HDB Singapore partners with local universities to leverage big data and smart technology in planning, designing and building public housing
The agreements include a S$4.7 million collaboration with NTU to develop a Smart Integrated Construction System and a S$6 million MOU with SUTD to embark on a data-driven study of HDB communities.
Above image: Smart Integrated Construction System (Credit: HDB)
The Housing & Development Board (HDB) in Singapore, the agency for all public housing developments in the country, signed two new research and development (R&D) agreements with the Nanyang Technological University, Singapore (NTU) and the Singapore University of Technology and Design (SUTD) today, at the International Housing Forum on sustainable urban development.
An investment of S$10.7 million will leverage the power of Big Data, data analytics and smart technology to boost construction productivity and safety, as well as to develop a new social framework to build stronger communities.
A S$4.7 million collaboration with NTU aims to develop a Smart Integrated Construction System (SICS). This system will harness smart technology, through the use of smart sensors and automation, to transform traditional construction work processes and boost productivity.
Another S$6 million Memorandum of Understanding (MOU) was signed with SUTD to embark on a study called the New Urban Kampung research programme. The study will adopt cutting-edge modelling tools to analyse shifts in socio-demographic factors, and create new housing solutions in line with residents’ evolving needs and aspirations.
The Smart Integrated Construction System project is funded by the Ministry of National Development (MND) Research Fund, while the New Urban Kampung Research Programme is part of the ‘Cities of Tomorrow’ R&D Programme funded by the Land and Liveability National Innovation Challenge (L2NIC).
HDB’s Chief Executive Officer, Dr. Cheong Koon Hean said, “The fast-changing urban landscape brings along with it increasingly complex housing issues and needs. To meet these challenges, HDB wants to advance the “science” behind how we plan, design and build our HDB towns and estates. With behavioural science studies and data analysis, we can better understand our residents’ needs and changing lifestyles and their likely responses to our plans and initiatives. Smart construction solutions will also enable us to build more productively and achieve better quality. The new R&D partnerships will further augment our Roadmap to Better Living in HDB Towns, as we work towards creating homes of the future.”
Smart Integrated Construction System
The SICS aims to facilitate data-sharing and synergise construction processes across industry partners through a central digital platform, powered by a smart tracking system to better manage the logistics of construction inventory, such as precast components for HDB buildings. The key features of the SICS system are:
- HDB Integrated Building Information System (IBIS) – The core of the SICS, this central digital database serves as a collaborative workspace. Using 3-dimensional modelling of HDB projects as a common platform, industry partners in the entire construction supply chain can log in real-time information and progress updates on the project from their dispersed locations. This streamlines information and speeds up data-sharing amongst the different partners, including architects, contractors, pre-casters and construction material suppliers, enabling them to better keep track of budgets and timelines.
- Smart Tracking System – Supporting the IBIS, the smart tracking system will virtually manage the logistics of construction inventory as they move from various suppliers to the construction site. Smart sensors with geo-tagging capabilities will be attached to building components to help contractors manage the flow of construction materials into the work site, and swiftly identify and correct lapses such as wrong deliveries. This will minimise disruptions to the construction process and enable it to progress smoothly.
- Smart Crane System – This will automate the manual hoisting process of building components on site. Through smart sensors embedded in the precast components and a network of sensors placed around the construction site, the Smart Crane System will be able to calculate and determine the quickest and safest hoisting path to mitigate potential collisions and swaying, thereby reducing construction time and improving safety.
Using smart sensors, the Smart Crane will be able to determine the quickest and safest hoisting path of building components on site (Image credit: Nanyang Technological University & Witteveen+Bos) via HDB press release
New Urban Kampung research programme
The New Urban Kampung research programme will combine the fields of behavioural studies, Computational Social Science and Urban Informatics. Divided into 4 parts, the collaboration will culminate in the development of a New Urban Kampung framework to steer future town planning and housing design that will improve the overall quality of life for residents.
The first part seeks to gain deeper insights into the composition of HDB residents beyond traditional demographic statistics such as age, race and income, and uncover emerging lifestyle trends, liveability definition and sentiments towards the community. This will be done through a combination of data from traditional census and surveys, with big data gathered through sensor networks placed around the estate (e.g. human traffic and movement sensors) and social listening. The insights gleaned will guide HDB’s planners and architects in formulating more targeted and customised improvements in HDB towns.
For example, with residents becoming increasingly more digitally-connected, void decks could be equipped with Wi-Fi-enabled workspaces for residents to gather and study, organise workshops, or hold classes. Such initiatives will also encourage residents to make fuller use of communal spaces and take ownership of such spaces.
The second aspect is to identify new quality of life indicators that reflect residents’ needs. As the socio-demographic makeup of HDB towns evolves, traditional quality of life indicators (e.g. healthcare, sanitation, safety etc.) may not adequately reflect the specific needs of HDB residents. Thus, research is needed to derive new quality of life indicators along two dimensions: Material conditions and resources within a neighbourhood (e.g. thermal comfort, access to amenities, urban greenery etc.), and psychosocial factors (e.g. cohesion among residents and sense of belonging). This will help guide future design and planning strategies to boost residents’ well-being.
Another key facet of the study will be to find new ways of incorporating community-centric design into the heartlands, beyond the current provision of communal spaces such as gardens, playgrounds and fitness corners.
Big data from sensors could help fine-tune the design of communal spaces for stronger community interaction. For example, movement trends captured by motion sensors on smart lighting in the estate could help HDB better understand how residents move around and utilise the community spaces in their estate. Residents could then be engaged to co-design those under-utilised spaces.
Secondly, the behavioural studies are expected to provide insights into the common interests of residents and finding new ways of bringing communities together, such as through smart applications and gamification. For example, if the data shows that residents in a particular estate are fond of cycling, customised cycling apps could be introduced to cultivate a cycling community in the estate. Such an app could link together residents who enjoy cycling, and allow them to publish their cycling mileage and make recommendations on scenic or safer cycling routes.
The final objective is to forecast the effects of new HDB living initiatives. There are existing environmental modelling tools, such as the City Application Visual Interface (CAVI), to assess the effectiveness of sustainability-driven initiatives in HDB towns and estates. By integrating urban analytics into the tools, large amounts of social data could be analysed and simulations could be run on new HDB living initiatives to predict residents’ receptiveness before test-bedding them in real-time.