ideating AI models to improve climate modeling

chevron-icon
Back
project-presentation-img
Presentation
oluwaseun oladipupo
Project Owner

ideating AI models to improve climate modeling

Funding Requested

$5,000 USD

Expert Review
Star Filled Image Star Filled Image Star Filled Image Star Filled Image Star Filled Image 0
Community
Star Filled Image Star Filled Image Star Filled Image Star Filled Image Star Filled Image 3.7 (6)

Overview

Climate change presents one of the most pressing challenges of our time, with far-reaching impacts on ecosystems, economies, and societies worldwide. To better understand and mitigate these impacts, there is a critical need to enhance our climate modeling and prediction capabilities. This project proposal aims to leverage advanced artificial intelligence (AI) models to improve the accuracy, efficiency, and reliability of climate modeling and prediction. Climate prediction data will be sourced from IPCC, ECMWF, CPC etc and then will be modelled on SingularityNET. This project will attract policymakers and the public to SingularityNET.

Proposal Description

How Our Project Will Contribute To The Growth Of The Decentralized AI Platform

Climate Change is a trending topic, attracting attention all over the globe. Our solution will take climate data from reputable Climate Change agents and process the data into what is more easily understandable for the public, this refined data will be integrated into SingularityNET platform. This initiative will drive public engagements and interface with the SingularityNET Platform on a daily basis. 

Our Team

Team Lead

Oluwaseun Oladipupo

Has a strong background in Climate Science

Conducted research on the application of AI techniques in Climate Science

Collaborated with interdiciplinary teams to integrate AI models with simulation models

A practising Environmental and Climate Science Specialist

View Team

Please explain how this future proposal will help our decentralized AI platform grow and how this ideation phase will contribute to that proposal.

The proposed ideation project aims to explore and develop AI models that can significantly improve climate modeling. Climate change is a trending topic globally, government and the public at large are interested in ways to reduce global warming and its impact, this solution will offer predictive analysis to help slowdown on climate change and also leveraging on SingularityNET advanced AI technology to enhance the accuracy, efficiency, and predictive capabilities of climate models. The focus will be on utilizing the decentralized AI platforms to distribute the computational load and foster collaborative innovation.

Clarify what outcomes (if any) will stop you from submitting a complete proposal in the next round.

I will only stop if this idea is not selected.

The core problem we are aiming to solve

Climate change is influenced primarily by human activities such as greenhouse gas emissions, deforestation, and industrialization, this poses significant challenges to ecosystems, economies, and societies worldwide.

The core problem that climate modeling and predictive analysis aim to solve is understanding and mitigating the impacts of climate change.

A lot of people are unaware that we can model environmental parameters and use the output as a predictive tool to model climate change. This solution will make climate model and predictive analysis more accessible and more understandable to the public. The solution is a WIN WIN for both SingularityNET, the public and our environment.

1.    

Our specific solution to this problem

Our solution is summarised below

  1. Gather data from reputable Climate Change agents such as IPCC, ECMWF, CPC
  2. Model development - Train machine learning algorithms. Choose appropriate model architectures and optimization techniques.
  3. Validate and evaluate the performance of the AI models using independent datasets and cross validation techniques.
  4. Integrate the Climate Models into SingularityNET platform
  5. User Interface Development - develop user friendly interfaces or visualization tools to communicate the AI model outputs to the public. These interfaces will present climate predictions and analysis results in an accessible and interpretable format, enabling traffic to SingularityNET platform.
  6. Feedback and Iteration: Gather feedback from users and stakeholder to improve the usability of the solution. Incorporate new data, update model parameters and refine algorithms based on feedback and emerging scientific insights.
  7. Scalability and Robustness - monitor to ensure the solution remains scalable and robust enough to handle large user interfaces and engagements.
  8. Real time monitoring and forecasting

Project details

Problem Definition

Climate change refers to the long-term alteration of temperature, precipitation patterns, sea levels, and other climate variables on Earth. The primary driver of contemporary climate change is the significant increase in greenhouse gas emissions, primarily carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), resulting from human activities such as burning fossil fuels, deforestation, industrial processes, and agriculture.

The consequences of climate change are widespread and profound, affecting ecosystems, economies, and societies worldwide. These impacts include rising temperature, depletion of ozone layer, loss of biodiversity, extreme flooding, extreme drought etc.

Majority of the general public are not well informed about how climate change data can be utilised to generate predictive analysis that will inturn guide our environmental activity to ensure that our environmental impact is further minimised to As Low As Reasonably Practicable (ALARP).

The Solution, serves several critical purposes in understanding and addressing climate change. The solution also make gather and interpretes climate data, these data are modeled into predictive analysis, This analysis helps policy makes, government and the general public to study trends and the emerging impacts on the environemnt.

The solution will be incorporated on SingularityNET platform, this solution will drive traffic and daily engagements to the platform. The solution will also help SingularityNET to decentralize AI solutions for Climate issues.

Existing resources

Climate and environmental data will be sourced from reputable irganizations such IPCC

Proposal Video

DF Spotlight Day - DFR4 - Oluwaseun Oladipupo - Ideating Ai Models to improve Climate Modelling

7 June 2024
  • Total Milestones

    4

  • Total Budget

    $5,000 USD

  • Last Updated

    13 Jun 2024

Milestone 1 - Research and Concept Development

Description

To conduct a thorough review of existing literature and concepts related to AI applications for climate change mitigation. This milestone serves as the foundation for the ideation process by synthesizing existing knowledge and identifying gaps where AI can make a significant impact. The literature review will inform subsequent stages of the proposal, ensuring that our approach is grounded in current research and best practices.

Deliverables

1. Identifying and reviewing academic papers, industry reports, and case studies on AI and climate change. 2. Analyzing existing AI technologies and their effectiveness in mitigating climate change impacts. 3. Identify key challenges and opportunities in leveraging AI for climate change mitigation In conclusion A comprehensive report highlighting some AI technologies and their potential applications in climate change mitigation will be given to SingularityNET

Budget

$2,000 USD

Milestone 2 - Conceptual Design and Ideation

Description

To brainstorm and conceptualize innovative AI-driven solutions for specific climate change challenges identified in Milestone 1. This milestone focuses on ideation and concept development, exploring diverse AI approaches to address identified climate change challenges. It encourages creativity and innovation while ensuring that proposed solutions are practical and aligned with real-world needs.

Deliverables

1. Brainstorm potential AI applications based on the findings from Milestone 1. 2. Develop conceptual designs for at least three distinct AI-driven solutions. 3. Evaluate the feasibility and scalability of each proposed solution. In conclusion, A detailed concept report outlining proposed AI solutions, their potential impacts, and implementation strategies will be given to SingularityNET

Budget

$1,500 USD

Milestone 3 - Model Selection and Architecture Design

Description

Selecting the appropriate model and designing its architecture require careful consideration of the project objectives available data computational resources and desired outcomes.

Deliverables

• Evaluate different AI techniques such as machine learning algorithms and deep learning architectures for climate modeling applications. • Design the model architecture considering factors like input features network structure and computational requirements. • Conduct initial experiments to assess the feasibility and performance of different model configurations. In conclusion, a comprehensive report of the selected model and architecture design will be submitted

Budget

$1,000 USD

Milestone 4 - Feasibility Assessment and Close-out Report

Description

Selecting the most promising AI solution and propose a preliminary prototype design. This milestone focuses on assessing the practicality and technical feasibility of proposed AI solutions. It involves detailed planning and initial design research to ensure that the proposed prototype is feasible

Deliverables

1. Assessing the feasibility and technical requirements of each proposed prototype. 2. Selecting the most feasible AI solution based on predefined criteria. 3. Develop a preliminary prototype design for the selected solution. In conclusion, a well detailed report highlighting the proposed prototype will be given to SingularityNET

Budget

$500 USD

Join the Discussion (1)

Sort by

1 Comment
  • 0
    commentator-avatar
    Gombilla
    Jun 2, 2024 | 6:15 PM

    Great efforts ideating this. This would wan to talk about the complexity and scale of climate modeling, as well as the need for large-scale data collection and processing. Climate modeling requires extensive data from various sources, and ensuring the accuracy and reliability of this data can be challenging. You may want to consider all these during your ideation. Thanks

Reviews & Rating

Sort by

6 ratings
  • 0
    user-icon
    Vuthuthuy031096
    Jun 10, 2024 | 10:34 AM

    Overall

    4

    • Feasibility 4
    • Viability 3
    • Desirabilty 4
    • Usefulness 4
    Ideating AI Models To Improve Climate Modeling

    - The project leverages advanced artificial intelligence (AI) models to improve the accuracy, efficiency, and reliability of climate modeling and prediction. I find this to be a good, promising idea that will significantly improve the accuracy, efficiency, and predictability of climate models. The team should add details about the AI ​​models used to develop this project.
    - I am not satisfied with the team's capacity and experience. The group should add information about the capacity and experience of group members in open links for the community to easily check. A lack of information from members reduces the feasibility of the project.
    - However, I think this project should still be developed to solve the urgent problem of climate change. The project's solution integrating AI technology will help solve climate problems, growing and strengthening the reputation and potential benefits of AI technology.

  • 0
    user-icon
    Max1524
    Jun 9, 2024 | 4:15 PM

    Overall

    2

    • Feasibility 2
    • Viability 3
    • Desirabilty 2
    • Usefulness 2
    All 3 members quickly added identity information

    I was disappointed that all 3 members of the team were anonymous. There is not a single bit of identity to add to the feasibility. I seriously request the team to add information of all three, otherwise at least one person is the owner of the Oluwaseun Oladipupo project so that everyone can know.

  • 0
    user-icon
    CLEMENT
    Jun 2, 2024 | 6:19 PM

    Overall

    4

    • Feasibility 4
    • Viability 4
    • Desirabilty 5
    • Usefulness 5
    Potential to enhance predictive climate models

    Hi Oluwa. I believe your project has the potential to enhance the accuracy, efficiency, and predictive capabilities of climate models, which are essential for understanding and mitigating the impacts of climate change.

    From a general perspective, this project's contribution to climate modeling could lead to more informed decision-making and policy development regarding climate change mitigation and adaptation strategies. By providing predictive analysis to help address global warming and its impacts, the project aligns with the growing interest in climate-related initiatives and could make a meaningful difference in addressing one of the most pressing challenges facing humanity.

    Kudos

  • 0
    user-icon
    Tu Nguyen
    May 31, 2024 | 4:24 AM

    Overall

    4

    • Feasibility 4
    • Viability 4
    • Desirabilty 4
    • Usefulness 4
    Ideating AI Models To Improve Climate Modeling

    I have 2 small comments. First, they should share more details about the members. For example, they can share members' social network links. In the project team, there are some members who are still waiting. Second, in the milestones section, they should clearly identify the start and end times of the milestones.

  • 0
    user-icon
    Rafael_Cardoso
    May 27, 2024 | 2:49 PM

    Overall

    3

    • Feasibility 3
    • Viability 3
    • Desirabilty 4
    • Usefulness 3
    How will the model account for Externalities?

    Climate change is for sure a big topic that has attracted the attention of many individuals, societies, and governments. Being so, this solution is positioned in a niche with a lot of interest and potential which is positive. While the problem and interest in climate change are well depicted within the proposal, it would be good to explore the need for a climate modeling AI model, and how much are governments, companies, or individuals actually willing to pay for such a solution, as well as the concrete impact this solution could have in the real world. 

    Another question I have from the IA model presented here, is whether it will analyse and model climate only based on current data, or wether it will also allow running simulations based on changes in certain variables? 

    Also wonder what is the strategy for this AI Model to account for positive externalities? With an AI model with a modeling capacity based on variables, it would be easy to come to conclusions such as, if we diminish the number of flights by 30% there would be an X% reduction in climate deterioration in 2030. However, will the model be flexible to account for positive externalities that might change previous relationships between variables? For example, there is a very interesting reforestation solution, that showed a very promising potential to help fight climate change while fighting food scarcity, as reforestation contributes to the absorption by Nature of higher levels of CO2. What is your strategy to account for such a change in circumstances? A lack of a strategy could make simulations extremely biased and the AI model wouldn’t actually be effective.

    What would be the eventual business model for such an AI? Would you focus on selling it to Governments? The Business Model is certainly important to understand how this AI would be used and who could eventually be the customer for such AI.

    Would this AI model be concerned in any way with promoting new solutions and innovative proactive behavior that generate a positive impact on the environment, such as reforestation, or would it just focus on promoting a reduction of emissions?

    I think this is an interesting use case, but would definitely need some more clarification in order to be able to have a clear notion of the real potential of this proposal.

  • 0
    user-icon
    Joseph Gastoni
    May 23, 2024 | 1:35 PM

    Overall

    5

    • Feasibility 5
    • Viability 5
    • Desirabilty 4
    • Usefulness 5
    using AI to improve climate modeling on SNET

    This proposal outlines using AI to improve climate modeling on SingularityNET. Here's a breakdown of its strengths and weaknesses:

    Feasibility:

    • Moderate-High: AI for climate modeling is a promising area, but the project complexity and computational demands need careful assessment.
      • Strengths: The proposal leverages existing climate data sources and explores established AI techniques.
      • Weaknesses: The proposal lacks details on the specific AI models to be used and how SingularityNET's platform can handle the massive computational needs.

    Viability:

    • Moderate: Success depends on securing funding, technical expertise, and attracting users beyond climate specialists.
      • Strengths: The project addresses a critical global issue and aligns with SingularityNET's goals.
      • Weaknesses: The proposal needs a clearer strategy for user engagement beyond just policy makers and the general public. The long-term maintenance and updates for the AI models need to be addressed.

    Desirability:

    • High (for a specific audience): For climate scientists, policymakers, and environmentally conscious individuals, this could be highly desirable.
      • Strengths: The proposal caters to a growing demand for more accurate climate predictions.
      • Weaknesses: The proposal needs to broaden its appeal beyond climate specialists by emphasizing the user-friendly interface and the potential impact on everyday life.

    Usefulness:

    • High Potential: The project has the potential to improve climate modeling and inform decision-making, but hinges on effective implementation, user adoption, and ongoing model updates.
      • Strengths: The proposal offers a framework for using AI to analyze climate data and generate insights.
      • Weaknesses: The proposal lacks details on how the project will ensure the accuracy and interpretability of the AI models' outputs.

    Overall, the proposal has a valuable goal, but focus on:

    • Technical Details: Provide more details on the specific AI models to be used, the computational resources required, and how SingularityNET's platform can handle them.
    • User Engagement Strategy: Outline a strategy for attracting a wider range of users beyond climate specialists. This could involve developing educational materials and visualizations that translate complex data into understandable information for the public.
    • Model Maintenance and Updates: Address how the project will ensure the ongoing updates and maintenance of the AI models to reflect new scientific data and evolving climate patterns.

    Strengths:

    • Addresses a critical global issue of climate change.
    • Leverages existing climate data sources and explores established AI techniques.
    • Aligns with SingularityNET's goals of decentralized AI solutions.

    Weaknesses:

    • Lacks details on the specific AI models and the computational demands of the project.
    • Needs a broader user engagement strategy beyond climate specialists.
    • Needs to address the long-term maintenance and updates of the AI models.

Summary

Overall Community

3.7

from 6 reviews
  • 5
    1
  • 4
    3
  • 3
    1
  • 2
    1
  • 1
    0

Feasibility

3.7

from 6 reviews

Viability

3.7

from 6 reviews

Desirabilty

3.8

from 6 reviews

Usefulness

3.8

from 6 reviews

Get Involved

Contribute your talents by joining your dream team and project. Visit the job board at Freelance DAO for opportunites today!

View Job Board