Seeking Experts to develop a Trial demonstrating effective use of Londoner’s Travel Data

OVERVIEW

Wazoku, the Seeker for this Innocentive Marketplace Expertise Challenge, on behalf of Transport for London (TfL), is seeking experts to conduct a trial to demonstrate effective use of mobile device location data and to develop a standard process for data collection and processing, the aim being to generate valuable insights into how Londoners travel and to identify opportunities for optimisation.

The trial is associated with the TfL Go app which was launched in 2020 and features a digital Tube map, network status updates, a multi-modal journey planner, and real-time bus arrival information. TfL Go has been downloaded over 10 million times and has more than 1.3 million monthly users. This user base provides TfL with an opportunity to generate a meaningful location-based dataset via the app.

This is a Marketplace Expertise Challenge seeking applicants to propose a solution approach and conduct a trial in collaboration with TfL. The Solver is invited to submit a written application about their approach to be evaluated first by Wazoku and then finalists by TfL, with the goal of establishing a collaborative partnership for the trial.

Solvers with a viable application and approach will be supported by Wazoku:

• With the potential to be invited to pitch their application to TfL in late March
• The trial must be completed during the following 12 months, by 31 March 2027
• Successful applicant(s) will work with TfL to trial their solution(s) for a location-driven data collection and analysis process, and to trial these with TfL customers. Any consideration of further adoption will be subject to business need, funding availability, TfL governance approvals, and the outcome of any future compliant procurement process
• Potential further support in the development of a prototype/pilot

In return, Wazoku will retain a share of 20% of any financial benefits you are paid for the trial and afterwards for your technology, as a result of the trial.

Submissions to this Challenge must be received by 11:59 PM (US Eastern Time) on February 11th, 2026.

Please review the later Participation Guidance section before submitting a proposal.
- Login or register your interest to apply!

ABOUT THE SEEKER & ELIGIBILITY

Wazoku is an innovation ecosystem platform encompassing AI, market intelligence, venture building, patent analysis and open talent networks. It centralises data, talent, and tools to make innovation measurable, impactful and able to solve pressing challenges.

Wazoku also operate Innocentive open innovation Challenges like this one, supporting the preeminent problem solver community who have delivered breakthrough results for organisations like NASA, the UK Ministry of Defence, the International Rescue Committee, and ExxonMobil.

 

Transport for London (TfL) is responsible for the day-to-day running of the UK capital's transport system. TfL must cater for more than 3.6 billion passenger journeys made each year.

The TfL Go app was launched in 2020 and features a digital Tube map, network status updates, a multi-modal journey planner, and real-time bus arrival information. Customers can also sign in to view their payments and travel history, top up their Oyster cards and opt in to receive service notifications.
 

This challenge is open to sole innovators, industry, academic and research organisations of all types and sizes.

THE CHALLENGE

Background

TfL must cater for more than 3.6 billion passenger journeys made each year.

As of November 2025, TfL Go has been downloaded over 10 million times. It currently has more than 1.3 million monthly users and is growing at a rate of 30% per year. This user base provides TfL with an opportunity to generate a meaningful location-based dataset via the app. Customers can also sign in to view their payments and travel history, top up their Oyster cards and opt in to receive service notifications.

Motivation for the Challenge

TfL wishes to understand how services can be improved by analysing users’ location data, enabling the identification of journey patterns at both individual and aggregate levels. Gaining insight into individual movements and identifying the modes of transport used—across public transport, walking, cycling, and driving—will support the creation of customer profiles and allow for tailored journey advice, ultimately enhancing customer experience.

Applying privacy-enhancing technologies and techniques—such as anonymisation and pseudonymisation—to large-scale data sets will provide a comprehensive view of movement across London and inform solutions for efficiency and achieving net zero, all while protecting individual identities.

There has already been some preliminary work; in 2019, prior to the launch of TfL Go, a small-scale location data exploration was conducted with approximately 20 TfL staff members. This involved an in-house test app capturing GPS data at various levels of detail, allowing for early research into journey mapping and mode detection. TfL now intends to expand on this foundation by defining and implementing a standardised process for location data collection and generating a suitable dataset for trial purposes.

The Challenge

We are seeking applicants for a trial to demonstrate effective use of mobile device location data and to develop a standard process for data collection and processing. The aim is to enhance existing TfL data sets at both an individual and aggregated level, generating valuable insights into how Londoners travel and identifying opportunities for optimisation.

We would like to better understand how TfL might make use of tools and methods built into smartphone hardware and available to an app, to collect mobile device location data at an appropriate level of granularity, and process that data to prepare it for analysis.

This will help TfL to quickly understand the potential of collecting high quality location data, and how it can be used to deliver greater customer and business value.

Using the successful applicant’s method for data gathering, TfL will require a trial dataset to be generated that achieves the above, providing a sizeable and representative dataset to explore and test hypotheses against.

To reach these aims it is expected that a trial will need to be undertaken to demonstrate:

• data collection,
• data processing and management,
• data validation,
• data analysis and insight

The successful applicant will work collaboratively with a TfL-supplied partner who will run the trial and be responsible for trial recruitment and management. The size and duration of the trial is to be determined based on the required outputs, built collaboratively with the successful applicant, trial manager and TfL.

In parallel to this challenge, TfL is also undertaking research into customer perceptions around location data sharing via mobile apps, and specifically attitudes to sharing data with TfL. The outputs of this research will be shared with the successful Solver to help guide and shape the trial.

Part 1

How might we define a location data collection standard process that maximises the opportunity for TfL to generate network insights and power customer-facing features, whilst minimising personal data collection?

Capture specification including but not limited to:

• When to start capturing, when to stop capturing location
• Top/tail journey (privacy zones)
• Location data capture underground on the TfL network

Part 2

How might we process, transform, and maintain the dataset defined through part 1 to ensure it is ready for analysis by TfL?

Areas to be covered include but are not limited to:

• Inferred mode of travel
• Identification of end-to-end journeys including multi-modal travel
• Implementation of privacy enhancing technologies and techniques (including, but not limited to, anonymisation and pseudonymisation processes)
• Demographic inference
• Ensuring separation of the aggregated and personalised datasets

TfL would also like to understand more about the system architecture, data processing rules, and data storage, management and retention rules that a live service would require.

SOLUTION REQUIREMENTS

Your application should detail your proposed approach, methods and tools for conducting a trial that fulfills Parts 1 and 2 of the Challenge (with your architecture/rules etc), considering the following requirements and assessment criteria:

Functional Requirements

• Use a smartphone app with iOS and Android versions to collect data
• Any trial will not be run through TfL Go (although if successful, the technology/solution could be licensed for integration into TfL Go)
• Data should be corroborated with travel diaries, to be led by TfL’s trial manager
• Integrate with a collection API or similar, to be specified during the trial
• There must be facility to port data directly into TfL's datastore so that TfL can use the data for further analysis

Technical Requirements

• Determine the suggested accuracy of location data to support desired outcomes, TfL wants to understand how granular this must be, to achieve required performance
• Identify individual trips, including information such as start and end point, time taken, inferred mode, trip type etc
• Provide options for TfL to access algorithms and models used for analysis at the end of the trial

Operating Conditions

• Process data in accordance with UK data protection legislation
• Provide pseudonymised data or anonymised and cleaned/store in appropriate way
• Provide a subset of the data (to be agreed with TfL) in the data’s raw form
• Delete data in line with the retention rules, defined as part of the project in collaboration with TfL's Information Governance team. TfL may retain anonymised or aggregated outputs from the trial for audit, transparency, and future planning purposes

Cost Requirement

Applicants should outline the expected costs for this trial including development, integration with trial running, data processing and analysis, and, if appropriate, IP licensing costs (for the trial period only).

Out of Scope - the trial solution should not:

• Require integration into TfL Go or be another travel app/Journey planning application
• Include a full insights analysis of the data
• Deliver app features for TfL Go or propose specific uses of the location data for personalisation of customer-facing features or business insight

Proposals will be assessed on:

• Relevance to the defined challenge
• Benefit of implementation
• Feasibility/economic viability
• Innovative nature
• Ability to participate in a trial to be completed no later than 31 March 2027
• Credibility of Solver
• Coherence of the proposed business model
• Development potential
• Maturity of the solution
• Suitability for the intended geographic market
• Understanding of, and compliance with, UK data protection legislation

YOUR SUBMISSION

Please login and register your interest, to complete the submission form and add attachments.

The submitted proposals must be written in English and include:

1. Participation type – you will first be asked to inform us how you are participating in this challenge, as a Solver (Individual) or Solver (Organization).
2. Idea Summary - Please identify your technology and its advantages for the potential solution to the challenge (Keep this summary under 300 words. Below, you can also upload up to 3 supporting documents - PDF, Word, PowerPoint and images (jpg and png), Max 10MB per file).
3. Technology Readiness - Please select which TRL (Technology Readiness Level) your technology is currently at.
4. Describe your technology readiness level (Keep the description under 300 words).
5. Intellectual Property - Describe your intellectual property (IP) status. Have you, or do you intend to, protect IP status associated with your technology? Please identify the IP status for any supporting technology. (Keep the description under 300 words).

PARTICIPATION GUIDANCE

1. Submission Close Date: Submissions to this Challenge must be received by 11:59 PM (US Eastern Time) on February 11th, 2026.
2. Late submissions: Late submissions will not be considered.
3. Multiple submissions, One Maximum: In case of multiple submissions by the same Solver, only one submission – the final one submitted – will be considered. Any other submissions will be deleted prior to evaluation.
4. Submission form and attachments: Your submission will first be evaluated by Wazoku and finalists by TfL’s evaluation team, first reviewing the information and content you have submitted at the submission form, with attachments used as additional context to your form submission. Submissions relying solely on attachments will receive less attention.
5. Evaluation notification steps: After the Challenge submission close date, Wazoku will review and select the solutions it will propose and position with TfL, according to the timeline in the Challenge header. Everyone who submits a proposal will be notified about the status of their submissions.
6. Use of AI: Please note that any submissions produced solely with generative AI are not of interest.
7. Learn more: Find out more about participation in Innocentive Challenges.