimum of 100 parking slots using IR/ultrasonic sensors or computer vision for real-time detection with ≥90% accuracy.
- Cloud & Analytics: Sensor data must be logged to a free-tier cloud platform and include at least one ML model to forecast slot availability or parking demand.
- Interface & Access: A mobile/web app must support real-time slot view, booking/cancellation, and secure user authentication.
- Power & Performance: Edge devices should support low-power (battery, solar) operation with ≤5 sec data latency and offline data caching capability.
Scalable up to 100 parking slots with ≥90% accuracy, use at least one ML model to forecast slot availability, must
support real-time slot view, booking/cancellation, and secure user authentication on a mobile/web app, must be battery
powered.
A team of up to 5 students, from various disciplines of Engineering & Technology are required to participate.