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Revolutionising Building Safety with Predictive Maintenance Powered by AI
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July 12, 2024 Bylines
Predictive Maintenance

Teoh Tze Ping, Managing Director, KONE Malaysia & Brunei

By Teoh Tze Ping, Managing Director, KONE Malaysia & Brunei

 

Think about Malaysia’s rapid urbanisation and the complex modern structures rising across the country. The need to revolutionise building safety has never been more urgent.

The intersection of technological advancement and engineering innovation in this transformative era offers unprecedented opportunities to elevate safety standards across our built environment. Among these advancements, Artificial Intelligence (AI) stands out as a key technology, capable of driving predictive maintenance, real-time monitoring, and advanced automation to safeguard buildings and their occupants.

In a scenario where all elevators and escalators in our cities abruptly cease to function, how would we ensure the smooth movement of people? What repercussions would this pose for metro stations, airports, hospitals, and office buildings in our densely populated urban areas?

Across the globe, AI technologies have been harnessed to augment structural health monitoring in diverse infrastructures like buildings, bridges, and roads. In Malaysia, the adoption of AI-driven technologies in buildings aligns with the nation’s ambitions to foster smart cities. Kuala Lumpur, in particular, where smart buildings equipped with interconnected technologies are becoming increasingly prevalent, according to Kuala Lumpur Mayor Datuk Seri Kamarulzaman Mat Salleh

Smart sensors and IoT devices powered by AI can continuously monitor structural health, detect anomalies, and predict potential failures before they occur. These technologies enable proactive maintenance to improve safety and ensure the longevity of buildings. 

Integrating AI into Buildings

Elevators and escalators, critical components of modern high-rise structures, benefit significantly from AI-driven enhancements. By leveraging AI algorithms, these systems can anticipate traffic patterns, minimise waiting times, and alleviate congestion—all while enhancing the overall user experience and operational efficiency.

In high-rise buildings, AI integration ensures smooth and seamless people flow, minimising wait times, reducing congestion and maximising efficiency. This is to ensure effective people flow management within complex-built environments, which is essential for maintaining optimal operations and enhancing the overall user experience. At KONE, we help customers connect elevators, escalators, and automatic building doors to our cloud-based service and use AI-enabled analytics to take people flow to a whole new level.

Predictive Maintenance for Enhanced Safety & Building Value

One key opportunity with AI is the predictive maintenance of elevators. An AI-based predictive maintenance approach allows building owners to continuously analyse elevator performance and risks, reducing breakdowns and enhancing accessibility. 

This proactive approach ensures higher safety standards and minimises potential hazards, making buildings safer for all occupants. For instance, KONE 24/7 Connected Services equips all elevators with sensors and state-of-the-art technology, providing extensive data on performance, usage patterns, and potential issues. Depending on the severity of the problem, this system informs building owners by identifying maintenance needs and alerting technicians or customer support.

Through 24/7 monitoring, building owners receive immediate notifications of problems and can plan future maintenance effectively. This continuous flow of information integrating real-time and historical data ensures that issues are addressed promptly, maintains the smooth operation of elevators, and contributes to overall building efficiency.  This results in enhanced safety, complete transparency, and peace of mind for consumers.

From a business perspective, AI-powered predictive maintenance offers substantial returns on investment by mitigating risks associated with equipment breakdowns and operational disruptions. According to Deloitte AI Institute Report, avoiding breakdowns can prolong the lifespan of machines and assets, enabling the business to derive greater value from its current investments. AI-based predictive maintenance can prolong the lifetime of equipment by proactively identifying up to 70% of faults, resulting in 44% fewer callouts and reducing unplanned equipment disruption for passengers. 

Transitioning to AI & Predictive Maintenance 

Transitioning from reactive to predictive maintenance in buildings presents an opportunity for growth. However, many building management teams may encounter challenges due to a need for specialised knowledge in effectively managing and interpreting data from advanced predictive maintenance technologies.

To bridge this gap, partnering with specialised service providers who can offer the expertise required can be a viable solution. Companies like KONE are at the forefront of this transformation, offering AI-powered vertical transportation solutions designed to optimise efficiency and elevate user experiences to new heights. 

The data and information provided directly integrate serviced equipment into building management systems. Not to mention, KONE also works with reputable partners to scale up their digital services for smart buildings. By leveraging global cloud solutions like IoT, analytics, and cybersecurity through these partnerships, the company strengthens its defences and ensures the security of its smart building technologies.

As Malaysia continues its journey towards urbanisation and sustainable development, the integration of AI in building safety and maintenance will play an increasingly pivotal role. 

AI technologies enable streamlined operations, reduced energy consumption, and enhanced passenger experiences within elevators and escalators. By adopting these innovative technologies, building owners can future-proof their properties, ensuring they remain attractive and efficient in meeting the evolving needs of tenants and residents alike.

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