Our project consists of two parts. Our aim is to direct the financial resources of management systems according to Covid 19 data and to determine the health areas for people easily and to direct people to these areas. For this purpose, it is the creation of a web and mobile portal.
While doing these operations, firstly, correlation between this data and Covid 19 will be searched by using the space-based MOPITT (CO data), Temperature, Wind data. There are many existing articles about this correlation process.
However, no definitive conclusion has been reached. The reason for this may be the fact that Covid-19 data is still new. As the world, we are at the beginning of the process.
When creating a model using this space-based data, the "time series prediction" model will be used. In this way, it is aimed to keep our model up to date depending on the time. It is planned to observe whether there is a correlation between the change of these data and the case increases depending on the process. In the portal developed in this direction, investments on carbon emissions in that region will be offered to managers.
For example, these people with high carbon emissions in your area may trigger lung diseases. And Covid can drive his 19 patients to death.
On the other hand, there is a possibility that the propagation speed of Covid 19 may be related to temperature by using various articles.
We want to observe in this correlation with time series prediction and publish some data on our portal.
Another part of the portal is using local management data and satellite-based location data to observe the density of people in that region and whether the area is disinfected or not. targeted to be found safely in environments.
We intend to display this data on the RADARSAT, which contains images from the space taken from the Earth.Data to be used in Project Direction
World CO Data: MOPITT,
World Views: RADARSAT
Our warning system works as follows:
Search on the map or search bar on the region you want to get information about.
-Our model about the region will be revealed on the map
Examples of these alerts are as follows:
Covid-19 cases with air pollution in the region are likely to turn into death
-The temperature in the region may decrease the spreading rate by varying the effectiveness of more saprophytes
-The disinfection process in the region may be dangerous when it was last applied
The density of people in the area is high, so it would be more useful for you to go to this area.
-We are a team aiming for a cleaner air and a world away from global warming. What inspires us as a team in choosing this challenge is our desire to prevent people from misleading. For this purpose, we want to examine the effects of viruses and environmental factors on each other and to solve problems about this.
-When designing the project, we had two approaches. While one is based on more environmental factors, the other is based on local and social factors. While doing this project, our approach was to think that air pollution is at the forefront not only in terms of covid-19 but also in all lung diseases.
-We used the “Measurements Of Pollution In The Troposphere” data, which examined air pollution data due to these lung conditions. We analyzed this data and make the covid 19 data we find with these data predictable using times series prediction.
-We made data analysis in Python. We started the process of creating a model that can update itself over time by passing our data through machine learning algorithms.
-The problems that occur in our team are that the time for model training is insufficient. Due to the insufficient air pollution data, we plan to have interviews within MOPITT and other data.