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Digital initiatives are improving the aging Hong Kong Mass Transit Railway to improve its efficiency, availability, and passenger experience.
Hong Kong’s traffic is heavily congested, with an average of 373 vehicles for every kilometer of road. This contributes to about a fifth of the city’s carbon emissions.
The Smart City Blueprint 2.0 champions smart mobility as a way to address these challenges, with emphasis placed on the need for relevant and accurate data. Siemens is helping to develop a Traffic Data Analytics System that uses modeling and prediction to find new solutions to enhance traffic management and efficiency. This innovative, AI-based approach will help Hong Kong to transform its road ecosystem for the benefit of businesses and citizens.
Public transport in Hong Kong is well used, with citizens making around 9 million journeys every weekday. The aging Hong Kong Mass Transit Railway (MTR) is the backbone of the city’s mobility network, and there are many digital initiatives to improve its efficiency, availability, and passenger experience.
Siemens is shaping the digital transformation of MTR railways using data analytics from our Railigent and MindSphere platforms. These powerful tools help to monitor rail asset conditions and facilitate predictive maintenance in diverse areas such as signaling systems, main control systems, and platform screen doors.
Encouraging citizens to walk or cycle is challenging in a city where nights can reach 28°C, and the length of the hot season continues to increase every year.
Nevertheless, the Transport Department’s HKeMobility real-time travel app helps citizens to plan their route on many transportation modes, including quick and convenient walking and cycling routes to help citizens see them as useful alternatives.