not approved

(Bio)metrics for Automotive/Sport

₳418,000.00 Requested
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Community Review Results (1 reviewers)
Feasibility
Value for money
Impact / Alignment
Solution

The project will conduct R&D on automotive racing performance signatures using biometrics, which will inform AI that can assist or drive outstandingly. A model for tokenized rewards will be created.

Problem:

Automotive sport lacks robust quantitatively driven pathways to improved driving performance. Future automobiles & automotive metaverse experiences will both employ haptics that depend on user state.

Yes Votes:
₳ 5,770,726
No Votes:
₳ 167,358,179
Votes Cast:
251

[IMPACT] Please describe your proposed solution.

AI is changing many industries, and automotive industry is a high-value one that will be subject to AI one way or another. Rather than completely obsolete drivers, their knowledge should be rewarded through tokenization. Our solution will conduct R&D on automobile racing performance to help deliver high-quality metaverse experiences of racing and performance more generally.

The proposed project aims to use biometrics, specifically EEG and other biosignals, to improve driving and train AI to drive in an automotive sport context. The project's ultimate goal is to translate the driving experience into the metaverse. By analyzing the biometrics of drivers while they are driving, the project aims to identify patterns and correlations between the biometric data and driving performance. This data can then be used to improve driving skills and train machine learning algorithms to better understand and replicate human driving behavior. The project also seeks to explore ways to translate the driving experience into virtual reality environments in the metaverse. Overall, this project has the potential to significantly improve the safety and efficiency of automotive sports and open up new possibilities for immersive driving experiences in virtual environments.

The proposed project has the potential to also shed light on driver experience in different styles and brands of cars. This may be from the natural experience in different cars, and/or from detection of mechanical issues in cars, such as noticing when certain car functions are not working and being able to detect these un/consciously. This would add value to the automotive industry.

Tokenomics may include:

  1. A token that can be used to purchase access to the biometric data collected during the driving experience. Drivers who contribute their data could be rewarded with a certain amount of this token, which they could then use to purchase access to other drivers' data or to purchase other goods and services related to automotive sports.
  2. Develop a token system that rewards drivers with tokens for contributing data to the project. These tokens could later be redeemed for various rewards, such as discounts on automotive sports events, access to exclusive events, or other perks.
  3. Implement a staking mechanism where drivers can stake their tokens to vote on future directions of the project. By staking their tokens, drivers would have a say in the development of the project and be rewarded with additional tokens for their participation.
  4. Create a decentralized autonomous organization (DAO) that is responsible for managing the project and issuing rewards to drivers who contribute data. Drivers who hold a certain amount of tokens could become members of the DAO and have a say in the management of the project.
  5. Explore the possibility of using non-fungible tokens (NFT's) to reward drivers for their contribution. For example, drivers who contribute a certain amount of data could be rewarded with an NFT that represents a unique piece of automotive sports memorabilia or an exclusive experience related to the project.

[IMPACT] How does your proposed solution address the challenge and what benefits will this bring to the Cardano ecosystem?

The proposed project brings a novel technology to Cardano, making Cardano a first-mover chain in the space. This proposal poises Cardano to be used in a key technology in the world. It also builds on and adds functionality to existing products (successful, closed-out proposals from F7, F8).

This proposal thereby fulfills criteria of the Challenge, including the following metrics:

  • Increasing the number products available for the community to use that help to enrich the ecosystem with new use cases.

  • Increase the number of integrations that bring existing solutions together for a more seamless and connected experience between different products.

  • Increased quality of existing products & integrations through improvements and new functionality.

    [IMPACT] How do you intend to measure the success of your project?

The success of the project will be determined by completed R&D on brain and biometric functions and use-cases, and by compatibility/integration with biometric hardware. Additionally, tokenomics structure will be completed. Benefits include those mentioned in the previous section of the proposal.

<u>Risk mitigation strategy</u>:

  • Risk (1): Immediate hiring need. Our team is actively searching for an appropriate engineer now. Due to global demand for specialised tech talent and in order to attract suitable talent in a timely manner, we are offering (in the budget) an above-average salary. This will also help to increase the chances of keeping a strong engineer beyond the scope of this proposal.

  • Risk (2): Limited social/marketing reach.

  • We have budgeted for a social media in this proposal in order to begin building toward this goal from the beginning.

  • The proposer is a notable member of and leader in the SingularityNET community and ecosystem, respectively, which has multiple projects with existing and expanding user bases that could be marketed to and leveraged.

  • Risk (3): R&D on the brain/biometric/hardware aspect(s) of the project not keeping pace with the software aspect of the project. As with any project that involves hardware, they tend to not move as fast as the software side. To mitigate this, in the R&D, we will use openly available data as much as possible (much of which has already been identified). This shifts the hardware logistics into more of a software matter.

    [IMPACT] Please describe your plans to share the outputs and results of your project?

Due to the sensitive nature of the project related to cryptography and user privacy, project sharing will be limited to high-level promotion and select collaborations. High-level sharing and and marketing will be conducted over social media.

[CAPABILITY/ FEASIBILITY] What is your capability to deliver your project with high levels of trust and accountability?

Evidenced by the proposer's handful of past successful and closed out Catalyst proposals, future performance can be expected.

[CAPABILITY/ FEASIBILITY] What are the main goals for the project and how will you validate if your approach is feasible?

The goals are to complete research that determines the brain and/or biometric signatures automotive racing performance, and to develop a basic tokenomic model.

[CAPABILITY/ FEASIBILITY] Please provide a detailed breakdown of your project’s milestones and each of the main tasks or activities to reach the milestone plus the expected timeline for the delivery.

Month 1:

Obtain the means to measure automobile racing performance; e.g. access to a suitable vehicle and driver experience

Month 2:

Conduct biometric measurement of racing

Month 3:

Repeated measurement

Data analyses

Month 4:

Cross-correlation of the various data types

Insights extracted

Month 5:

Documentation of insights for AI, racing, and metaverse

Month 6:

Project completion

[CAPABILITY/ FEASIBILITY] Please describe the deliverables, outputs and intended outcomes of each milestone.

Progress reports/briefs will be delivered based on the milestones:

Month 1:

Obtain the means to measure automobile racing performance; e.g. access to a suitable vehicle and driver experience

Month 2:

Conduct biometric measurement of racing

Month 3:

Repeated measurement

Data analyses

Month 4:

Cross-correlation of the various data types

Insights extracted

Month 5:

Documentation of applicable insights for AI, racing, and metaverse

Month 6:

Project completion

[RESOURCES & VALUE FOR MONEY] Please provide a detailed budget breakdown of the proposed work and resources.

R&D and Project Management: $42,000 ($7,000 x 6 months)

Engineering: $50,400 ($8,400 x 6 months)

Biometrics hardware: $14,400 (1x slim form-factor EEG headset)

Social media / Marketing: $10,200 ($1,700 x 6 months)

Total: $117,000

An exchange rate of $0.28/ADA (reflecting the rate at the time of this writing) has been used for budget calculation.

[RESOURCES & VALUE FOR MONEY] Who is in the project team and what are their roles?

Dr. Gabriel Axel Montes, Ph.D.

Neuroscientist & consciousness expert, Ethical AI, SingularityNET (Cardano partner) pedigree; founding extended team, Head of People, Music Co-Director and guitarist for in-house touring band with humanoid robot vocalist.

Formerly, VERSES Director of Communications and researcher, building the Spatial Web (realistic metaverse).

Will serve as the project creator, leader, and director, and delegating tasks for execution. Gabriel has a small team of contractors who have track record of delivering on past Catalyst proposals.

Advisors:

  • David Harding: Advisor. CTO, SVP Engineering, Renown Security, Identity, Cloud Expert. Private Equity.

  • Dan Mapes, PhD: Advisor. Co-designer of the Spatial Wb IEEE Protocol. President, VERSES.ai & The Spatial Web Foundation.

  • Edward Brennan: founding CFO & Advisor. Venture Capitalist, Board Member, Advisor to Several StartX & Y-Combinator Companies.

    [RESOURCES & VALUE FOR MONEY] How does the cost of the project represent value for money for the Cardano ecosystem?

All costs will be commensurate to majority of wages and capital required to execute. Due to the high value-add R&D and scientific work required of the proposal, costs are above average in order to rapidly secure the human resource talent and equipment needed to conduct the work.

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