Positive-stranded RNA viruses with an envelope make up coronaviruses. The COVID virus has been proposed to be known as severe acute respiratory syndrome coronavirus 2 by the International Council on Taxonomy of Viruses’ Coronavirus Study Group.
Another betacoronavirus, the Middle East respiratory syndrome virus, seems to have less of a connection. Two bat coronaviruses share the most RNA sequence similarity, suggesting that bats are the primary source. The source of the transmission is unknown, though.
Examining the history
Researchers from all across the world are studying the spread of COVID-19 viruses. Cornell University has previously suggested AI-inspired techniques for real-time COVID-19 forecasting to determine its size, duration, and end time across China.
For modelling the epidemics’ transmission dynamics, they modified layered auto-encoded. Using the latent variables in the auto-encoder and clustering methods, they used this mode to forecast COVID-19 cases in real time.
Similarly, AI plays a vital role in the development of prediction models, the discovery of new drugs, the care of the aged, and the detection of viruses in chest X-rays.
An artificial intelligence (AI) model was recently created by researchers at the Central Building Research Institute (CRBI) in Roorkee to forecast the “transmission probability of COVID-19 in a closed space in a building. The open-access scientific journal IEEE Access just released an analysis on the results. “Transmission Probability of SARS-Cov-2 In Office Setting Using Artificial Neural Network” is the title of the document.
Recognizing the variables
The model makes use of an electronic device to measure the temperature, humidity, and carbon dioxide content of a space. These and other input criteria are used to calculate the likelihood that the COVID-19 virus will exist in a closed office, classroom, or other area of a building.
After calculating the parameters, the software calculates the transmission probability and presents the findings as a text alert on the screen. The authors claim that their research is unique.
Using the criteria
The R-value, or estimated number of new infections that originate in each event occuring over a period of time in any space, was predicted by the study using 11 input parameters. The following parameters are listed:
Ambient Temperature (TIn)
Relative humidity in a room (RHIn)
Size of the opening (AO)
number of people inside (O)
Per-person area (AP)
volume per individual (VP)
concentration of CO2 (CO2)
Air-quality rating (AQI)
Outwind velocity (WS)
ambient temperature (TOut)
external humidity (RHOut)
With a cataloguer, the CO2 concentration, temperature, and humidity are recorded. Readings of the AQI and wind speed are provided by other pieces of equipment. Other parameters are manually calculated. In the spring of 2022, the study collected data in real-time for the workplace setting in a naturally ventilated office space under a variety of environmental circumstances.
