Currently Funding

3 Projects To Fight Covid-19 using advanced technology

DIY @ Home Covid-19 Test

$250,000

USD needed

Facial recognition technology leveraging facial expression patterns using machine learning models trained with datasets curated consenting covid-19 infected people .

3D Printed Ventilators

$1,250,000

USD needed

Fund development of this high volume Rapid 3D printed Ventilator production system that costs less than current manufacturing standards and produces more life saving ventilators faster.

Consolidated SCM Bidding

$250,000

USD needed

The United States is bidding for supplies to fight COVID-19 with bids from the federal, state, and county governments. Consolidate redundant bids for strategic winning bids that cost less.

WORLD WAR Covid-19

Humans Vs Covid19

This is biological war threatening the human race as a species regardless of color, creed, or nation.

Address

401 Bay Street 16th Floor
Toronto ON M5H 2Y4 Canada

Email

jesse@covid19star.com.com
support@covid19star.com

Business Info

6360025 CANADA INC.
Business Number 862808896

Coronavirus attack in microscopic view. Virus from Wuhan
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Project 1: DIY @ Home Covid-19 Test

A smartphone app that tests for covid-19.Possible with machine learning models trained using computer vision from datasets of people confirmed with covid-19 infection.

Human facial expressions are consistent for everyone regardless of who they are and where they come from. Our face reveals so much about how we feel, our physical health, and the state of our lives. The smile is a universal example of happiness recognized by anyone on the planet regardless of language spoken or education level.

If you are happy, you smile, if you are sad, you frown, and you may or may not be conscious of your facial expressions. What if we all made the same expression when we are sick and what if that was specific to the type of ailment? Computer vision training for machine learning models to identify patterns in facial expression that are invisible to the naked eye is why we need data sets of people before confirmed infection, during (as well as the added benefits of social media grouping clusters of people who were together at the time of contagious but unknown infection.

We are all human and we share consistent patterns of facial expression. If we all smile when we are happy maybe we all make the same expression when we are infected with COVID-19 and we can’t see it with human eyes. Computer vision and ML training with algorithm catalogues and data-sets organized here we can maybe identify patterns using machine learning models that the human eye can’t recognize.

The number of infected people worldwide grows exponentially every day. This makes data-sets available across all nations from all sorts of people from all walks of life. If we can get those who have smartphones with auto backups (e.g. consent to share app data from WhatsApp, iCloud, google photos, Samsung cloud/, one drive, etc.) To give us access to their photos taken before and after they were sick we may be able to put together databases that we can use to train ML model(s) to identify the probability of infection based on a selfie and their maps time/date stamped maps and image metadata.

ai_facial_engine

Project 2: Rapid High-Volume 3D Printed Ventilator Manufacturing

Leveraging 3D technology to produce life saving ventilators faster, cheaper, and of better quality than traditional manufactering practices.

Medtronic is providing the hardware design specifications and manufacturing instructions, additional ventilator design documents, including manufacturing fixtures, printed circuit board drawings, multiple bills of materials (BOMs), and 3D CAD files. These assets are provided free of charge for third-party development.

The design specifications for the Medtronic PB560 ventilator system and 3D printing technology integration with existing manufacturers, engineers can use these files for the development of a next gen production system.

 

3D printing in the laboratory

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Project 3: Multi Government Level Bid Consolidation Platform

Consolidating supply chain management bidding platform for federal, provincial/state, county, and municipal governments.

The United States is bidding for supplies to fight COVID-19 at all government levels, federal, state, county, and in some cases municipal. Our software stack consolidates redundant bidding into strategic bid tiers that increase likelihood of winning bids that cost less.

How does it work?

All levels of government entering bids sign into one central database enter their current stock, estimated need, and any/all current bids for medical supplies.

County, state, federal governments competing for the same contract to supply from the same vendor have their bids adjusted to compete against foreign governments not against each other. We will employ AI powered Machine Learning models to adjust bids to win using public data (budget meetings for supply and public bid info from competing foreign governments to estimate necessary winning bid value. 

County, state, federal governments competing for the same contract to supply from the same vendor have their bids adjusted to compete against foreign governments not against each other. We will employ AI powered Machine Learning models to adjust bids to win using public data (budget meetings for supply and public bid info from competing foreign governments to estimate necessary winning bid value. Bidding at the federal level will be done so by consolidating all 50 states consisting of 3,141 counties for maximum discount as well as entering bids by each state and each county with appropriate cost to volume bids. (e.g. if the Federal Government bids 50m for a contract that each state bids 1.5m-2m and each county bids 25k-50k so vendors with less supply capacity aren’t ruled out by massive contracts they can’t fill and for vendors who can supply mass quantities appropriate discount is applied for order volume.

6360025 CANADA INC.
dba: covid19star.com

401 Bay Street
16th Floor
Toronto ON M5H 2Y4
Canada

The true soldier fights not because he hates what is in front of him, but because he loves what is behind him. – G.K. Chesterton