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Development of a Scalable GIS-Powered Logistics Platform with Custom Mapping and Routing Capabilities
  1. case
  2. Development of a Scalable GIS-Powered Logistics Platform with Custom Mapping and Routing Capabilities

Development of a Scalable GIS-Powered Logistics Platform with Custom Mapping and Routing Capabilities

rst.software
Logistics
Supply Chain
Transport

Identifying the Challenges in Building an Advanced Geospatial Logistics System

The client faces the need for a stable, cost-effective, and high-performance logistics platform that integrates precise geospatial data and mapping solutions within their existing web infrastructure. They require real-time location-based services, route optimization, geofencing, and telematics integration to support their large user base across multiple countries, while avoiding excessive costs from third-party geospatial data sources.

About the Client

A large-scale freight and transportation company operating across multiple countries in Europe and Asia, requiring an integrated platform to manage offers, orders, locations, and geospatial data.

Key Goals for Developing an Integrated GIS-Enabled Logistics Platform

  • Create a robust, scalable mapping solution powered by open-source geospatial data, integrated seamlessly into the web platform.
  • Support over 100,000 concurrent users and process up to 6 million map-related API requests daily.
  • Implement custom data layers for industry-specific geospatial analysis, route planning, and visualization.
  • Develop interactive maps with features such as drag-and-drop route creation, markers, and tooltips.
  • Enable geolocation, geofencing, and route optimization to improve operational efficiency.
  • Reduce dependence on costly third-party geospatial data by developing custom tools and integrations.
  • Ensure system stability, high performance, and maintainability to support continuous growth across multiple regions.

Core Functional and Technical System Requirements

  • Custom geospatial data layer support with multi-source integration and styling.
  • Generation and visualization of vector and raster map tiles.
  • Map generation based on postcode ranges such as countries, regions, streets.
  • Interactive maps with drag-and-drop route creation, markers, and tooltips.
  • Advanced route management with multi-destination routing and road limitations.
  • Geocoding services supporting multiple languages, including automatic address and coordinate lookup.
  • Geofencing with automatic generation and real-time monitoring of operational zones.
  • Integration with GPS providers and telematics systems for in-depth location data collection.
  • Tools for enhancing open-source mapping data with custom functionalities and updates.

Preferred Technologies and Architectural Approaches

React for frontend development
TypeScript for maintainable and scalable codebase
Node.js for backend development
Docker for deployment and environment consistency
OpenStreetMap as the geospatial data source
Maputik, React Leaflet, Tippecanoe, TileServer GL for map rendering and tile management
RST for system stability and modular growth

Essential External System Integrations

  • Third-party geocoding API providers for address and coordinate lookup
  • GPS and telematics data sources for location tracking
  • Mapping and routing services for route optimization
  • Paid and open-source geospatial data sources for customizable data layers

Critical Non-Functional System Requirements

  • Scalable architecture to support over 100,000 concurrent users
  • Processing capacity for at least 6 million API requests daily
  • High reliability and system uptime
  • Cost-efficient integration of geospatial data sources to minimize operational expenses
  • Real-time data update mechanisms to ensure map accuracy
  • Strong security measures to protect location and user data

Expected Business Impact of the New GIS Logistics Platform

The new platform aims to enhance operational efficiency through optimized route planning, geofencing, and location management, resulting in increased user capacity and reduced data costs. It is projected to support tens of thousands of concurrent users, process millions of map requests daily, and improve logistics operations across multiple regions, thereby setting a new standard of digital infrastructure within the supply chain and transportation industry.

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