Escalators are indispensable parts of daily life, commonly found in shopping malls, train stations, office buildings, etc.
However, some operational problems can arise, posing safety risks to passengers. Human problems such as foreign objects falling into the escalator tunnel, heavy baggage impeding passage or malfunctioning parts can lead to abrupt stops of escalators, resulting in dangerous consequences.
To reduce the risks of such events, the intelligent digital escalator monitoring system (i-DEMS) was developed. This system monitors and automatically collects real-time data on escalator operations. By leveraging cloud computing technology, it analyses the data to identify potential anomalies and predict potential failures. This system promptly notifies the person in charge and maintenance staff through machine learning and applications, which enables more efficient predictive maintenance work.
Problem Addressed | The objective of i-DEMS is to enhance the safety and reliability of escalators, minimise the likelihood of common incidents and reduce the number of passenger injuries. This is achieved through the adoption of predictive maintenance, which proactively identifies early faults and schedules maintenance works in advance. |
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Innovation | iDEMS, is an intelligent escalator sensing system that comprises optical fiber sensing technologies, high accuracy electronic sensors, artificial intelligence and machine learning. Its purpose is to provide comprehensive and real-time monitoring of escalators, aiming to minimise the likelihood of common escalator incidents, including defects of escalator step rollers, handrail synchronization issues, jamming of foreign objects at escalator combs, and main drive failure due to overheated motors or abnormal vibration. |
Key Benefits |
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Patent and Award |
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Project Reference | Mong Kok Langham Place, Tuen Mun Siu Lun Government Complex, Central Mid-Level, Queensway Government Offices |
Other Reference | https://youtu.be/4vsWPrk4vKg (Video Introduction) |