Deque by Scufftech

render of deque

Inspiration

The wake of the Covid-19 pandemic saw a surge in e-commerce. This caused a significant increase in home deliveries which raises environmental concerns (carbon emissions). A solution is desperately needed to curb carbon emissions for deliveries.

What it does

A system that utilizes the local rapid transit system (MRT) to deliver packages and store parcels in pick-up locations (MRT Stations).

How we built it

We used blender for the renders and fusion for the 3D printing and adobe illustrator for the laser cutting. We also used a bandsaw to cut the wood and Arduino to automate the process.

Challenges we ran into

Hardware issues. Obtaining relevant last mile delivery data for Singapore.

Accomplishments that we're proud of

Designing a holistic solution to reduce carbon emissions for last mile deliveries. Expanding the solution to fit different train models.

What we learned

A solution should be holistic for it to be a social good.

What's next for Deque by Scufftech

Implement Machine Learning Models for unsupervised learning (eg: peak and non-peak periods of commuters or common location.) to optimize the flow of last mile deliveries.