Internship_task

I. Introduction

The logistics platform is designed to provide a scalable and efficient solution for goods transportation. The platform connects users who need to transport items with a fleet of drivers, providing real-time availability, pricing, and tracking of vehicles.

II. System Architecture

The system architecture consists of the following components:

• User Interface: provides a user-friendly interface for users to book transportation services.
• Booking Service: handles booking requests, including pricing and availability.
• Driver Service: manages driver information, including availability and location.
• Vehicle Service: manages vehicle information, including type and capacity.
• GPS Tracking Service: provides real-time GPS tracking of vehicles.
• Payment Service: handles payment processing and transactions.

III. Component Design

Booking Service

• Handles booking requests, including pricing and availability.
• Interacts with the Driver Service and Vehicle Service to determine availability.
• Provides real-time pricing and availability information to the User Interface.

Driver Service

• Manages driver information, including availability and location.
• Interacts with the Booking Service to determine driver availability.
• Provides real-time driver location information to the GPS Tracking Service.

IV. Database Design

The database schema consists of the following entities:

• Users
• Drivers
• Bookings
• Vehicles
• Payment Records
• GPS Tracking Data

V. Scalability and Performance

The system is designed to handle high traffic and frequent updates. The following strategies are used to achieve scalability and performance:

• Load balancing: distributes incoming traffic across multiple instances.
• Caching: stores frequently accessed data to reduce database queries.
• Distributed databases: uses a sharded database architecture to handle high-frequency updates and transactions.

VI. Real-Time Data Handling

The system is designed to handle real-time GPS tracking data. The following strategies are used to handle real-time data:

• Message broker: uses a message broker like Apache Kafka or RabbitMQ to handle real-time GPS data updates.
• Caching: stores frequently accessed data to reduce database queries.
• Data streaming: uses a data streaming service like Apache Kafka or Amazon Kinesis to handle real-time data.

VI. DEMO

Landing Page

User Page

Drive page