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Evidence of Work

KidPool

Project Info

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Team Name


DataNerd


Team Members


Lerr

Project Description


Project Name: Kidpool – Sharing the School Run

Overview

Kidpool is a carpool app designed to solve the first and last mile of student travel while complementing public transport. It provides safe, trusted, and coordinated rides for students, reducing congestion at schools, easing parental stress, and optimising public transport usage.

Key Features

  • Scheduled & Ad-hoc Rides: Book recurring or one-off trips.
  • Trusted Network: Only parents you know or school community members can offer rides.
  • Destination Flexibility: Drop students directly at home or the nearest public transport stop.
  • Safety Features: Verified users, school community matching, parent notifications.
  • Trip History & Planning: See past trips and upcoming schedules for transparency.
  • Public Transport Complement: Kidpool does not replace buses or trains; it optimises first/last mile connections to increase overall efficiency.

Impact

  • Families: Safe, verified rides reduce driving burden and give peace of mind.
  • Policymakers & Planners: Aggregated, anonymised journey data provides insights to optimise bus stops, reduce congestion, and improve public transport access.
  • Communities: Supports a future-ready transport system that accommodates population growth, mixed-mode travel, and complex multi-leg journeys.

Relevance to Hackathon Challenges

  • Optimising Transport Networks for School Kids:

    Kidpool addresses first/last mile inefficiencies, reduces congestion, promotes alternative transport, and supports working parents by coordinating trusted carpools. It leverages journey data to generate actionable insights for smarter route planning and safer school transport.

  • Delivering the 20-Minute Neighbourhood Plan:

    By mapping student journeys and identifying common pickup/drop-off points, Kidpool highlights transport gaps and inefficiencies, enabling planners to make local areas more accessible, liveable, and connected.


#carpool #school transport #first mile #last mile #public transport #mobility #congestion reduction #student safety #community planning #multi-modal journeys #data analytics #graph analysis #urban planning #transport insights #families #policymakers

Data Story


Current Transport Problem:
- High car dependency: Over 76,200 kids travel as car passengers vs 14,200 on public transport and 16,700 walking.

- Declining public transport use: Dropped 22% between 2017–2022.

- Multi-leg journeys: Over 40% of student trips involve two or more transport modes, increasing travel time and complexity.

- Mode mismatch: 760 kids use only one mode, mostly car passengers, while multi-modal trips dominate for buses, trains, and walking.

- Population pressure: Australia’s population expected to reach 30M by 2032, increasing potential congestion.

How Kidpool Solves This:
- Connects homes to schools & transport hubs efficiently: Reduces reliance on private cars and multi-leg inefficiencies.

- Supports public transport: By sending students to nearby bus/train stops, Kidpool complements existing networks.

- Trusted & safe rides: Only known parents in the community, verified users, school matching, and notifications.

- Data-driven insights: Aggregates anonymised journey patterns to help planners optimise bus stops, routes, and accessibility.

Outcome:

Kidpool creates a safer, more efficient, and flexible school transport system that benefits families today while providing planners with actionable insights for future-ready, connected neighbourhoods.


Evidence of Work

Video

Project Image

Team DataSets

Population Projections, Australia 2012-2071

Description of Use To see the population projections to see how it multiply the transport impact to the Australian community.

Data Set

ACT and Queanbeyan-Palerang Household Travel Survey 2022

Description of Use To understand the how ACT kids commute from home to education, as well as seeing the transport mode trend from 2017 and 2022

Data Set

Data Vic. Journey to Education 2022-2023

Description of Use To understand the dynamics and number of transport modes used for kids journey to education.

Data Set

Challenge Entries

Optimising Transport Networks for School Kids

How can we leverage graph analytics, generative AI and other data approaches to optimise public school transport networks to make it simple to get the next generation of students to school with less hassle?

#Reimagining-school-transport-networks

Eligibility: Open to all, although special consideration will be given to teams with a lead based in ACT. Contestants are strongly encouraged to use multiple sources of data including datasets outside of those listed below.

Go to Challenge | 13 teams have entered this challenge.

Delivering the 20-Minute Neighbourhood Plan

How might we use open data to understand and improve the ways people move, work, and access services — creating neighbourhoods that are more liveable, inclusive, and resilient?

#Accessible-communities

Eligibility: Open to all, but preference given to teams with a lead in VIC. At least one dataset from data.vic.gov.au must be used. Open data on transport networks, amenities, planning permits, green spaces, demographics, and mobility patterns is suggested but creativity in dataset usage and sourcing is strongly encouraged.

Go to Challenge | 11 teams have entered this challenge.