TMT Eye | Enterprise Intelligent Transport Operating System

Overview

TMT Eye represents the pinnacle of Fleet Management Systems (FMS), designed not just to track vehicles, but to orchestrate entire city-scale operations. The challenge was massive: build a single, unified platform capable of handling disparate verticals—Public Transit (Rehla), Waste Management, Ride-Hailing Compliance (Ujrah), and On-Demand Dispatching—without becoming a monolith of spaghetti code. I architected a modular frontend ecosystem using Next.js that treats every operational vertical as a distinct 'Product' sharing a core 'kernel' of geospatial and asset management services. The system manages thousands of live assets, processing real-time telemetry data to drive automated decisions: from dispatching a waste truck to a full bin, to optimizing bus schedules based on traffic variance. The platform enforces strict regulatory compliance through dynamic validation engines, ensuring that every driver, vehicle, and trip adheres to complex municipal laws before a wheel turns.

Key Achievements

Architected a 'Vertical-Agnostic' Core System: Designed a flexible foundational layer that handles shared entities (Vehicles, Drivers, Geofences) while allowing distinct business logic for specific modules (e.g., Waste Management bins vs. Bus Route schedules) to coexist seamlessly.

Engineered the 'Rehla' Public Transit Module: Built a complex logistics engine enabling visual route composition. Solved the N+1 problem of linking Stops-to-Routes-to-Vehicles through a graph-like state management approach, validating geospatial constraints in real-time.

Developed a High-Performance 'Live Map' Engine: Optimized Google Maps for high-density asset rendering (10,000+ entities). implemented clustering, lazy-loading viewports, and memoized marker configurations to maintain 60FPS even on low-powered dispatcher terminals.

Implemented 'Ujrah' Compliance Workflows: Digitized complex regulatory frameworks into a user-friendly wizard. The system strictly validates driver certifications and vehicle permits against government schemas before allowing dispatch, reducing legal liability.

Built a 'Polymorphic' Dispatch System: Created a unified job assignment interface that adapts strictly to the context—assigning a 'Pickup' job for logistics looks different from a 'Route' assignment for buses—sharing the same underlying database relations.

Optimized Global State Management: Leveraged TanStack Query (React Query) to implement aggressive caching and optimistic UI updates. This ensures dispatchers see immediate feedback when assigning jobs, while the system handles eventual consistency and conflict resolution in the background.

Designed a Native Internationalization (i18n) Layer: Built the entire dashboard with RTL (Right-to-Left) priority for Arabic support. The UI layout dynamically mirrors, ensuring a native experience for local operators without code duplication.

Engineered 'Smart Form' architectures: Utilized React Hook Form and Zod to create self-validating, multi-step forms for complex asset onboarding. These forms handle asynchronous backend checks (e.g., IMEI uniqueness) in real-time as the user types.