AI-Powered Multi-Agent Parking Management Solution using CrewAI
The Smart Parking Lot Management System is an intelligent multi-agent AI system built with CrewAI that revolutionizes parking lot operations. The system autonomously manages parking spaces, optimizes pricing strategies, coordinates valet services, and ensures efficient traffic flow through coordinated AI agents working together.
📝 Smart Parking System - Agent Overview
🎯 Agent Roles & Responsibilities:
🎥 Camera Controller
Captures vehicle photos at the gate Extracts license plate numbers using OCR technology Processes images in various lighting conditions
🧠 Traffic Decision Manager
Makes critical entry/exit decisions based on database lookup Determines if vehicle is NEW (not in database) or EXITING (in database) Controls the entire workflow direction
📺 Display Controller
Shows parking bills and payment information on gate display Generates QR codes for payment Presents clear, driver-friendly billing interface
💳 Payment Processor
Verifies QR code payment completions Handles payment confirmations and transaction security Coordinates with database for payment status updates
🗃️ Database Manager
Manages all parking records (entry/exit times, payments) Controls gate opening for both entries and exits Maintains data integrity and transaction logs Uses Google Sheets for data storage
🔄 Agent Workflow: Camera Controller → Reads plates Traffic Decision Manager → Entry/Exit decision Display Controller → Shows bills (exits only) Payment Processor → Handles payments (exits only) Database Manager → Records data + opens gate Total: 5 specialized agents working together for seamless parking management
flowchart TD
A[Vehicle Approaches Gate] --> B[Camera Captures Image]
B --> C[Extract License Plate]
C --> D[Database Lookup]
D --> E{Decision Point}
E -->|NOT FOUND| F[NEW ENTRY]
F --> G[Record Entry Time]
G --> H1[GATE OPENS]
E -->|FOUND| I[EXIT ATTEMPT]
I --> J[Calculate Duration]
J --> K[Display Bill & QR Code]
K --> L{Payment Confirmed?}
L -->|Yes| M[Update Database]
M --> H2[GATE OPENS]
style A fill:#lightblue
style E fill:#lightyellow
style L fill:#lightyellow
style H1 fill:#lightgreen
style H2 fill:#lightgreen
| Agent | Role | Responsibilities |
|---|---|---|
| 🏛️ Parking Director | Coordinator | Oversees all operations and ensures smooth workflow |
| 📊 Senior Parking Analyst | Analyst | Data analysis, trend identification, and strategic insights |
| 💰 Pricing Specialist | Economist | Dynamic pricing optimization and revenue management |
| 👁️ Vacancy Monitor | Monitor | Real-time space tracking and availability reporting |
- Python 3.10 - 3.14
- OpenAI API Key
- Clone the repository
git clone https://github.com/your-username/smart-parking-lot-management-system-v1.git
cd smart-parking-lot-management-system-v1- Install dependencies
pip install uv
crewai install- Environment Setup
# Copy environment template and add your API key
cp .env.example .env
# Edit .env file with your OPENAI_API_KEYExecute the parking management crew:
crewai runCustomize the system by modifying:
config/agents.yaml- Define agent roles and capabilitiesconfig/tasks.yaml- Configure task workflows and objectivessrc/smart_parking_lot_management_system/crew.py- Main crew logicsrc/smart_parking_lot_management_system/tools/- Custom tools implementation
from src.smart_parking_lot_management_system.main import run
result = run()
print(result) # Comprehensive parking management reportsmart-parking-lot-management-system-v1/
├── 📂 src/smart_parking_lot_management_system/
│ ├── 📜 __init__.py
│ ├── 📜 main.py # Entry point
│ ├── 📜 crew.py # CrewAI implementation
│ ├── 📂 config/
│ │ ├── 📜 agents.yaml # Agent definitions
│ │ └── 📜 tasks.yaml # Task definitions
│ └── 📂 tools/
│ ├── 📜 __init__.py
│ └── 📜 custom_tool.py # Parking-specific tools
├── 📂 knowledge/
│ └── 📜 user_preference.txt # Domain knowledge
├── 📜 pyproject.toml # Project dependencies
├── 📜 .env # Environment variables
└── 📜 README.md # This file
The system includes specialized parking management tools:
- Vacancy Detection: Real-time space monitoring
- Pricing Calculator: Dynamic rate computation
- Traffic Flow Analyzer: Congestion prediction
- Valet Service Coordinator: Automated valet assignment
The system generates comprehensive parking management reports including:
- 📈 Occupancy Analytics
- 💵 Revenue Optimization
- 🚦 Traffic Flow Recommendations
- 🎯 Space Utilization Insights
- 📅 Demand Forecasting
We welcome contributions! Please follow these steps:
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
Core dependencies are managed through pyproject.toml:
[project]
name = "smart-parking-lot-management-system"
python = ">=3.10,<3.14"
dependencies = [
"crewai>=0.5.0,<1.0.0",
"langchain-openai",
"pydantic"
]API Key Error: Ensure OPENAI_API_KEY is set in .env file
Python Version: Use Python 3.10-3.13 (not 3.14)
Dependency Issues: Try crewai install --force
export CREWAI_DEBUG=1
crewai run- IoT sensor integration for real-time data
- Mobile app for parking reservations
- AI-powered security monitoring
- Integration with smart city infrastructure
- Predictive maintenance scheduling
This project is licensed under the MIT License - see the LICENSE file for details.
- Built with CrewAI
- Powered by OpenAI GPT
- Inspired by modern parking management challenges
Let's revolutionize parking management with AI! 🚀