Elevating Tomorrow: Leading the Way in AI, Sustainability, and Safety Innovations for Vertical Mobility
In conversation with Charulatha, Correspondent, Silicon- india Magazine. Mr Gossian shared his views about the elevators incorporating green technologies, the role AI plays in optimizing energy consumption and the future of elevator maintenance evolving with the increasing reliance on AI-driven predictive analytics and monitoring.
In smart buildings, elevators are integrated with interconnected systems such as IoT devices, building management systems, and security networks
What specific challenges has the elevator industry faced in adopting AI and ML technologies, and how have these challenges been overcome?
The elevator industry has encountered challenges in adopting AI and ML due to the complexity of integrating these technologies into traditional systems. Challenges include the cost and logistics of retrofitting elevators with extensive sensor networks for real-time data collection. Safety concerns have also been prominent, requiring rigorous testing to ensure AI-driven systems meet stringent standards and respond effectively to emergencies.
Resistance to change within the conservative sector has added to the hurdles. Convincing stakeholders to embrace AI necessitated education about its benefits, such as improved efficiency, predictive maintenance, and energy savings.
How do you see the integration of predictive maintenance through AI affecting the overall reliability of elevator systems in India?
The integration of predictive maintenance through AI in India's elevator systems is poised to significantly enhance overall reliability. By leveraging AI algorithms to analyze data from sensors and historical performance, predictive maintenance can identify potential issues before they lead to breakdowns. This proactive approach allows for timely interventions, reducing unplanned downtime and minimizing disruptions in elevator services. In a country like India, where elevators play a crucial role in urban infrastructure, enhancing reliability translates to improved accessibility and efficiency in residential and commercial spaces. Predictive main- tenance not only extends the lifespan of elevator components but also contributes to cost savings by preventing major repairs and optimizing maintenance schedules. Ultimately, the adoption of AI-driven predictive maintenance is a strategic step towards ensuring a more dependable and efficient elevator ecosystem in India.
With the increasing emphasis on sustainability, how are elevators incorporating green technologies, and what role does AI play in optimizing energy consumption?
Elevators are embracing green technologies, with AI playing a crucial role in optimizing energy use. Regenerative drives convert excess descent energy into electricity, reducing overall consumption. LED lighting, lightweight materials, and energy recovery systems enhance eco-friendliness. AI dynamically adjusts elevator operations by analyzing real-time data, predicting usage patterns, and optimizing movements based on factors like occupancy and traffic. This integration minimizes environmental impact, aligning with global sustainability initiatives for more energy-efficient and environmentally responsible elevator systems.
AI and ML algorithms can analyze data related to energy consumption patterns in buildings, allowing KONE to develop more energy-efficient solutions. This could involve optimizing the use of elevators and escalators based on real-time energy demand and cost considerations.
"The future of elevator maintenance is poised for a transformative shift with the increasing reliance on AI-driven predictive analytics and monitoring"
How do elevators play a role in the broader landscape of intelligent infrastructure as industry increasingly adopts smart building technologies, and what challenges arise in the process of this integration?
Elevators play a crucial role in the broader landscape of intelligent infrastructure as industry embraces smart building technologies. In smart buildings, elevators are integrated with interconnected systems such as IoT devices, building management systems, and security networks. This integration allows elevators to communicate and collaborate with other building components, optimizing overall efficiency and user experience. For example, elevators can align their operations with occupancy patterns, contribute to energy management, and enhance security through access control systems.
However, challenges arise in the process of this integration, including interoperability issues among diverse smart technologies, ensuring data security, and addressing the complexity of retrofitting existing systems. Coordination among various stakeholders, including elevator manufacturers, building developers, and technology providers, is essential to overcome these challenges and create a seamless and intelligent infrastructure that maximizes the benefits of smart building technologies.
In the context of contactless technology, what specific features or innovations are being introduced to enhance user safety and hygiene in elevators?
Elevator manufacturers are meeting the demand for enhanced user safety and hygiene by introducing contactless features. Touchless controls, such as smartphone apps, gestures, and proximity sensors, are increasingly common, enabling users to select floors without physical button contact. Additionally, elevators are integrating antimicrobial materials to address hygiene concerns, creating surfaces that resist the spread of germs.
How do you foresee the future of elevator maintenance evolving with the increasing reliance on AI-driven predictive analytics and monitoring?
The future of elevator maintenance is poised for a transformative shift with the increasing reliance on AI-driven predictive analytics and monitoring. AI enables elevators to move from traditional, schedule-based maintenance to a more dynamic and proactive approach. Predictive analytics, powered by AI algorithms, continuously assess elevator performance in real-time, analyzing data from sensors and historical records to anticipate potential issues.
This shift to predictive maintenance offers several advantages. Firstly, it reduces downtime by addressing problems before they become critical, enhancing elevator reliability and performance. Secondly, it optimizes maintenance schedules, minimizing unnecessary interventions and extending the lifespan of components. Moreover, AI-driven monitoring allows for a more comprehensive understanding of elevator health, enabling technicians to focus on specific issues rather than conducting routine checks.
As AI continues to evolve, machine learning algorithms will become more sophisticated in predicting and preventing elevator malfunctions. The future holds a landscape where elevators are not just transportation devices but smart, self-monitoring systems that can adapt and optimize their maintenance needs in real-time. This evolution will result in cost savings, improved efficiency, and a more seamless, reliable vertical transportation experience.