Selangor Journal
Menteri Besar Dato’ Seri Amirudin Shari (centre) during the launch of the Smart Road Asset Management System at the Selangor State Secretariat Building, Shah Alam, on March 16, 2022. Also present are state executive councillor for infrastructure Izham Hashim (left) and Selangor deputy state secretary (management) Mohamad Zahri Samingon, who is also chairman of Selgem Sdn Bhd. — Picture by REMY ARIFIN/SELANGORKINI

Smart system for a Smart City

By Alang Bendahara

DAMAGED roads and street furniture like traffic lights, benches and signage are prevalent and do not usually get repaired quickly.

Selangor has recognised that in order to become a liveable Smart State in Asean by 2025, it needs to adopt more innovative ways to manage its roads and maintain its image as a city that uses technology to speed up such repairs.

On March 16, it launched the Smart Road Asset Management System, which provides more efficient solutions for monitoring, identifying and repairing damaged roads and their assets.

Developed by Selgem Sdn Bhd (Selgem) together with the state’s road maintenance concessionaire, Infrasel Sdn Bhd, the new road maintenance system also supports the state’s existing Intelligent Response System (IRS) application for reporting potholes, which was formulated by Smart Selangor Delivery Unit (SSDU).

From August 2017 to September 2020, the IRS received 113,588 pothole reports via the Waze navigation system, where 108,022 were verified.

Selgem principal officer Mohammad Hafizuddin Zakaraya speaks to Selangor Journal in an e-mail interview to unveil more about what the new system has to offer, both to the public and to its stakeholders.

AI and automation

During the launch of the system, Menteri Besar Dato’ Seri Amirudin Shari said that the use of the system by the local authorities to standardise its assets and road maintenance is expected to be implemented by June.

According to Mohammad Hafizuddin, the system caters to two primary users: government agencies or road managers and the public.

He said its main goal is to help road managers make better-informed decisions by reducing human intervention with the help of automation.

“With this system, road inspectors would no longer need to park their vehicle, manually key in the data and take photos of potholes as the Artificial Intelligence-enabled dashcam would automatically detect the potholes and take photographs of them to generate a report.

“As for the public, if they were to post their complaints on any road-related damage or defects on social media platforms like Twitter or Facebook, the system would be able to locate the complaint, capture it and sort it according to type, severity and location,” he said.

Mohammad Hafizuddin said, as a result, the system is well-suited as a comprehensive solution for the entire road ecosystem as it is paperless, fully automated, and excellent as a tool for the public to make reports as well as for contractor administration.

Saves money

The locally-developed system was created to be versatile and for use on all types of roads in both urban and rural areas, said Mohammad Hafizuddin.

He said for it to work, it only needs systems that are already in the market, such as the Light Detection and Ranging (LiDAR) system, a 360-degree camera for scanning and an AI-assisted dashcam to detect defects.

“So the cost is very minimal. In the long run, it will give the state a big impact and savings by reducing the man-hours on the roads, time in preparing the reports, and time in making decisions. It would also increase productivity,” he said.


According to Mohammad Hafizuddin, there are big plans ahead for the system as there is the prospect of it being used outside of Selangor.

He said his company had been approached by a few parties with requests to expand its usage.

“We are also confident that it would be future-proof as the AI function keeps on learning to calculate the severity of the damage, the quantity of materials required for repairs, and other conditions,” he said.

On top of that, he said the system’s AI has been spending more than a year learning about the various road conditions that it would encounter in the course of its work in the future.

“So we are already one year ahead of others, and the learning never stops,” he said, adding that more than 500 terabytes of data has already been captured and stored in cloud servers.

“In fact, in the future, the system can assist autonomous vehicles based on the massive data analytics it has collected on the various road conditions in Selangor.”


This article first appeared in the Selangor Journal monthly April edition, published on March 28, 2022

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