A DATA­-DRIVEN APPROACH FOR BUILDINGS TO ACHIEVE GREEN BUILDING CERTIFICATIONS

Abstract

The launch of Green Mark (GM) Certification by the Building and Construction Authority (BCA) has made an impact in the building landscape in Singapore by promoting the adoption of numerous Green Building Technologies. This has expedited the adoption of green building technologies and design practices as well as the number of environmentally-­friendly buildings in Singapore. However, in 2020, the Singapore Government has set an ambitious goal of greening 80% of buildings by Gross Floor Area by 2030.

This highlights the critical need for buildings to be green before 2030 and what can be done to make the planning process easier and faster for new and existing building owners. Thus, this study aims to develop a data­driven tool, leveraging on existing Green Mark data of Singapore buildings to mitigate the challenges faced in the quest to attain this certification. Data was web scraped from the BCA website and pre­processed. A list of keywords and phrases were created from the Green Mark assessment criteria after which all the green features of each certified building were identified and labelled according to their corresponding Green Mark sections.

The insights derived will provide a better understanding to Singapore’s building landscape. Access to the tool will allow users to narrow down the uncertainty when it comes to deciding the myriad range of building designs available in the market. Data-­driven decision-­making reinforces the users’ choices with substantial evidence provided by successful use cases in Singapore.