This article first appeared in The Edge Malaysia Weekly on June 15, 2026 – June 21, 2026
Cities may be becoming smarter, but they are not necessarily becoming more environmentally resilient.
Malaysia, like many countries, rapidly adopted the smart city agenda, investing in digital infrastructure, command-and-control systems, artificial intelligence and data-driven urban services. These smart city initiatives drive efficiency, connectivity, competitiveness and better urban living.
Yet, today’s smart city model still emphasises optimisation and operational efficiency. Many within urban smart city planners view environmental resilience as secondary rather than a core governance function.
A truly smart city must do more than digitise services or optimise mobility. It needs institutional capacity to anticipate environmental risks, protect vulnerable groups, and guide decisions with predictive environmental intelligence.
Recent environmental crises, particularly in Greater Kuala Lumpur (GKL), expose a critical gap in the smart city vision. Transboundary haze, flash floods, landslides and extreme heat are now recurring features of urban life in GKL. These are not isolated incidents but systemic environmental hazards that are disrupting the economy, healthcare, public welfare and safety.
Environmental hazards in urban areas are often highly complex, shaped by interconnected physical, chemical, ecological and climatic processes operating across micro- and macro-environmental conditions. These interactions are influenced by factors such as urbanisation patterns, geographical morphology, pollutant emission intensity, land-use change and meteorological dynamics.
GKL exemplifies this complexity. Situated within the Klang Valley and influenced by the surrounding highlands and coastal atmospheric conditions from the Strait of Melaka, the region experiences dynamic interactions among topography, weather systems and pollutant transport.
These conditions can intensify pollution accumulation, alter ecosystem behaviour and complicate environmental risk management. As environmental management becomes more interconnected and difficult to manage through conventional monitoring alone, the need for predictive, data-driven governance becomes increasingly critical. This reveals a key limitation in how smart cities are currently conceived.
It is timely to present “environmental proofing”, a novel concept that integrates predictive environmental intelligence into urban planning and operations. More importantly, environmental proofing redefines what it means for a city to be truly smart by shifting urban governance from reactive management towards anticipatory decision-making. In doing so, it enables cities to better protect and inform residents, and respond to their needs.
Environmental proofing does not eliminate hazards in Malaysia that are caused by natural processes, climate variability or complex meteorological conditions beyond human control. Instead, it enables cities and communities to anticipate risks, respond sooner and make informed decisions before crises escalate. With timely predictive intelligence, governments, businesses and the public can adapt through remote work, school closures, travel restrictions, health measures or targeted emergency responses.
Data analytics lies at the core of environmental proofing. Environmental data should do more than report conditions; it must evolve into a decision infrastructure that supports anticipatory governance. Advanced analytics can help governments identify patterns, anticipate risks and intervene earlier before disruptions escalate into crises.
Yet, much of today’s smart city management remains focused on operational command centres for traffic, surveillance and public services, often without integrated environmental proofing capabilities. As climate-related disruptions become increasingly complex, smart cities must evolve beyond reactive monitoring towards predictive systems that can forecast risks, inform the public earlier and support adaptive decision-making.
A practical example is the use of artificial intelligence and machine learning to forecast environmental hazards in GKL. These systems combine observations, satellite data, weather patterns and spatial analytics. They can predict environmental risks days ahead. Such technologies could support anticipatory governance across many other environmental risks.
Environmental proofing can be a key governance layer as cities use digital twins. While digital twins are often seen as technical tools, their real value is in turning data and analytics into action and public resilience.
In the end, city governance depends not on how much data is collected but on turning data into foresight. As climate uncertainty grows, resilience cannot remain just a reactive function. It must be part of each city’s core operations. The next generation of smart cities must be environmentally proofed, able to adapt, anticipate and prepare before damage occurs.
Ultimately, resilience is measured not by the speed of response but by a city’s foresight in preparing its people, informing decisions and anticipating crises before they unfold.
In an era of climate uncertainty, how smart is a city without smart environmental governance?
Dr Jayaprakash Murulitharan is with the Ministry of Housing and Local Government and a University of Cambridge-trained atmospheric scientist, who recently introduced the concept of environmental proofing at the “Perspectives on the societal impact of digital twins conference” in Cambridge, United Kingdom.
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