JLD will be a model district to demonstrate how technology can enable a liveable and sustainable urban environment.


This will be driven by a combination of district-level infrastructure, data-driven decision-making platforms and forward-looking policies.

For example, residents and businesses will enjoy reduced energy use with district cooling systems and the highest Green Mark standard for buildings. The use of pneumatic waste collection systems, common services tunnels and consolidated logistics mean that urban services will be cleaner, less disruptive and use fewer workers.

Real-time data exchange will also enable facility managers to diagnose and fix problems timely in their buildings, and service providers to understand residents’ needs to arrange transport and social services and serve them better.

 

 

 

 

 

SMART PLANNING

With advances in sensors and computing power, urban planners today can generate, combine and process vast amounts of data about the city. Using new digital tools, such data can be analysed and visualised in various ways, uncovering new possibilities to guide better decisions for our city.

 

 

Simulation Models


New technology allows planners to analyse and visualise the impact of developments on the microclimate and thermal comfort of outdoor spaces.
This allows planners to introduce measures, such as increasing greenery, adjusting building massing and orientation, and safeguarding wind corridors, to make the district cooler and more comfortable.
 

 

 

Big Data

 

Data analytics enables planners to better plan, design and manage the district. Examples include refining public transport services based on travel pattern data from EZ-Link and sensors; and planning for social amenities such as child-care centres and polyclinics based on anticipated demand and demographic changes in the district.

 

 

Underground Master Plan

 

A three-dimensional digital underground space planning platform helps planners organise the use of underground space more efficiently. Conflicts can be identified early before construction begins.