30/04/2026

LYFE THURSDAY | APR 30, 2026

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Malaysian Paper

@thesundaily @t

Ű BY AMEEN HAZIZI

A RTIFICIAL intelligence (AI) is no longer separate from daily life. It is built into how homes function, often in ways that feel gradual rather than dramatic. What began as simple automation has shifted into systems that learn habits, adjust settings and respond with minimal input. The modern home is becoming less about control and more about adaptation. From automation to intelligent living Basic smart homes once relied on timers and manual triggers. That model is fading. Research from St Wilfred’s College of Computer Sciences on machine learning in home automation shows how systems now learn directly from behaviour. By analysing data from sensors and devices, AI identifies routines and begins to replicate them. Lights switch on when someone typically arrives home. Cooling systems adjust before sleep. The change is subtle, but it reshapes how a home feels to live in. Voice, natural interaction One of the clearest entry points for users is voice control. The same study highlights how natural language processing enables people to interact with devices through speech instead of apps. Over time, these systems adapt to how users speak and what they typically ask for, making interaction feel less rigid and more intuitive. Automation, personalisation Much of what defines a smart home comes down to personalisation. Research from Dean & Francis on smart home adoption and user behaviour shows how AI builds profiles from daily habits. Patterns such as when lights are dimmed, how often appliances are used or preferred temperature ranges are turned into automated responses. Instead of reacting to commands, the home begins to anticipate them. The effect is not dramatic, but it is consistent, making the space feel more aligned with its occupant.

Smart home devices are projected to exceed 1 billion units globally within the next few years.

Smart homes, smarter living o AI integration in modern homes strengthens personalisation, security

individual devices but by how they work together. The De Montfort research also highlights how connected systems share data and respond collectively. Temperature, lighting and security are no longer isolated functions. They operate as part of a unified system, coordinated through AI. This integration is what turns a collection of devices into something more cohesive. Challenges, limitations Despite its advantages, adoption remains uneven. The Dean & Francis study on consumer perception points to recurring concerns. Privacy remains a major issue, particularly as systems collect and process large amounts of personal data. Compatibility is another barrier, with devices from different brands not always working well together. Cost also plays a role, limiting access to more advanced systems. For many households, smart technology still begins and ends with basic devices. Future of AI-powered homes Looking ahead, the focus is on reducing the need for interaction altogether. Across these studies, the direction points towards ambient intelligence, where homes anticipate needs based on behaviour and context, adjusting settings without direct input. AI is not transforming homes through a single breakthrough. It is doing so through small, continuous adjustments that build over time. Each system, whether focused on comfort, efficiency or safety, contributes to a larger shift. The home becomes less of a tool to manage and more of an environment that adapts, responding to how people live rather than waiting to be told what to do.

Healthcare, assisted living In some cases, AI serves a more critical role. The same St Wilfred’s study also points to healthcare monitoring, where smart homes track movement patterns and detect irregular behaviour. A fall, prolonged inactivity or sudden changes in routine can trigger alerts. This is particularly relevant for elderly individuals or those living alone, where early detection can make a significant difference. Interconnected smart ecosystems A smart home is not defined by

Security, monitoring Home security has also moved beyond passive surveillance. Research from Hindusthan College of Engineering and Technology on AI-based home security shows how systems now interpret what they capture rather than simply recording it. Cameras can distinguish between familiar faces and unknown visitors. Sensors identify unusual activity instead of triggering constant alerts. The focus shifts from recording everything to recognising what matters, making systems more precise and less intrusive.

Energy efficiency, optimisation Some of the most practical benefits appear in energy use. Research from De Montfort University and its research partners on AI-driven energy management shows how systems track consumption and adjust in real time. Heating and cooling respond to occupancy rather than running constantly. Lighting adapts to natural daylight. These adjustments happen quietly, but they reduce waste and cost over time. It is one of the clearest examples of AI delivering measurable impact in the home.

AI in homes contributes to broader smart city infrastructure through data integration.

AI assistants are increasingly being integrated into appliances, not just standalone devices. – ALL PICS FROM 123RF