Project Info

Movely thumbnail

Team Name


Team Members

Viknesh , Zach Sim and 3 other members with unpublished profiles.

Project Description


Our CBD is the heart of a growing region, an asset for our people, and an enabler for people to achieve their goals and succeed. With strong projected growth in residents, jobs, and visitors, the central city offers great opportunities for the region’s future prosperity. But with any growth, comes its challenges. Our transport system is approaching capacity while our roads are getting more congested which will start to undermine the very liveability and culture that is a city's greatest strength. With increasing changes and variables to our surroundings, it becomes more important to know what is happening along your journey so you can plan ahead.


Movely is a simple interactive tool that allows people to visualise the traffic in real time so that users can plan their journey.
We engaged design-thinking principles to create an aesthetic, simple yet powerful tool to comprehend the current traffic situation at a glance. It can be overwhelming for people who aren’t familiar with the area to figure out how much traffic to expect in detail.
The tool caters for the planners and spontaneous people alike, who like to know how congested the roads are right now and whether it’s a good time to explore the city using their usual route or if they need to find another way to reach their destination.
Movely provides a dynamic visualisation of real time traffic with additional customized information. It features a range of options to tailor to your needs, like setting a specific location you want to keep an eye on, available car parks in your region and the number of people walking and cycling in the area near you. All this can be accessed and plugged in through a range of applications that make it convenient to access, from a web browser to your mobile screensaver. With a simplistic design, it keeps key information easy to digest while giving additional awareness to how the transport system will look like if nothing is changed in the year 2043.

Data Story

Data sources

Behind the scenes, Movely utilizes data from a range of sources.
Using NZTA’s traffic camera API, we’ve gathered snapshot images of all the different highways across New Zealand in 30 second increments. These images are used to feed through AWS AI Rekognition services that identifies the number of cars on the road for each snapshot. This data count is then used to provide a live visualization of real time traffic.
The Stats NZ Commuter matrix, Census 2013 data and population projections 2043 were used to show a historical view and make future predictions on vehicle use.
City council data was used for the 3D animated buildings and parking meter locations.

Note: Due to the size of the datasets the Application utilises it can take awhile load for first time users.

Evidence of Work



Team DataSets

Wellington Buildings

Description of Use Used to show 3d buildings in movely.

Data Set

Open Route Service

Description of Use Used to generate sample data of actual travel patterns of commuters using cars, bicycles, or walking.

Data Set

WCC Car Parks

Description of Use Used to visualise where the car parks in wellington are and if they are occupied or not.

Data Set

Motor Vehicle Register

Description of Use Used for the count of vehicles on NZ roads and future projections.

Data Set

AWS Polly

Description of Use Used to narrate our video

Data Set

Commuter matrix

Description of Use Used to get numbers of people travelling too and from area units, broken down by mode of transport.

Data Set

AWS Rekognition

Description of Use Used for counting the number of cars in the images produced from the NZTA Traffic Camera API.

Data Set

Traffic Cameras API

Description of Use The traffic camera api provided by NZTA, was fetched and piped through to AWS Rekognition for a real time dataset of car positions.

Data Set

Travel Times

Description of Use Used to identify peak travel times in Wellington.

Data Set

Household Travel Survey

Description of Use Used for proportion of population that use the different modes of transportation

Data Set

Area unit population projections

Description of Use This data has been used in conjunction with the other datasets to create an indicative forecast of future congestion.

Data Set

Challenge Entries

Public Transport for the Future

How might we combine data with modern technologies - such as AI/ML, IoT, Analytics or Natural Language interfaces - to better our public transport services. Outcomes could take the form of new commuter experiences, reduced environmental impact, or helping plan for the future.

Go to Challenge | 45 teams have entered this challenge.

Most Artistic use of data (outside the box)

Most Artistic use of data (outside the box)

Go to Challenge | 11 teams have entered this challenge.

Combating the Climate Emergency

Best hack to combat the climate emergency.

Go to Challenge | 6 teams have entered this challenge.

Best use of data to assist in a Civil Emergency

Best use of data to assist in a Civil Emergency

Go to Challenge | 3 teams have entered this challenge.

Best Creative Use Of Technology

Best Creative Use Of Technology

Go to Challenge | 13 teams have entered this challenge.

Reducing CBD Traffic Congestion

How to reduce traffic congestion or parking problems in CBD?

Go to Challenge | 39 teams have entered this challenge.

Innovate New Zealand

Best innovative hack using Stats NZ data

Go to Challenge | 16 teams have entered this challenge.