| Idea Name: |
ACUTE |
| Slogan: |
Intelligent Decisions for Healthy Tomorrow |
| Supervisor Name: |
Dr. Imran Mahmood |
| Supervisor Designation: |
Assistant Professor, SEECS | Research fellow in Multi scale Modeling and Simulation, Brunel University London |
| Supervisor School: |
School of Electrical Engineering and Computer Sciences |
| Supervisor Department: |
Department of Computing |
| Contact number: |
+447415010620 |
| Email ID: |
[email protected] |
| Abstract: |
| ACUTE is an AI-based Agent-Based COVID-19 simulation framework that generates reliable forecasts for the spread of Coronavirus to facilitate healthcare decision-making and policy evaluation. |
| What is the unmet need in society that your idea will fulfill ? |
| Much of the COVID-19 uncontrolled spread throughout 2020 can be attributed to our bad-decision making and unreadiness. We need to have an easy-to-use simulation framework for Coronavirus where we could design scenario-based experiments and based on the outcome, take more informed decisions. |
| Who needs it ? How many would benefit ? |
| Government officials and healthcare experts need access to a simulation framework with which they can forecast how a certain decision would impact the spread of virus before implementing it. With access to such a tool they would take much better decision that can eventually save lives of millions |
| How will the solution works |
| ACUTE uses Agent-based modelling to generate virtual agents in a simulated environment modelled after real regions. These virtual people visit supermarkets, offices, schools and mosques each day depending upon their needs. We developed a disease model that defines how Covid-19 spread and based on these rules we govern the spread of disease in the simulated environment. The results of the simulation are processed and analyzed to determine how the disease spread and how our decisions affected it. |
| Who are your competitors ? How is your solution different |
| Almost no tools for Covid-19 forecasting use agent-based simulation. We have an advantage that we can design a simulation environment which mimics real world regions and produce accurate forecasts in a much more natural manner rather than making prediction purely based on historic data. |
| Status: |
new |
| Entry Date & Time: |
2020-12-20 (1613) |
