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07 Apr 2026
6 Min Read
Dr Phang Swee King (Academic Contributor), Nellie Chan (Editor)
Across Malaysia, roads are more than infrastructure—they are lifelines. From daily commutes through dense urban traffic to long interstate journeys during festive seasons, movement drives how we live, work, and connect. But when road surfaces deteriorate over time, the consequences can be costly and, at times, deadly. As complaints mount and safety concerns compound, the challenge is no longer simply repairing roads but anticipating hazards before they cause accidents.
At Taylor’s University, Dr Phang Swee King is developing the Intelligent Road Safety Monitoring System (IRSMS). Rather than relying solely on ground-level inspections, he introduces a smarter solution for monitoring road conditions, integrating drone technology with artificial intelligence to detect surface defects from above. It optimises how road risks are recognised and responded to, supporting safer journeys for millions daily.
Dr Phang is an associate professor at the School of Engineering, where he specialises in automation and robotics with a focus on drone systems. His project, IRSMS, was awarded a gold medal at the 36th International Invention, Innovation, Technology Competition & Exhibition (ITEX 2025).
While many municipalities still perform physical inspections that place teams in traffic-heavy or hazardous environments, IRSMS offers a safer, more data-driven alternative, helping authorities monitor roads with greater speed, accuracy, and transparency.
We spoke with him to explore how the project evolved, the decisions behind developing an intelligent detection system, and what it could mean for the future of smart infrastructure.
Q: What is the IRSMS, and how does it work?
A: The IRSMS is a smart solution designed to detect road surface defects, such as potholes and cracks. It uses drones to capture aerial images and artificial intelligence (AI) to analyse them, displaying detected defects on a digital map. This provides a clear, real-time overview of road conditions and automates what would otherwise be a slow, manual process.
Q: What inspired the idea?
A: The idea for IRSMS was inspired by growing public concern about road safety, particularly in response to rising reports of pothole-related accidents. Alongside this, policy shifts in transport and road agencies facilitating the adoption of smart technologies solidified the team’s decision to develop a solution that could address this real-world pain point.
Q: What research gaps do IRSMS seek to fill?
A: Despite growing public concern, road safety remains a persistent issue due to deteriorating road infrastructure, high traffic volumes, and climate- and weather-related effects. Traditional inspection methods are manual, labour- and time-intensive, and prone to human error. There’s also a lack of integrated, data-driven management systems to help local authorities prioritise road repairs efficiently. IRSMS was developed to fill these gaps by introducing a more automated, accurate approach to monitoring road conditions.
Q: Did the project evolve during development?
A: Yes—initially, we aimed to detect a broad range of road surface defects. However, we didn’t have sufficient training data to effectively model all defect types. As a result, we refined the scope to focus on potholes and cracks, which allowed us to develop a robust system that still makes a significant impact.
Q: How did you overcome the lack of sufficient training data?
A: To overcome this, we drew on datasets from other countries with road conditions similar to Malaysia’s, since no local dataset is available, and collected additional data from roads around Taylor’s University. Together, these sources were sufficient to train the system successfully.
Q: What are common misconceptions about this innovation?
A: Some hold the misconception that AI detection of road surface defects is inaccurate, given its fine-grained nature. In fact, manual inspections can suffer from fatigue, error, and inconsistencies, reducing reliability. AI allows our system to scan thousands of images systematically, improving precision while keeping inspection teams safe by eliminating the need to be physically on high-traffic or hazardous roads.
Q: Who benefits from IRSMS?
A: IRSMS benefits several key stakeholders. Road inspection and maintenance teams, together with local authorities as its direct users, can monitor road conditions more efficiently, prioritise repairs, and deploy resources more strategically. Motorists and the wider public benefit indirectly through safer road conditions, which can reduce accidents and the risk of vehicle damage caused by potholes and cracks. At a broader level, government agencies can integrate IRSMS data into smart city and infrastructure initiatives, supporting more data-driven urban planning.
Q: How could IRSMS influence the future of road condition monitoring?
A: By collecting consistent, location-based data over time, IRSMS could influence how roads are monitored and managed. This data enables predictive maintenance rather than reactive repairs, helping local authorities anticipate deterioration before it leads to defects. Beyond potholes and cracks, the system could be adapted to detect other types of defects, paving the way for broader applications.
Q: What is needed for IRSMS to be adopted at scale?
A: For IRSMS to be adopted at scale, two conditions are critical: regulatory approval and stakeholder adoption. Approval from aviation authorities such as the Civil Aviation Authority of Malaysia (CAAM) is required to ensure drone operations comply with national aviation and airspace regulations, particularly for automated flights over public roads. Once regulatory clearance is secured, adoption by local and national stakeholders—including municipal councils, the road transport ministry, and major infrastructure developers—is essential to embed IRSMS into existing road inspection and maintenance workflows. Together, these conditions facilitate the scaling of IRSMS beyond pilot projects into a nationwide, data‑driven tool for proactive road safety and surface management.
Q: In what ways has your academic background shaped your approach?
A: My academic background shaped my approach to this project by fostering practical problem-solving that extends beyond theoretical understanding—the same mindset I instill in my students—which guided our work on IRSMS, informing decisions about planning, testing, and refining to ensure that the solution solves real-world problems.
Q: What was the most important lesson you learned from this project?
A: The most important lesson came from stepping out of the lab and into the field. In the lab, conditions are idealised, but in the field, they’re often less so—like when we discovered there were no local datasets available, which we then had to collect ourselves. This taught me the need to be adaptable and to tackle challenges as they arise in real-world system development.
IRSMS offers a glimpse into the future of smart infrastructure—transforming roads through automated monitoring and management. By strategically combining drones, AI, and on-the-ground data, the system not only detects surface defects but also enables faster, safer interventions.
Next, the project looks to advance by collaborating with a local drone technology provider to co‑develop a purpose‑built platform tailored to IRSMS requirements. A custom drone could offer longer flight endurance, automated mission capabilities, and high‑resolution imaging optimised for detecting surface defects, further enhancing system efficiency and supporting nationwide deployment.
Beyond the technology itself, Dr Phang’s work shows that impactful innovation often comes not from creating entirely new tools, but from integrating current ones thoughtfully to solve problems at their source. Sometimes, it all begins with seeing roads differently—from above, with intelligence guiding the way.
Master of Science in Engineering or Doctor of Philosophy in Engineering programmes.
