QRNM · Concept prototype

Qatar Road Network Monitor

One live map for every closure, diversion, and roadwork in Qatar.

Open the live prototype →

All event data is illustrative. This is a concept, not a live service.

The gap

Qatar's road information is scattered. Ashghal announces closures in one place. MOI posts incidents in another. Utilities dig on their own schedules. There is no single view — not for a control room, not for the public.

Some countries run national roadworks platforms: every closure and dig on one map, used by authorities, utilities, and drivers. The Gulf has nothing like it. So I built a concept of one, for Qatar first.

What it does

• Live network map. 33 illustrative events across Greater Doha, Lusail, and Al Khor. Closures, diversions, maintenance, utility works, permits, and public events.
• One dataset, ten viewpoints. A role switcher shows the same network through different eyes: Ashghal's control room, MOI Traffic, emergency response, public transport, logistics, and a commuter. Each role is one config entry, not a separate build.
• Journey impact. Save a home and work location, or just describe your route in plain English or Arabic. The app checks today's events against it and tells you what will hit your commute — before you leave. Live traffic apps tell you about congestion while you drive. This tells you about planned disruption in advance.
• AI briefing room. A reporting dashboard that tailors the picture to the audience — public, business, or government — with live stats, charts, and a written briefing generated in Arabic or English.
• Scenario switching. Flip the whole network between normal operations, a major incident, and severe weather, and watch every view recompute.
• Clash detection. Pure geometry: any two events within 500 m with overlapping dates get flagged. A road closure on top of a water-main dig is exactly what a shared platform catches and siloed authorities miss.
• Address lookup. Zone → street → building, through Qatar's national addressing system (QNAS).
• Bilingual by design. The chrome uses stacked Arabic-over-English labels, the same pattern as Qatari road signs. An AI layer powered by Fanar — Qatar's sovereign LLM, built by QCRI — generates the briefings and answers questions in Arabic or English, with deterministic local fallback when the service is unreachable.

Who it's for

The same road-event data serves very different people. That's the core idea — one source of truth, many lenses. Here's what each would get from it.

Ashghal / road operations. One coordinated view of the network instead of closures tracked across separate teams and spreadsheets. Clash detection would flag a planned closure sitting on top of a utility dig before both hit the same street in the same week — the kind of overlap that's expensive when it's missed and invisible until it happens.

Emergency response (Civil Defence, ambulance). Which closures block a response route, seen before the vehicle is dispatched. A life-safety lens on the same data everyone else uses for planning.

Public transport (Mowasalat) and logistics fleets. Which corridors are disrupted and for how long, so bus routes and delivery runs are planned around closures rather than discovered mid-shift.

The commuter. Their own route, checked against today's events before they leave home. Not live traffic while driving — planned disruption, in advance.

Government / executive. Network health at a glance: how many critical events, which authority owns the most disruption, where risks compound. The strategic view above the operational detail.

These are illustrations of the value each stakeholder would get from a shared platform — the prototype runs on illustrative data, not live feeds from these bodies.

How it's built

Next.js and React. Leaflet with MapTiler basemaps. Turf.js for the spatial maths. Routing runs through a three-tier fallback: live routing API, cached route, straight-line corridor. If everything upstream fails, the app still answers. Deployed on Cloudflare Workers.

The AI layer is deliberately split. Clash detection and reports are deterministic — distance and date maths, no model, no way to hallucinate. Two language models each get one job they're actually good at: Fanar writes the audience briefings in Arabic and English; Gemini Flash parses a typed sentence like "I drive from Al Waab to West Bay" into a structured route. Both are grounded in the event data, and both fall back to local computation if the service is unreachable — the app never dead-ends.

The map has to be right

This is a tool about a real city, so it has one hard rule: every coordinate is real. Each of the 33 events sits on a verified location, pulled from live map data and checked by hand. The headline closure sits on the actual Salwa Road, between the actual C-Ring and Expressway interchanges. A Doha local spots a misplaced marker in seconds, and this map is built to survive that look.

The addressing work taught me something along the way. The QNAS zone list returned three entries for zone 5, which looked like duplicate data. It wasn't. In Qatar, one numbered zone contains several named districts — zone 5 holds Fereej Al Asmakh, Al Najada, and Barahat Al Jufairi. The right fix was grouping them, not deleting real places. When data looks wrong, check your assumptions before you "clean" it.

The honest part

The software was never the hard problem. The data is.

Platforms like this work abroad because regulation forces the data to exist — authorities must register street works, and the platform sits on top of that. Qatar has no such mandate. A version of this with real data needs either the authorities as customers, publishing through their own tool, or patient aggregation of what they already announce in public.

That's a business-development problem, not a code problem. This prototype exists to make the conversation concrete: here is what the platform looks like, here is what the commuter gets, here is what the control room gets. The build is done. The interesting question is who wants it.

What I'd do next

• Bake real road geometry into routes and events (the prototype uses point markers and corridor approximation).
• Vector map tiles for full label-language control at every zoom.
• A pilot with one authority's real published data.
• Zone-based alerts by Telegram, so a subscriber gets notified when their area is affected.

Why I built this

This is a culmination of my work on Intelligent Transport Systems in Qatar. Across those projects, the same gap kept showing: no single, shared view of what's happening on the road network — nothing like it in the country, or the region. I set out to address it, and to see how far one person could take the idea on their own.

The engineering was never the hard part. Getting the data from the authorities who hold it is, and no prototype solves that — it takes the right relationships and, most likely, the authorities themselves as the customer. That's the real conversation this is meant to start.

If you're working on transport, mobility, or smart-city data in Qatar, I'm Shiraz Hussein — get in touch.

Built by Shiraz Hussein. Planned with Claude, built with Claude Code, reviewed and tested by hand.