System requirements

Functional:

Parking Spot Allocation:

• Allocate parking based on vehicle size (motorcycle, car, truck, etc.).
• Ensure efficient use of space (avoid leaving spots unused if smaller vehicles can use them).

Entry and Exit:

• Automated gates that open when a vehicle enters/exits.
• Keep track of the parking duration for each vehicle.

User Convenience:

• Mobile app or website for finding available spots, pre-booking, or navigating within the parking lot.
• Payment system integration (credit card, mobile payments, etc.).

Security:

• Use cameras or RFID tags to detect vehicle entry/exit and prevent unauthorized access.
• Security personnel monitoring or automatic alerts for suspicious activity.

Accessibility:

• Priority parking for disabled drivers, electric vehicle charging, or other special requirements.
• Ensure clear signage and directions for smooth navigation.

Non-Functional:

Scalability: The system should handle a large number of vehicles efficiently in different parking lots.

Reliability: High availability for users with minimal downtime.

Real-Time Updates: Real-time availability of parking spots.

Security: Ensure data security and protection from breaches or fraud.

Ease of Use: The system should have an intuitive user interface.

Capacity estimation

Let’s assume the system is being built for a large parking facility in a city. For a quick estimation:

• Total Parking Spots: 500 spots (300 regular, 50 EV, 50 for large vehicles, 100 for motorcycles).
• Average Daily Traffic: 2000 vehicles per day (assuming high turnover).
• Peak Load: 10 vehicles entering/exiting per minute.

Data Storage:

• Each parking event (entry, exit, spot, payment) needs to be stored. If we assume 1 million events annually, we need a database designed to handle this scale.

API design

We’ll design APIs to handle the core functionalities:

• Parking Spot Management:
  • GET /spots/available: Retrieve available spots based on vehicle type.
  • POST /spots/reserve: Reserve a spot for a vehicle.
• Vehicle Entry/Exit:
  • POST /entry: Log vehicle entry (with license plate or RFID).
  • POST /exit: Log vehicle exit and calculate the parking fee.
• Payment Processing:
  • POST /payment: Process parking payment.
• User Account Management:
  • POST /user/signup: User registration.
  • GET /user/history: Retrieve user’s parking history.

Database design

We’ll need multiple tables to manage different aspects:

• Users Table:
  • user_id, name, email, phone, vehicle_type
• Vehicles Table:
  • vehicle_id, license_plate, vehicle_type, user_id
• Parking Spots Table:
  • spot_id, spot_type (small, large, EV, etc.), status (occupied/vacant), location
• Parking Events Table:
  • event_id, vehicle_id, spot_id, entry_time, exit_time, total_time, fee
• Payment Table:
  • payment_id, event_id, amount, payment_method, status
• Security Log Table (optional):
  • log_id, event_type (entry, exit, camera alert), time, license_plate, vehicle_id

Choice of Database:

• Use SQL for structured data like vehicles, spots, payments.
• Use NoSQL (e.g., MongoDB) for unstructured data like images, logs, or sensor data.

High-level design

Main Components:

• Entry/Exit Subsystem: Cameras or RFID readers at the gate detect and log vehicles entering or leaving.
• Parking Spot Management: Keeps track of spot availability and updates dynamically.
• User Mobile App: Users can search, reserve, and pay for spots, as well as navigate to their spot using GPS.
• Payment Processing: Connects to payment gateways to process payments securely.
• Surveillance System: Monitors the parking lot using CCTV and ensures safety.

Request flows

Vehicle Entry Flow:

1. Vehicle approaches the entrance.
2. License plate is scanned, or the user scans an RFID card.
3. The system checks available spots and assigns one based on vehicle type.
4. The user is guided to the parking spot via the mobile app or digital signs.

Payment Flow:

1. The user exits the lot, and the system calculates the parking fee based on duration.
2. The user pays through the mobile app or a payment kiosk.
3. Payment is confirmed, and the exit gate opens automatically.

Detailed component design

1. Parking Spot Management Service:

• Tasks: Track real-time spot availability using IoT sensors.
• Implementation: Use IoT devices for each parking spot. The sensor detects vehicle presence and updates the database.

2. Entry/Exit Management:

• Tasks: Automate entry/exit logging, calculate parking time, and manage gates.
• Implementation: Use cameras with license plate recognition (ANPR) or RFID readers. Integrate with spot management to assign and free up spots as vehicles enter/exit.

3. Payment Service:

• Tasks: Handle parking fee calculations and payment processing.
• Implementation: Integrate with external payment gateways (Stripe, PayPal) for online payments and provide kiosks for physical payments.

4. Mobile App:

• Tasks: Allow users to reserve spots, navigate, and pay.
• Implementation: Cross-platform mobile app using Flutter or React Native, integrated with real-time spot availability through an API.

Trade offs/Tech choices

Parking Spot Detection:

• Cameras: More expensive but accurate, can also be used for security.
• Ultrasonic Sensors: Cheaper, but less accurate and less useful for security purposes.

Database:

• SQL (e.g., PostgreSQL): Ideal for structured data (users, vehicles, spots).
• NoSQL (e.g., MongoDB): Ideal for unstructured or semi-structured data (sensor logs, images).

Mobile App:

• Flutter/React Native: Write once, run on iOS and Android.
• Native iOS/Android: For superior performance, but requires two codebases.

Failure scenarios/bottlenecks

Sensor Failure: If IoT sensors stop working, fallback to manual spot allocation or rely on cameras.

Payment Gateway Downtime: Implement multiple payment gateways to ensure redundancy.

Traffic Congestion at Entry/Exit: Add multiple entry/exit points to balance the load, or use dynamic load balancing for busy times.

Future improvements

• Dynamic Pricing: Implement surge pricing based on demand, e.g., higher prices during peak hours.
• AI Optimization: Use machine learning to predict parking lot usage and optimize spot allocation.
• Energy Efficiency: Use solar panels and motion-sensor lighting to make the parking lot eco-friendly.
• Self-driving Car Support: Develop navigation aids for autonomous vehicles to park themselves.