Geomatway is a next-generation highway management platform that transforms traditional intercity roads into intelligent, adaptive corridors. Our system uses artificial intelligence to analyze and respond to real-time traffic flow, road geometry, driver behavior, weather conditions, and vehicular capacity — all in one unified decision-making platform. It adjusts speed limits, lane usage, and flow strategies dynamically, creating a safer and more efficient experience for every vehicle on the road. Designed for modern infrastructure challenges, Geomatway makes highways think, adapt, and perform.
Highways don’t adapt dynamically based on geometry, vehicle density, or predicted conditions — because no AI platform connects it all.
Highways still depend heavily on human judgment, leading to accidents caused by fatigue, distraction, or unpredictable behavior.
Static speed limits and fixed lane rules fail to adjust to live traffic conditions, causing unnecessary slowdowns and delays.
Today’s highways rely on sparse, infrastructure-based monitoring — cameras, patrols, or occasional sensors — which often miss fast-developing incidents.
Building more lanes is expensive, time-consuming, and often ineffective without smarter management of existing capacity.
Weather changes like fog, rain, or sandstorms aren’t accounted for in real-time traffic flow or speed regulation.
Current highway tech solutions work in silos — surveillance, signage, flow control, and emergency response are rarely unified.
Billions spent on widening roads or adding infrastructure — with limited long-term impact. What’s missing is intelligence.
Geomatway continuously collects and analyzes real-time data from vehicles, road conditions, and driver behavior. This enables continuous visibility across the entire network — identifying patterns, detecting anomalies, and informing system-wide decisions in milliseconds.
Rather than reacting to congestion, Geomatway forecasts it using live and historical data. The system dynamically adjusts speed limits, lane priorities, and flow rules in advance — minimizing delays and preventing buildup before it starts.
Traditional systems ignore road shape. Geomatway incorporates curves, gradients, lane width, and merging zones into its decision engine — optimizing how traffic moves based on the natural design of each segment.
The platform responds automatically to weather conditions like fog, rain, dust storms, or poor visibility — adjusting speed zones, driver alerts, and traffic behavior based on real-time environmental feedback.
Geomatway links surveillance, vehicle input, and control systems. It detects incidents instantly and triggers automated responses — rerouting traffic, reducing speed, or alerting nearby vehicles in seconds.
Instead of rebuilding roads, Geomatway adds a digital, modular layer that integrates with existing infrastructure. It’s cost-effective, easily deployed in phases, and designed to scale across cities, regions, or national networks.
Geomatway integrates the human dimension of driving into its decision-making engine. It interprets real-time behaviors like overtaking, tailgating, and late merging, while also learning from long-term trends across corridors and time windows. This behavioral intelligence enables more culturally aware, risk-adjusted, and responsive traffic control.
Geomatway is an AI-powered platform that transforms traditional highways into intelligent, adaptive corridors.
By combining road geometry, real-time traffic data, human behavior insights, weather conditions, and vehicle capacity, the system enables dynamic control of speed, safety, and flow across high-speed intercity networks.
Geomatway is a centralized, AI-powered highway management system that transforms traditional intercity roads into intelligent, adaptive corridors. It continuously analyzes data from connected vehicles, environmental conditions, road geometry, and human behavior — enabling real-time decision-making across the entire highway network.
Geomatway has received early-stage recognition and interest from both public and private sector leaders in mobility innovation:
Offered an entrepreneurial opportunity and formally referred the project to relevant smart mobility bodies.
Introduced for potential collaboration on highway modernization initiatives.
Profile shared via MISA with TGA and affiliated transport operators for early-stage review; feedback emphasized interest in proven, ready-to-deploy smart mobility solutions.
Concept reviewed and forwarded to their Enterprise teams for potential integration or partnership.
In early observation trials, expert drivers applying geometry-aware driving techniques demonstrated measurable improvements in travel efficiency, performance stability, and dynamic responsiveness on select intercity corridors.
While not part of a formal pilot, these insights helped validate the system’s potential to improve traffic flow, decision support, and operational safety under real-world conditions — reinforcing the foundational assumptions behind Geomatway’s AI logic and optimization strategy.
Launch UAE feasibility studies, concept design, and stakeholder engagement with platforms like Sandbox, DSO, and Oraseya Capital.
Begin pilot deployment on selected Abu Dhabi corridors and initiate parallel feasibility planning in Saudi Arabia and across the GCC.
Roll out Geomatway in key Saudi highway segments aligned with Vision 2030, while preparing for broader regional scaling.
Expand across GCC countries and export the platform to global early adopters in Europe, Asia, and smart city ecosystems.
