| IoT-Based System for Crop Forecasting: Design and Implementation |
| Paper ID : 1149-ICEEM2023 (R2) |
| Authors: |
|
Sayed kenawy *1, Basant Sameh2, Menna Atef3, Tatiana Makarovskikh4, Mostafa Abotaleb5, Valentina Maksimova6, Olga Dernova6 1Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology 2Department of Communications and Electronics Delta Higher Institute of Engineering and Technology, Mansoura, Egypt 3Department of Civil Engineering Delta Higher Institute for Engineering and Technology, Mansoura 35111, Egypt 4Dep. of System Programming South Ural State University Chelyabinsk, Russia 5Department of System Programming South Ural State University, Chelyabinsk 454080, Russia 6Dep. of Information and Analytical Support South Ural State University Chelyabinsk, Russia |
| Abstract: |
| In this paper, we discuss the design of a system for crop forecasting. Despite the presence of a fairly large number of software products for precision farming on the market, many of the existing developments, on the one hand, are not intended to provide data for further analysis by specialists who are not employees of the developer company, and on the other hand, do not ensure food security of the Russian Federation. We have designed a system for the acquisition and subsequent analysis of aerial photographic data. The paper describes the method of presenting data, the process of calculating vegetation indices for a certain date, and provides approaches to modeling the vegetation process using high-quality determinate mathematical models and predicting the yield of a field in the next season, and the cost of this crop. We discuss the opportunities of our system and show the ways of further increasing its quality. |
| Keywords: |
| Forecasting, Mathematical model, Grid search, NDVI, dynamic system, Iot, crops |
| Status : Paper Accepted |
