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Weekend Property

Transforming Hong Kong into a smart city

PwC in its Smart City Blueprint for Hong Kong report makes many suggestions for implementing smart city projects across the city

PUBLISHED : Friday, 11 August, 2017, 3:04pm
UPDATED : Friday, 11 August, 2017, 3:04pm

Albert Wong, a consulting director for PwC Hong Kong, talks about what characterises a smart city and how the Hong Kong government can collaborate with the public and private sectors to transform Hong Kong into a smart city.

What is the purpose of the Smart City Blueprint for Hong Kong report that the government asked PwC to prepare?

We were mandated by the government to offer independent views on possible ways to develop Hong Kong into a smart city by looking at international practices, identifying local challenges, and coming up with solutions for formulating a blueprint. The government will discuss internally the ideas and initiatives suggested, including those for governance arrangements, the digital framework, development plans, legal framework, public-private partnerships, and pilot projects.

What is the ‘smart city’ concept? How will it work in Hong Kong?

From our perspective, a smart city is characterised by its smart living, smart government, smart economy, smart environment, smart mobility, and smart people. Smart living focuses on improving an individual’s ability to interact with electronic services, and on improving well-being and health. Smart government serves its stakeholders through the deployment of supporting infrastructures that collate, analyse and present city data in ways that support stakeholders. Smart economy strengthens the city’s economy by improving the business climate. A smart environment changes how government manages the built and natural environments. Smart mobility aims to enhance people’s mobility through infrastructure investments. Smart people aims to transform the way people access public and private sector services and facilitates lifelong learning.

What key suggestions and recommendations are in the report for the government to consider?

The recommendations made are aimed at helping to achieve the goals outlined above. For example, we propose developing a road map for intelligent transport systems, with sensors at public transport interchanges to help with smart mobility. To achieve smart living and a smart environment, we propose offering more digital payment options and promoting green and intelligent buildings. On smart government, we propose enabling more efficient building life cycles through the use of building information modelling and setting up a 3D simulated platform for interactive visualisation and analysis of city data. To assess the feasibility of our recommendations, we propose experimenting with pilot projects such as smart public transport interchanges, smart parking, a smart region living lab, and so on. We believe Kowloon East, especially the Kai Tak Development Area, is a good testing ground, where a number of smart city projects are underway or have been proposed, such as a smart water meter system and electric vehicle charging facilities and real-time parking information.

What are the challenges in transforming Hong Kong into a smart city? Do we have the necessary infrastructure, talent and regulatory environment in place?

A key challenge is that private businesses may be reluctant to contribute their data to the Big Data environment. For example, most privately operated car park operators have not responded positively to the Transport Department’s call to share their real-time parking availability data. Other issues will also affect the adoption of certain technologies or the implementation of certain policies. Having said that, in Hong Kong we do have the necessary infrastructure, a good education system, world-class tertiary institutions, and sufficient legal protection for intellectual property (IP) and privacy. The government can further promote innovation by making IP rules more transparent and fair for determining whether the data can be redistributed or combined with other data.