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Mostafa Abotaleb: My PhD candidate in developing Artificial Intelligence and Machine Learning models from South Ural State University, Russia (Direction of Physics and Mathematics). I'm a faculty member in the Computer Science department at South Ural State University. I then became a researcher engineer for Advanced Research in the department of System Programming at the University of South Ural. In 2021, I got a patent from the Russian Federation for developing a library for forecasting COVID-19 infection cases using R programming. I have many publications related to developing deep learning models and classical models to improve the forecast through minimizing the error of forecast. Now I design machine learning algorithms. The connected machine learning algorithms in the drone can perform some advanced tasks. My aim is to discover a learning procedure that is efficient at finding complex structures in large, high-dimensional datasets and to show that this is how the brain learns to see. In addition, I reviewed some research papers in mathematics and deep learning in the top 10% indexed in Scopus.
Smart village. Analysis of the level of development of agricultural crops based on the analysis of images obtained from drones.
The advantage of my idea of using drones for agricultural technology is the lower cost of land development analysis than using expensive satellite imagery, which may not be available to farmers.
The idea of a smart village is proposed, which is based on the use of artificial intelligence methods: the drone establishes a connection with software that allows, based on the analysis of the received images, to classify and explore agricultural land. The purpose of image analysis is to determine the quality of farming in different areas and to determine the reasons for the underdevelopment of crops. An experiment is currently underway to analyze wheat crops. A drone has been designed and developed that flies at an altitude of more than 500 meters, the radius of the drone's flight is more than 11 kilometers. Work is currently underway to develop a more powerful battery for flights longer than 3 hours. Algorithms that use artificial intelligence methods have been added to the developed drone to obtain the most accurate image analysis results for different varieties of wheat.
Today, technology plays a vital role in all areas of human activity. For example, there is progress in the development of agricultural technology, but there is no tool that could determine and predict the effectiveness of plant development on agricultural land and at the same time help the decision maker on the possible import or export of cultivated crops, fertilizers, etc. Therefore, I put forward a new idea of a smart village, thanks to which villages can be combined into a single digital system. The idea is that the farmer will be able to keep track of all the changes, weaknesses and strengths in his field, which will benefit both the farmer and his counterparties. In my project, the analysis of the quality of development of wheat crops is considered. According to the International Grains Council (IGC), wheat remains the world's most important source of food grains for humans. Thus, determining the dynamics of wheat production plays a very important role in ensuring food security.
Description of the problem situation
The problem is that currently there is no technical tool that could help the decision maker on the import and export of the wheat crop, since there is no available information on the productivity of wheat crops, which can lead to some financial problems, as well as problems in the food supply. security. The currently existing method of obtaining information on the yield of agricultural crops from satellite images is quite expensive. There are also traditional methods, such as using sensors to detect defects in crops. But this method is not financially accessible to most farmers. At the heart of my idea is the use of an unmanned aerial vehicle, for which a program has been developed using artificial intelligence algorithms. The UAV, in turn, analyzes the received images of the field, displays all information about the field on the screen of the device, lists the problem areas of the field. Thus, all the information obtained during the survey of the field can help the farmer in increasing crop yields and knowing the shortcomings in the field. This is my first drone model that works in large fields, and can be used not only by farmers, but also by authorities to help make food security decisions.
The development will solve the following tasks:
1. Reducing the efforts of the farmer when searching for problem areas of land.
2. Increasing crop yields.
3. Identification and elimination of shortcomings of agricultural lands.
4. Constant monitoring and control over the state of the land.
5. Achieve food security.
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