Telesto.x| Automated Detection of Hazards
Automated Detection of Hazards
Agriculture at home
Summary
The idea we found for the competition is to enable people to farm in the most efficient way with less cost, and the reason for this is that people stay at home and look for a useful occupation due to Covid-19, and we, as a team, came up with the idea of home agriculture and we supported it with artificial intelligence algorithms.
How We Addressed This Challenge
The biggest factor that allowed us to overcome the project is that we trust this idea and we think that it will be a beneficial work for humanity, we have been motivated to this very much. The biggest target group in our project was that people who want to farm at home were doing it at the lowest cost and in an optimized way. Covid-19 pandemic was the biggest factor in the formation of this idea. The project is actually an artificial intelligence project. We realized the weather forecast of Istanbul with artificial neural networks.
How We Developed This Project
The biggest reason for joining this challenge with my teammate is to show myself internationally.
We can say that there is a Covid-19 pandemic. We used intelligence neural networks while developing our project. We trained it with eight optimization algorithms to find the right data with this neural network model. The performance of the models was evaluated with appropriate methods. We used the correlation coefficient and R-square statistics to determine the exam of the models. We obtained the data sets used in the project from the Istanbul Provincial Meteorology System. We found that the recommended model obtained better results than the algorithms in the literature. We also used Matlab in the project.
How We Used Space Agency Data in This Project
Istanbul provincial Meteorology and Meteomaticsin data.
Project Demo
https://drive.google.com/file/d/1KCvVfv9reuJZQi4ThhHl__qKRW4A0yzO/view?usp=sharing
Data & Resources
Istanbul provincial Meteorology and Meteomaticsin data