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Development of a Scalable Route and Fare Testing Platform for Public Transportation Systems

innokrea.com

Logistics

Information technology

GPS

Challenge in Ensuring Public Transport System Accuracy and Adaptability

The growing public transport market demands precise and adaptable mobile applications. Existing manual testing methods are inefficient and error-prone, leading to potential inaccuracies in route optimization and fare calculations. Developers require automated tools to simulate diverse travel conditions and ensure system reliability.

About the Client

A global provider of solutions for the mobile world, specializing in public transportation systems and employing 3,000 people worldwide.

Objectives for Developing Route and Fare Testing Software

Automate testing of route and fare systems to improve accuracy and efficiency
Reduce operational costs associated with manual testing and system errors
Enable scalability to handle peak times, dynamic pricing, and route changes
Ensure compliance with regulatory standards for fare systems
Integrate continuous testing into development pipelines for ongoing improvements

Core Functionalities and Features

Creation of advanced test scenarios with customizable travel conditions
Simulation of dynamic variables (e.g., peak hours, special fares)
Generation of detailed reports for error identification and resolution
Web and console application interfaces for developer flexibility
Integration with external systems for real-time data validation

Technologies for Implementation

Docker

MongoDB

NestJS

React

TypeScript

External System Integrations

Route planning APIs
Fare calculation engines

Non-Functional Requirements

Scalability to handle thousands of concurrent test scenarios
High performance for rapid simulation and reporting
Security measures for data privacy and compliance
User-friendly interfaces for developers

Expected Business and Environmental Impact

The platform will reduce manual testing labor costs by 40-60%, cut error-related revenue losses, and save 1,000 tons of CO2 annually through optimized simulations. It will enable compliance with regulations, accelerate development cycles (e.g., 4-week console app creation), and support data-driven decisions for system improvements.