Sunway researchers tell Kuala Lumpur forum that connected cities must decide, not just sense

A Malaysian university research institute has asked the local built environment industry to change how it measures a smart city. Sunway University said its Future Cities Research Institute took part in Cities Climate Connect 2026, the flagship conference of the Malaysia Green Building Council, held in Kuala Lumpur on 12 and 13 August 2026 and attended by policymakers, industry leaders, researchers and practitioners.[1][2]

Representing the institute, its co-director Professor Ir. Dr. Rosdiadee Nordin delivered a keynote at the Future Cities Forum titled Connected Cities: AI and Real-Time Urban Systems, From Urban Sensing to Intelligent City Response. The university said it covered artificial intelligence, digital twins, advanced sensing networks and next-generation wireless communications.[1]

The account is the university's own record, so it reports position rather than measured city outcomes. The question it raises is still useful locally: once the equipment is installed, who reads the data, who decides, and how quickly does the city respond.[1]

The university reported that the keynote closed on a single message: a connected city is not defined by the number of sensors it deploys, but by its ability to learn, decide and respond responsibly to real-world challenges. That is a governance claim rather than a technology claim, and it can be tested without buying anything new.[1]

For a Malaysian council or campus operator the practical version is short. Take one recurring problem, such as flash flood warning or energy waste in a building block, and check whether the data already reaches an officer with authority to act. If it does not, more sensing will not shorten the response time.[1]

A highlight of the session, according to the university, was the showcase of Sunway City as a living laboratory together with the Sunway City Digital Twin. The institute presented these as demonstrations of how data-driven technologies can support smarter urban planning, sustainable infrastructure and evidence-based decision-making.[1]

That matters locally because a privately managed township can trial instrumentation faster than a local authority with a mixed asset base and a tight budget. It also bounds how far the result travels, since a test bed on well-mapped assets does not prove the same approach holds on older public infrastructure with incomplete records. The university added that the institute is developing LoRaWAN sensing networks, net-zero building management systems and AI-enabled urban intelligence platforms, which is a research programme rather than a deployment.[1]

One forum screen photographed in the university's own gallery set out four maturity levels for urban infrastructure. Level one is a digital model, described as a static three-dimensional visualisation with no live data connection. Level two is a digital shadow with one-way live data feeds for monitoring and situational awareness. Level three is a digital twin with a multi-layer model, analytics and testing that supports planning and operations. Level four is an intelligent twin covering prediction, simulation, optimisation and autonomy.[1]

The ladder is a useful procurement filter because level one and level two deliverables are often sold under the digital twin label. Asking which level is being supplied, and what evidence supports the live data connection behind it, separates a visualisation contract from an operating capability that must be funded and staffed for years.[1]