After the appearance of COVID-19 pandemic. There was an increasing rate of the virus spread without knowing its pattern.
Our project is by using our low cost Biosensor with its fast detection capabilities. It can send data of the positive cases locations in real-time integrated into web map app with NASA SEDAC of population density statistics to visualize and analyze the data on geographical form (e.g Heatmap) to predict the virus spreading pattern
Despite social distance policies and quarantine in Egypt and the world. the number of the positive cases are increasing every single day. more cases means more contact with healthy persons and more and more positive cases...etc , the RT-PCR is the gold standard to detect the Novel Corona Virus but it's complicated, time comsuming and expensive. this a serious problem in the developing countries. this made descision makers in these countries to decrease the number of cases tested every single day. which means more and more silent cases.
Imagine some one who is feeling tired and he was coughinng all night and he decides to go to the hospital. he wears his clothes. taking public transportations, pay money, wait at hospital in contact with other people, do other lab tests and PCR sample with contact with medical staff, the result will take from 1:2 days, he takes another public transport, he goes to grocery store to buy some food for dinner, he waits till tommorow to make the same journy!! and SURPRISE the sample result is POSITIVE !!!
just imagine the number of people he met in only 2 days! and how one person and one day can make a huge diffrence in the spread of the pandemic.
This scenario has inspired us that We want to alter this scenario by making a new detection method that should be easy, rapid, low individual cost and available not only in certain hospitals but every where.
Our approach
Our goal is to make COVID-19 test available everywhere for everyone without harming the others.
Brain storming
we started brain storming and collecting the data we need that could help us to reach our goal. we agree as medical and engnieering students that we can combine biology,chemistry, electronics together to solve the challenge.
Discussion
this step started after collecting enough data. we agreed that we want to make a bio sensor. the sensor will be sensetive for COVID-19 virues only. it will take few minutes to get the result. and to navigate the result to a map
The project steps
1.The Biosensor
it has 2 components
1-Polydiacytelene (PDA) paper is a paper that assemble the cell membrane. It has a unique chromatic properties, It change its colour from blue to red after ligand-antibody interaction due to the transformation that occur upon its side chain.
we add a monoclona antibody specific to COVID-19 spike protein (which is a major protein in all virus variations) to the immobilied PDA paper. When we add a sputum sample from a patient to it, the antigen react with the antibody, causig break of the hydrogen bond of the carboxyl head group, transforming the structure of the paper , causing the blue colour to change into red colour which can be detected by naked eye. (it was tested on other viruses)
2- LDR+LED, as a sensor of the color change of the PDA paper
2. NodeMCU
it works as a loT Dev board ( we used Android IDE for programming) it's connected to internet by the WIFI. it collects 4 information and send them to excel sheet.
-If the IDR detected the color change ( positive sample ) or stayed blue (negative sample).
-GPS coordinants :it will be obtained by 2 ways, by GPS module connected to NodeMCU or by the user own phone while connecting the microcontroller. ( we used GPS module in our prototype).
the GPS coordinates and device serial will be send once at the start of the program. to save an excel row for the device.
-total cases detected by this device
-new cases detected daily with live data update.
What we achieved?
we made simulation for the electronic component on proteus link
(Note: proteus file is attached to github link in code section)
we made a prototype that works effectively Pic-1 , Pic-2 ,Pic-3
Using Google-Maps API to analyse the (test) data and navigate it on a map link
we made an illustrative 3D model of our Biosensor to visualise its components using Blender link
The harware
The software
Programming language
https://drive.google.com/drive/folders/1KUVeC4kHIBUbNcl_SeLUP0fClZpW9ZSQ