ZeroTech

Smart Parking Management System Documentation

1. Introduction

The Smart Parking Management System is designed to optimize parking availability by integrating IoT sensors, computer vision and deep learning. It provides real-time information on parking slot availability, automatic number plate recognition (ANPR), and a App based solution for booking and navigation. The system is developed to reduce parking congestion, improve user experience and enhance security through automation and data analytics.

2. System Overview

The system consists of two major parking types:

• Private Parking: Allows pre-booking, navigation, and ANPR-based automated gate access.

• Public Parking: Uses image processing with Raspberry Pi and cameras for real-time slot monitoring, updating a centralized server for user access.

3. Key Features

• Real-time parking availability detection using IoT sensors and image processing.

• Automated parking gate system with ANPR for authorized vehicles.

• User-friendly mobile application for slot booking and navigation.

• AI-based chatbot and voice command support in regional languages.

• Data analytics and forecasting for peak hours.

• QR code-based entry for unauthorized vehicles in private parking.

• Smart navigation system to guide users to the nearest available parking spot.

• Secure authentication and user verification using encrypted databases.

• Live camera feed monitoring for enhanced security.

4. System Architecture

4.1 Hardware Components

• Cameras (IP Cameras / ESP32-CAM) for image capture.

•  ESP32 for sensor communication.

• Ultrasonic Sensors (HC-SR04) for vehicle detection.

• Raspberry Pi / Server for image processing and database handling.

• SG90 Servo Motor for gate control.

• LED Indicators for signaling parking availability.

4.2 Software Components

• Deep Learning Models (YOLOv5) for vehicle and number plate detection.

• OpenCV for image processing.

• Flask  for backend server and API integration.

• WebSockets for real-time data communication.

• React Native for front-end app development.

• Firebase for database management.

5. Workflow

1. Vehicle Detection: Ultrasonic sensor detects a car, triggering the camera.

2. Image Capture & Processing: Camera captures an image and sends it to the server.

3. ANPR Processing: If a number plate is detected, text extraction and database verification are performed.

4. Gate Control: If authorized, the gate opens; otherwise, a QR code is generated for temporary access.

5. Real-time Updates: Parking availability is updated and reflected in the user app.

6. Navigation Assistance: The system provides directions to the nearest available parking spot.

7. Exit Process: The system verifies the parked vehicle and updates slot availability upon departure.

6. Deployment

• Local Deployment: Running on a laptop/server with an RTX 3050 GPU for AI processing.

• Edge Computing: Using Raspberry Pi for localized image processing.

• Mobile App Deployment: Android and iOS compatibility for enhanced accessibility.

7. Challenges & Solutions

Challenge

Solution

Real-time Processing

GPU acceleration and optimized models

Low-Cost Hardware

Using ESP32 and Raspberry Pi for cost efficiency

Unauthorized Parking

QR code-based entry system

Network Latency

WebSocket-based real-time communication

Security Concerns

Encrypted user authentication and access control

8. Future Enhancement

• Predictive Analysis for Parking Demand

• Blockchain-based Secure Parking Transactions

• Integration with Electric Vehicle Charging Stations

• Automated Payment Systems using Wallets

• Automated Parking Assistance using Robotics

• Multilingual Support for Improved Accessibility

Task Assigned by Judges

Team Name: Zero Tech

Project Name: Parking Problem

Task to be completed:

Task 1: Deploy the comparison analysis in case of navigation

Task 2: Deploy the Level type Car parking system

Task3: Real-time Parking Availability

Goal: Display available parking slots in a mobile app/web dashboard using IoT sensors

(RFID, IR, or Ultrasonic sensors). Use GPS integration for locating nearby parking areas.

Task4: Smart Booking System

Goal: Users can pre-book parking spaces based on availability. Integrate a QR-code or OTP-

based access system for security.

Task5: Automated Entry & Exit

Goal: Implement ANPR (Automatic Number Plate Recognition) for automated vehicle

identification. Use boom barriers to allow only authorized vehicles.

Task6: Cashless & Contactless Payment

Goal: Provide online payment options (UPI, credit/debit cards, wallets). Introduce a

subscription-based or hourly billing model.

Task7: Navigation Assistance

Goal: Use AI-based routing to guide users to their reserved spot efficiently. Provide voice-

enabled turn-by-turn navigation.

Task8: IoT Sensor-Based Detection

Goal: Ultrasonic/Infrared sensors in each slot to detect vehicle presence. Sensors send real-

time data to the cloud for live updates. Red/Green LED lights to show occupied or available

slots. Digital signboards displaying slot availability at the parking entrance.

Task9: Vehicle Movement Tracking and Automated Alerts & Notifications

Goal: Monitor time spent in the parking area for optimized billing. Detect illegally parked or

unauthorized vehicles. Identify frequently congested areas to improve design. Notify users

when their parking session is about to expire. Alert admins about suspicious activities (e.g., a

car parked beyond allowed time).

*We Completed 8  task from 9 and only task 7 done partially by us.

9. Conclusion

This Smart Parking Management System provides an efficient, automated, and user-friendly approach to handling parking in urban areas, reducing congestion and improving the overall parking experience. With advancements in AI, IoT, and cloud computing, this system aims to revolutionize traditional parking infrastructure, making it more accessible, secure, and intelligent.