Flood Risk Visualization in Complex Virtual Worlds

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Expert Review🌟
XyrisKenn
Project Owner

Flood Risk Visualization in Complex Virtual Worlds

Funding Awarded

$40,000 USD

Expert Review
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Status

  • Overall Status

    🛠️ In Progress

  • Funding Transfered

    $5,000 USD

  • Max Funding Amount

    $40,000 USD

Funding Schedule

View Milestones
Milestone Release 1
$10,000 USD Pending TBD
Milestone Release 2
$5,000 USD Transfer Complete 18 Apr 2024
Milestone Release 3
$5,000 USD Pending TBD
Milestone Release 4
$5,000 USD Pending TBD
Milestone Release 5
$3,000 USD Pending TBD
Milestone Release 6
$3,000 USD Pending TBD
Milestone Release 7
$2,500 USD Pending TBD
Milestone Release 8
$1,500 USD Pending TBD
Milestone Release 9
$1,500 USD Pending TBD
Milestone Release 10
$1,500 USD Pending TBD
Milestone Release 11
$1,500 USD Pending TBD
Milestone Release 12
$500 USD Pending TBD

Project AI Services

No Service Available

Overview

We propose building a flood risk predictive model + API & show its utility with an advanced immersive simulation of flooding effects in a real-time 3D generated environment. We will train our model on existing real-world datasets and hydrological services, emulating Google Flood Hub's documented strategy. In Unity3D (RT3D) we will represent a map-based riverine terrain flooding event with first-person perspective: high water levels, effects of flood waters on civic infrastructure, instances of fluid simulation, interaction with vehicles, with avatar-based citizens & responders in crowd simulations. We will include ChatGPT conversational ability with select citizen and responder avatars.

Proposal Description

Company Name (if applicable)

Xyris XR

How our project will contribute to the growth of the decentralized AI platform

Extreme weather events are increasingly common: heavy rains, tropical storms & hurricanes flooding riverine & coastal regions, all resulting in loss of life, property destruction & economic pressures on all levels.

Combining robust riverine flood datasets with real-time immersive 3D first-person simulation can become a robust business for SNET, applicable across national boundaries. This will help grow the AI platform with new markets with policy-makers, government & emergency response. 

New AI services:

Yes

Description of the new services.

We will develop a flood prediction model of select locations based on Google's Flood Hub strategy of topological & hydrological model training. We will build an API service to access this model data.

Training a machine learning model combining hydrology, inundation models, and topographic map layers has proven to compensate for areas of scarce data points while actually improving accuracy (see links).

We will compare our model with Google Flood Hub's forecasting outputs to determine our accuracy. Of course, a model benefits from more iterations, and we expect to continue improving the model throughout and after this project. 

We will connect API data from our flood model to our 3D environment simulating terrain, water sources, civic infrastructure, traffic, citizenry and first responders, providing an effective multidimensional first-person immersive experience.

With this combination we can demonstrate the value of presenting flood information in an experiential first-person context.

Existing AI Services:

Yes

Names of the existing services

We'd like to utilize Photrek's Risk-Aware Assessment and SNET's Time Series Forcasting to analyse the incoming data, and potentially provide data visualization within the Unity UI as an adjunct to the experiential environment.

We will also utilize Carbix's ChatGPT and Speech to text APIs to make conversation possible with in-world avatars enacting the roles of citizens and responders.

We are also very interested in new services being built during Round 3. We're aware of other SingularityNET services coming online that will ease our access to datasets and to combine SingularityNET services. We'll use these too as they become available.

The core problem we are aiming to solve

Flooding due to climate change is having an increasingly significant impact on lives, housing, infrastructure & the economy. 
In the last three years, in Canada alone, tropical storms and hurricanes, along with exceptional levels of precipitation, have created catastrophic flooding on both coasts.
Map data coverage is often insufficient in areas most at risk due to lack of budget in smaller civic areas. Communicating these changing conditions to long-term residents & communicating strategies to volunteer responders are additional barriers to safety.

We need a way to visually portray climate-change-driven flooding events, based on data, to overcome climate skepticsm & promote life and property-saving policy changes.

AI modelling of flood prediction helps overcome scarce data points & reduces complexity of physical simulations. Pairing model data with a first-person interactive demonstration of flood consequences & strategies is highly convincing to stakeholders who may not have the science training needed to visualize the data.

Our specific solution to this problem

1. Train our own Flood Prediction model based on existing datasets and public API services.

2. Build an API which can return riverine flood prediction data from our model.

3. Within Unity, demonstrate effects of flood waters on a generated city's infrastructure:        

     - Overwhelmed levees and berms         
     - Overwhelmed sewage channels         
     - Eroded home foundations of varying quality (dirt, stone, cinder block, poured concrete, concrete posts).         
     - Interrupted services (electrical, cellular, gas, transit)         
     - Boyant objects and debris         
     - Catastrophic failure of civic structures

4. Simulate crowd behaviour of citizenry and behaviour of first responders in Unity3D.

5. Select avatars to be given conversational abiilty VIA Carbix's ChatGPT SNET API services.
     - Additionally, script an avatar lesson on emergency preparedness for residents in flood-prone areas.
     - Provide emergency evacuation routes for residents & NGOs, based on policy & data, for our select locations.
     - Compare established evacuation routes with our model's prediction of flooded locations.

Project details

Introduction:

At the time of writing, both coasts of North America is receiving a potential historic high precipitation event impacting power infrastructure and neccessitating evacuations. Canada's East coast is seeing record snowfall of up to four feet, and snowdrifts of up to ten feet, over only a few days creating subsequent flood risks from impending snowmelt and service interruptions. 
In Cape Breton, snowfall drifts are heavy enough to destroy windows, exposing occupants to frigid temperatures. Neither can first responders get through the snowfilled streets to help.
When the accumulated snow melts, these may overwhelm infrastructure with not designed for this volume of water.

In an era marked by the escalating frequency of extreme weather events such as wildfires, heavy rains, and tropical storms, the imperative for advanced flood prediction capabilities has become more pronounced. These events pose threats to coastal & riverine regions, leading to the loss of life, property destruction, and economic strains.

The integration of artificial intelligence services for modeling flood threats, coupled with immersive applications for education and training in these emergency situations, is crucial.
Our proposal focuses on developing a flood prediction model by incorporating historical precipitation with flooding datasets, then representing the data in our interactive real-time 3D Unity environment.

Project Overview:

We propose the development of a flood prediction model grounded in existing datasets made accessible through an API service on the SingularityNET marketplace. To augment user understanding, we will leverage Unity3D to visualize the flood data in a first-person simulation depicting civic infrastructure, traffic, citizens, and emergency responders.

Utilizing SingularityNET Marketplace Services:

To bolster the accuracy and effectiveness of our flood prediction model, we plan to integrate Photrek's Risk-Aware Assessment to check model accuracy. We will also compare our model outcomes with Google's Flood Hub alert JSON, which contains limited flood forecasting data. 

Additionally, we intend to incorporate Carbix's ChatGPT and Speech-to-Text APIs to enable conversations with avatars within the simulated world, allowing avatars to assume the roles of citizens and responders responding to user questions.

Addressing Climate Change Impacts:

The devastating impact of climate change-induced flooding on lives, housing, infrastructure, and the economy necessitates urgent action. Recent catastrophic events in Canada, including tropical storms, hurricanes, and historic flooding with shoreline loss, underline the urgency of our project. 

We aim to visually depict climate-change-driven flooding events based on modelling data to counter climate skepticism and advocate for life and property-saving policy changes.

Project Objectives:

1. Train a proprietary Flood Prediction model using existing datasets and services.

2. Develop an API providing riverine flood prediction data for select locations or sets of topographic and hydrological map layers.

3. Showcase flood effects on infrastructure within Unity3D, including portrayal of overwhelmed levees, berms, sewage channels, eroded home foundations, and disruption of civic services.

4. Simulate crowd behavior and first responder movement within the flood area.

5. Implement contextual conversational abilities for avatars using Carbix's ChatGPT API services.

Resources and Capabilities:

With an extensive library of Unity assets, including terrain generated from map layer data, city generation tools, the Kitbash3D model library, customizable avatar design software, behavioral graphs, fluid simulation tools, and experience in this medium, we are well-equipped to efficiently construct detailed Minimum Viable Products (MVPs). 
Our capabilities also extend to sound design, text-to-speech, conversational avatars, and Virtual Reality (VR) builds.

This robust toolkit and experience positions us to deliver a cutting-edge compelling and realistic user experience.

The integration of our flood prediction model and real-time in-game 3D simulation technology provides invaluable benefits to various stakeholders including policy makers, residents, and first responders. With enhanced predictive capabilities, we can refine our understanding of flooding impacts, facilitate research and foster advancements in flood mitigation strategies.

Benefits:

Policy makers stand to gain significant advantages from our proposal. The real-time 3D environment allows for communicating complex flood scenarios in the first person, provides shared experience in the simulation, allows the design of challenging situations without personal risk, while aiding policy makers testing informed decisions about first response strategies, land-use planning, extreme weather risks, infrastructure development, and disaster preparedness.

This immersive approach enables us to comprehend the severity and chaos of climate change-induced flooding, then formulate policies that are not only effective but also responsive to the evolving nature of these threats.

For the public, the benefits of our project extend to education of flood risks & being prepared for extended periods without electricity, heat and clean water, with potentially the need for basic first aid training. 

This heightened awareness empowers individuals to make informed decisions, evacuate when necessary, and actively participate in community resilience efforts. 

Moreover, the economic advantages are evident as well, with potential for reduced property damage and loss of life, leading to significant cost savings for both individuals and the broader economy. 

Finally, emergency response teams could benefit from our flood prediction model by gaining access to data and immersive simulations enhancing their preparedness conversations and decision-making during flood events, ultimately improving their effectiveness in safeguarding communities and mitigating the impact of disasters.

Conclusion:

In conclusion, our proposal to develop a flood prediction model, coupled with a highly interactive real-time 3D simulation, represents a strategic and worthwhile investment. The integration of AI-driven flood prediction and Unity3D simulations not only addresses the urgent need for improved forecasting in the face of escalating climate change-induced flooding but also offers a multi-faceted approach benefitting scientists, policy makers, the public, the economy, and emergency response teams.

The public benefits from increased awareness and education on flood risks, empowering communities to take proactive measures.

From an economic perspective, our proposal offers significant cost savings by visualising policy improvements that could lead to reduced property damage and enhanced protection of life.

In essence, this investment is more than a technological endeavor; it is a commitment to resilience, informed decision-making, and the safeguarding of lives and property.

The competition and our USPs

Yes

Describe how your solution distinguishes itself from other solutions (if exist) and how it will succeed in the market.

Google Flood Hub provides limited (but highly accurate) flood prediction data. ArcGIS provides flood mapping. We distinguish our model as open source, and usable within a real-time environment like Unity3D. 

We believe showing how effective a first-person demonstration of flood data is, and how accessible the model is via the SingularityNet marketplace is, without requiring an expensive software license, and aiding communities in flood risk locations, will help us to succeed in the market.

What we still need besides budget?

Yes

Describe the resources you still need

Collaboration with Singularity community leaders flood emergency protocols, in probability assessment and in model training are most welcome. I have external local contacts in mapping and geology who have offered access to their data and expertise as well.

Existing resources we will leverage for this project

Yes

Description of existing resources

We have an extensive library of Unity assets including map layer transformers used to generate terrain, roads, building massing models, rivers and lakes into a real-time format.

City generation tools, the entire Kitbash3D model library of buildings and objects, avatar design software, behavioural graphs, animal models and behavioural simulators, fluid simulation, weather simulation, ocean sims, physics sims, vehicles and vehicle controllers, time of day effects, localized weather, geosynced night/day cycles and more also allow us to quickly & efficiently build immersive MVPs.

Additionally I'm equipped for professional sound design, text-to-speech, conversational avatars, and VR builds. 

Collaboration with Singularity community leaders in probability assessment and modelling are our most powerful resource. 

Open Source Licensing

Apache

Describe license details and, if applicable, list any components that are not subject to this license.

Commercial Unity assets, datasets under other ownership, and real time Unity original project files & assets cannot be included in any open source commitment because of software license restrictions. 

The API code to access our trained model and the model code shall be made open source at the project conclusion.

Additional videos

Miro board: https://miro.com/app/board/uXjVNxtJpNg=/?share_link_id=992813906157

Carbix MVSE Highlight Reel (avatars & immersive installations)
https://www.xyris.ca/carbix-mvse/

Quick city visualization with a flooding event, and Unity map layer import screens:
https://shorturl.at/duJO0

Ocean simulation example (science fiction environment with Kitbash3D models):
https://youtu.be/jxQwmg7sLms?si=SwrmrVFk5E4Wm3Jn
Nightime city simulation:
https://youtu.be/kHhwkuJHJWo?si=CI0Ft4v2YsBVy3nM

 

AI services (New or Existing)

Proposal Video

Floog Risk Visualization - Kenn / Xyris XR

9 February 2024
  • Total Milestones

    12

  • Total Budget

    $40,000 USD

  • Last Updated

    26 Apr 2024

Milestone 1 - API Calls & Hostings

Status
😐 Not Started
Description

This milestone represents the required reservation of 25% of your total requested budget for API calls or hosting costs. Because it is required we have prefilled it for you and it cannot be removed or adapted.

Deliverables

You can use this amount for payment of API calls on our platform. Use it to call other services or use it as a marketing instrument to have other parties try out your service. Alternatively you can use it to pay for hosting and computing costs.

Budget

$10,000 USD

Link URL

Milestone 2 - Contract Signing Onboarding AI/ML talent

Status
😀 Completed
Description

Contract signing and commissioning of model development. Commence building a fictional demonstration city environment in Unity 3D.

Deliverables

Verification of commissioning AI/ML developer. Initial Unity3D environmental file of a selected location with imported map data.

Budget

$5,000 USD

Milestone 3 - Delivery of M2 Additional ML training Start API

Status
🧐 In Progress
Description

Iterate Flood Model. Start API development. Continue Unity3D environment.

Deliverables

Delivery of Milestone 2 ML model. Delivery of revised Unity environment with change log.

Budget

$5,000 USD

Link URL

Milestone 4 - Delivery of M3 ML iteration and API.

Status
😐 Not Started
Description

Delivery of the M3 Flood Model & API presenting predicted flooding of a real world geosynced location. Import of world location map layers into Unity3D surfacing and city generation.

Deliverables

Deliver iterated ML model and functioning API endpoint. Deliver updated Unity Windows desktop exe of selected terrain with a generated city atop it.

Budget

$5,000 USD

Link URL

Milestone 5 - Unity Flood location example

Status
😐 Not Started
Description

Represent Flood data in Unity from the model's API endpoint. Expectation is to layer water height with physical simulation of liquids in Unity.

Deliverables

Unity Windows desktop build of the first selected explorable area with a water surface set at the vertical axis height communicated by the API service matching geosynced location terrain map layers in Unity. Example of fluid simulation around immobile objects in Unity.

Budget

$3,000 USD

Link URL

Milestone 6 - Unity3D Infrastructure example & Model iteration

Status
😐 Not Started
Description

Add geometry in the Unity city example to represent waterways sewage channels levees and berms. Demonstrate flood waters overwhelming these channels and disrupting them. Iterate our Flood Model to improve accuracy.

Deliverables

Unity Windows desktop build with updates that include infrastructure geometry and examples of flood waters overwhelming waterways sewage channels levees and berms.

Budget

$3,000 USD

Link URL

Milestone 7 - Unity Flooding Debris & Iterate Flood Model

Status
😐 Not Started
Description

Demonstrate improved Flood Model. Add floating debris to the Unity3D example.

Deliverables

Flood Model iteration. Updated Unity Windows desktop exe with floating debris interacting with flood waters.

Budget

$2,500 USD

Link URL

Milestone 8 - Crowd simulation

Status
😐 Not Started
Description

Simulation of citizen crowds and first responders in the Unity 3D project. Crowd simulation animation will be obtained from Reallusion ActorCore assets.

Deliverables

Updated Windows Desktop builds of the Unity scene to include the crowd simulation animations and activities of first responders.

Budget

$1,500 USD

Link URL

Milestone 9 - Conversational Avatars

Status
😐 Not Started
Description

Selection of one citizen avatar and one first responder in the Unity 3D project. The citizen will describe their situation in a flood event and the first responder avatar will speak about their current activity managing the situation. This will be conversational chat provided VIA the Carbix ChatGPT API service on the SingularityNET marketplace.

Deliverables

Updated Windows Desktop build of the Unity scene to include the conversational avatars: one citizen and one first responder.

Budget

$1,500 USD

Link URL

Milestone 10 - Obstructing Debris and Structural failures

Status
😐 Not Started
Description

Addition of obstructing debris to the flooding scene. Addition of several failing structures in Unity. The debris shall match that of the environment: vehicles traffic signs trashcans rocks & trees household materials and miscellaneous objects. The failing structures will use physics simulations to show shattered buildings and infrastructure in a catastrophic flooding scenario.

Deliverables

Addition of immobile debris in the Unity scene. Addition of failing destructible objects. Updated Windows Desktop Build demonstrating first-person exploration of the flooded environment and conversational interaction with citizen and responder avatars.

Budget

$1,500 USD

Link URL

Milestone 11 - SNET Market Integration & Final Deliverables

Status
😐 Not Started
Description

Final delivery of ML model API scripts and a compiled Unity Windows desktop exe. Integration of the API with the SingularityNET marketplace.

Deliverables

1. Delivery of ML model scripts & repositories delivery of final Windows Desktop exe. 2. Integration of services with SingularityNET Marketplace.

Budget

$1,500 USD

Link URL

Milestone 12 - Marketing

Status
😐 Not Started
Description

We will hold a streamed video event showcasing our service on SingularityNet Marketplace and a demonstration of the Unity 3D Flood Event application.

Deliverables

Live streamed event presenting our Flood Model and the Unity 3D Flood Event app.

Budget

$500 USD

Link URL

Join the Discussion (7)

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7 Comments
  • 0
    commentator-avatar
    XyrisKenn
    Feb 12, 2024 | 10:04 AM

    After watching my presentation (I'm getting better at that!), there are two questions I want to delve into again: - Is the model scalable? The ideal situation would be to succeed in developing a model that understands & predicts riverside inundation accurately, that is, how does water behave in riverside flooding in a generalized sense, then apply that intelligence to local maps. I think this is a situation of "shoot high but aim low": we can access inundation datasets publicly that are localized, so we will start building in a localized sense for this project, and rely on expert ML guidance to eventually develop a useful generalized model over time, outside the project (and perhaps in a subsequent DF round). This kind of model should become usable worldwide as an open-source project at SingularityNET. - Who are the customers? Thinking of this more critically as a business, it makes sense to approach well-financed entities as customers, yet, municipalities with limited budgets are the entities who need the data most to save lives and property. So an ideal situation might be: - Find customers in business and private schools who see value in simulating first-person responder or citizen training with their staff or students. - Approach provincial entities like GIS/Geological survey who wish to combine their mapping data with our Model & real-time simulation, & investigate how our ML model could supply accurate data for incomplete locations. Beneficial collaborations are also likely in this scenario; the GIS/Geological scientists I've worked with are interested in new technologies. Thank you for those questions and your kind attention.

  • 0
    commentator-avatar
    Jan Horlings
    Feb 1, 2024 | 3:18 PM

    Hey Kenn, Coming from the Netherlands I can certainly relate to the necessity of this! :-) What is not exactly clear to me: Are the simulations based on a) Some example imaginary world, or b) On real-world actual situations? - In case of 'a' How exactly will this help policy makers i their local situation? - In case of 'b' That would seem hugely ambitious. Where would you get the proper 3D maps of a specific environment, for starters?

    • 1
      commentator-avatar
      XyrisKenn
      Feb 1, 2024 | 7:05 PM

      Hello Jan! Thank you for your question, and mentioning this ambiguity in my proposal. Allow me to clarify. Modelling datasets are real-world. I can also access real-world map layers data and bring these into Unity; Unity then translates the topographical maps and roads, rivers and lakes into 3D meshes that can be explored in a first-person view. In fact, the test world I'm now building is based on current flooding on the Gudenå River in Denmark, near Tvilum Klosterkirke if Google Flood Hub is placing its marker accurately. There is also flooding in northern Poland on the Brda river. In the proposed detailed Unity simulation, to perfectly replicate a real city is too large a job, so I will place instead a generated city, then focus instead on the effects of flooding on structures and services, and add conversational avatars that will role-play residents and responders. A policy maker's project could use the flood model data, trained on real-world datasets, in a Unity or Unreal city simulation of their own to show flood effects and the results of policy changes. This requires time but is entirely possible. I believe seeing flood effects in the first person is dramatically different to viewing it on a 2D map. With successful training of a model on how river flooding behaves on the land, with hydrological principles, this should also be applicable to imaginary or generated terrain, which would be useful for areas with scarce data.

      • 0
        commentator-avatar
        Jan Horlings
        Feb 2, 2024 | 12:02 PM

        wwo. Amazing!

  • 0
    commentator-avatar
    seirayun
    Jan 30, 2024 | 10:13 AM

    Hi Kenn, a great project. I love it:) Could you clarify who are the intended users of this service? I see "stakeholders (residents), policy makers, and provide value to emergency responders"; are you targeting them? If so, will there be any difference in user experience for each persona?

    • 0
      commentator-avatar
      XyrisKenn
      Jan 31, 2024 | 10:50 PM

      Hello Seirayun. Thank you! Your project is interesting to me too. I appreciate your question. Intended users are people interested in communicating flood prediction to their communities to show risks & discuss mitigations and/or change policy. I see also this benefits for responder teams who want to use an immersive experience for training purposes.

      • 0
        commentator-avatar
        XyrisKenn
        Feb 1, 2024 | 1:43 AM

        Additionally we'd like to have a flood prediction model accurate enough for expert use, either during this Deep Funding test run or VIA improvements to the model in a subsequent round of funding.

Expert Review

Overall

5

user-icon
  • Feasibility 5
  • Viability 5
  • Desirabilty 5
  • Usefulness 5
Good value for money!

The project addresses a key segment that a lot of innovations do not address, the issue of flooding is mostly overlooked by a lot of innovations, what's fascinating is that this project will be doing so much with so little amount of dollars this provides value for money, and the technical feasibility of the project is not in doubt because this team has been working on similar projects for a while now. This is a highly recommended project

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2 ratings
  • 0
    user-icon
    seirayun
    Feb 11, 2024 | 4:25 PM

    Overall

    5

    • Feasibility 4
    • Viability 4
    • Desirabilty 5
    • Usefulness 5
    Impactful project that could help many people

    This is a great project that includes several features. It involves integrating Unity3D to create a simulation of riverine terrain flooding, as well as fluid simulation and interactions with vehicles, avatar-based citizens, and responders in crowd simulations. Additionally, it includes ChatGPT integrations. If the project is realized, it will be highly useful.

    However, there is a concern regarding the project's scope, as it is quite large. It is important to assess whether it can be implemented within the proposed budget.

  • 1
    user-icon
    JQSammy2024
    Feb 8, 2024 | 5:30 PM

    Overall

    5

    • Feasibility 4
    • Viability 4
    • Desirabilty 5
    • Usefulness 5
    Flood mapping review

    Overall, the project is exciting to read about as exacerbated flooding from global heating may affect areas unexpectedly. 

     -Allows app users to map flood routes that may affect their home and work habitats.              -

    -Great for planning evacuations, or remaining off-road and refraining from traveling. 

    -Useful tool for emergency response. 

    -Deploying on the SNET platform as a way for users to download or access the app without or with endpoints would be the next level, if done. 

    Challenges;

    -getting users to download during non-flood periods and plan ahead with the app should be addressed.

    -where do users go and how to evacuate during these flood events should be included for individuals as well as Govt/NGO users and depends on the predictive ability of the app to determine which areas will or will not flood during rainy season and flash flooding. 

Summary

Overall Community

5

from 2 reviews
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    2
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  • 3
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  • 2
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Feasibility

4

from 2 reviews

Viability

4

from 2 reviews

Desirabilty

5

from 2 reviews

Usefulness

5

from 2 reviews