Repo related to the 2020 GS1 US Hackathon with YouTube video here.
Project name: Quantum Chain
COVID19 vaccine distribution and en-route monitoring using Quantum Computing, AI and ML tools
The current Corona-Virus pandemic has a significant impact on people's lives. To return to a “normal” people will need vaccines to minimize the risk of getting sick. How to distribute a finite and fragile resource like the COVID19 vaccine while maintaining its effectiveness and maximizing its impact and value to the whole community?
We look at the distribution of vaccine batches across the USA as an optimization problem on (1) the impact of a particular distribution and (2) the delivery routes. Once the distribution of a batch is in progress, we monitor the environment and assess the state of the vaccine packages. Data is stored using GS1 formats & conventions to be used in our AI/ML decision making and re-routing algorithms.
Step 1: Identify the maximal impact distribution plan: Identify cities for vaccine distribution by solving an optimization problem with adjustable impact function; charting delivery routes from the main distribution hubs to the targeted hospitals/clinics.
Step 2: Start a continuously monitored distribution process: Send viecles en route, monitor the microclimate, store data using GS1 standards; upon delivery evaluate the data collected and its limits. Are the states of other packages within the expected bounds?
Step 3: Re-balance and re-route the distribution: If vaccine efficiency/product quality is affected then assess for alternative nearby delivery locations that will maintain maximum impact solution; proceed with the updated delivery schedule;
Step 4: Update Model Parameters and the Data Assessment: Update the input records for better assessments, AI/ML analyzes, forecasting of the vaccine states, and impact estimates relevant to the previous steps. Prepare for the distribution of the next batch.