Authors

Kirollos Amir, Mahmoud Heidar,Waleed Wagdy, Yara Negm

Dr. Taraggy Mohey, Eng. Randa Osama

Publishing Date

12-November-2020

Abstract

Agriculture is one of the most important sectors in Egypt, although environmental factors affects the crops’ life cycle. Many diseases severity depends on the weather climate changes. Integrating technology with agriculture is a big challenge yet an important approach for the evolution of the agriculture sector. We aim to build a system that collects data from weather station, this data help in measuring weather impacts on crops and fungicides. This data is used in three models: The first model is an IOT model that recommends the fungicide to be applied on crops with the exact dosage percentage taking in consideration any corrective action beside the time to use it based on weather API. The second model is a fuzzy inference model that predicts the severity of diseases in crops based on weather station. The third model to be built at the end of the project is an ANN model that predicts some diseases in some crops based on dataset collected from the weather station and the user during the project period.

1.1 Background

Agriculture is one of the most important economic, social and environmental activities of humans. Agriculture is the backbone of a given country’s economic system in addition to providing food and raw materials. Agriculture also provides job opportunities for a very large percentage of the population. Almost 70% of people depend directly on agriculture as a means of livelihood .However, disease is a major source that can harm crops and plants. Diseases often have a major economic impact on yield and quality, so disease management is very important to crop production.

1.2 Motivation

Farmers began to face the problem of plants and crops being affected by numerous diseases due to climate change. The crop must be monitored every day or else the disease will expand and eventually kill all crops. This problem can be solved by providing an Iot model that predicts the timing of the disease with appropriate timing for Fungicide or Insecticide. Based on weather station readings and experiments, we aim to build an AI model that predicts diseases that may affect crops such as wheat and corn. The motivation for our work was the earlier work of Sassenrath, Varney and Lulato cite {sassenrath2019impact}, in which the they presented the climatic impact of the fungicides and pesticides used to produce wheat in an extremely rainy environment. Stefanello et.al cite {stefanello2016effect}, presented the effect of the interaction between fungicide spray time and rain interval to simulate precipitation on controlling the efficacy of Asian soybean rust.

1.3 Problem Statement

Farmers face the problem of plants and crops being affected by many diseases due to climate change. Also, in the process of healing crops with fungicides , the crop does not take the full concentration dose of treatment due to climate factors.

Our aim is :

Build a system that collects data from the weather station.

Create a fuzzy inference model that predicts the severity of disease in crops based on the weather station.

Building an IOT model that recommends the use of fungicides on crops in an accurate dose ratio.

Building an AI model that predicts some diseases in some crops based on a dataset collected from the weather station.