The system monitors inspection procedures at RTA-approved testing centres using computer vision and video analytics, flagging violations and providing near-real-time visual evidence that specialists review and approve. Now in full operation and integrated with the CIS and E-Traffic systems, it turns oversight into proactive, data-driven monitoring.

ARIIS automatically inspects Dubai Metro's track infrastructure, using advanced sensors and AI-supported analysis to detect defects in the track and third-rail components. Following a successful proof of concept, the system is now in operational trials on the Metro network.

AutoCheck 360 uses computer vision and the Internet of Things (IoT) to automate vehicle inspection, standardise its criteria and reduce human error. It has cut inspection time from 17 minutes to 7, improving the customer journey and road safety, and is one of the first fully integrated solutions of its kind in the region.

The project supports the delivery sector's shift to electric bikes through battery-swapping station infrastructure that helps cut emissions and improve operational efficiency. The proof of concept was carried out with Terra, ahead of implementation and scale-up.

A rail inspection and maintenance vehicle based on passive magnetic levitation, equipped with AI-powered inspection systems and a wayside sensor network for comprehensive monitoring of rail infrastructure. Following a successful proof of concept, a fully operational vehicle is planned, with AI image analysis, vibration monitoring and real-time data transmission.

The system monitors rail turnouts and crossings with sensors that continuously measure wheel-rail interaction, assessing wear, detecting cracks and measuring acceleration in real time. Data is processed through edge computing, enabling early detection of deterioration and supporting predictive maintenance. Implementation is under way.

The system measures passenger numbers in stations and trains in real time through video analytics, presenting them as figures and heat maps, with congestion alerts and footfall predictions. The project is complete, having been tested at Business Bay station, and includes train loading analysis and estimation.

The project builds an automated system for compiling train timetables, using optimisation algorithms and AI based on passenger flow and historical patterns to reduce overcrowding and improve punctuality and energy efficiency. It has been completed, delivering an optimised Dubai Metro timetable.

The design, fabrication, and validation of a piezoelectric system that converts wheel-rail vibration into stable DC power for IoT sensor networks along Dubai Metro corridors. It replaces chemical batteries with maintenance-free, desert-resilient power (IP67-rated, PZT kept below 75°C).

This research focuses on the development of a photoluminescent/bioluminescent road coating that absorbs solar energy by day and glows for 8–10 hours at night, without electricity. Combines strontium aluminate pigments with UV-resistant polymer coatings, engineered for Dubai's heat, UV, and sand-abrasion conditions.

This research focuses on developing an integrated decision-support and evaluation framework for high-power quasi-dynamic wireless charging systems in electric bus networks. Unlike conventional plug-in charging or fully dynamic charging approaches, the proposed system enables buses to recharge wirelessly during short dwell times at bus stops while passengers board and alight.

A hybrid Photovoltaic-Thermal (PV-T) and cooling pavement system that reduces pavement surface temperature (targeting 65°C+ summer highs) while generating renewable power. Four design layouts (baseline PV-T, blue coating, permeable pavement, elevated solar shading) will be simulated in ANSYS, ranked via multi-criteria analysis, and the top option validated through a lab-scale prototype and a field pilot, feeding a real-time IoT dashboard. Targets: 30% surface temperature reduction and 150–200 W/m² electrical output.

A user-controllable AI traffic management system using GenAI, semantic retrieval, and Retrieval-Augmented Generation (RAG) to help RTA identify matching historical congestion scenarios and get recommended control strategies and journey-time predictions. Built on a novel interpretable, low-dimensional embedding of multi-modal traffic data (structured, visual, and spatial-temporal), with a natural-language GUI and built-in bias detection.

A 12-month study mapping pedestrian shade and connectivity within 400/800/1200m walking catchments of three representative Metro stations: Union, Business Bay, and Jebel Ali. Combines satellite imagery, field thermal measurements, and Urban Network Analysis (route directness, accessibility, betweenness) to pinpoint "hot corridors" where high pedestrian demand overlaps with poor shade. Delivers station-specific shade-gap maps, prioritized intervention recommendations, and a repeatable GIS/Python workflow RTA can apply citywide.

A controlled outdoor mock-up (~15 m² pedestrian pathway) testing a solar-cooling, carbon-reducing MgO paver against a conventional OPC control, targeting a 2–3°C surface-temperature reduction plus quantifiable CO₂ uptake. The fiber-reinforced, carbonated paver batch is produced with an industrial precast partner, installed, and monitored across four phases: concept & design, development, testing & validation, and closure & reporting.

An advanced vertical-axis wind turbine (VAWT) system developed to address the limitations of conventional turbines in urban and low/variable-wind environments. The system starts generating power at lower wind speeds than traditional turbines, making it suited to unstable airflow zones such as roads, Metro corridors, and rail tracks.

An analysis about the efficiency and accessibility of Dubai’s urban food delivery network. Evaluate connectivity between residential areas and food preparation outlets using multimodal transport analysis. Identify spatial and morphological factors affecting delivery performance and accessibility. Assess sustainability indicators such as travel distance, time, route efficiency, and emissions