A smart student graduation project to predict plant pests and enhance food security.

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Inauguration of the discussion of innovative industrial graduation projects for students of the sixth batch of the Mechatronics Engineering Department
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The President of the University chairs an expanded meeting at the College of Engineering to follow up on the needs of the educational process
A smart student graduation project to predict plant pests and enhance food security.

A Smart Student Graduation Project to Predict Plant Pests and Enhance Food Security

 

University Media

 

As part of its ongoing pursuit of excellence and innovation in its educational outcomes, the Information Technology Department at the Emirates International University discussed a unique graduation project today, Wednesday, with a strategic dimension in supporting food security and achieving sustainable agricultural development. Titled "Plant Pest Prediction Project," the project was implemented within the university's Information Technology Department by students Hashem Al Kahli and Khaled Al Khawlani, under the supervision of Prof. Ahmed Sultan Al Hajami and Dr. Muhannad Al Mashriqi. The discussion committee consisted of Dr. Mohammed Al Khawlani, Dr. Hisham Aqlan, Engineer Zaid Al Washli, and Engineer Azza Al Harthi.

 

The project represents a qualitative leap in the use of artificial intelligence and cloud computing technologies to serve the agricultural sector. It aims to develop a smart system capable of predicting and detecting plant diseases, either as early as 48 hours, or at later stages, depending on the severity of the infection. This enables farmers and relevant authorities to intervene quickly and make appropriate decisions to reduce losses and enhance production.

 

 The system collects and analyzes data using two innovative methods: inputting raw digital data based on area, plant type, and geographic location; and capturing plant images using automated cameras, which are later analyzed using computer vision techniques.

 

The system is also connected to cloud computing, allowing users to access and analyze data anytime, anywhere, while continuously storing and processing information. The system allows any user to contribute to training the AI model through a simple interactive interface, by entering data about a specific plant or images showing signs of infestation. When a new plant species is introduced, the system automatically expands its database.

 

Most importantly, the system transforms live data from sensors into strategic insights that aid in making preventative decisions, contributing to the prevention of agricultural pests before they occur and enhancing the sustainability and efficiency of agriculture.

 

 This project reflects the excellence of the Emirates International University in empowering its students to produce advanced digital solutions directly related to real-world challenges. It embodies the integration of academic and societal aspects in the university's vision to prepare graduates capable of making a tangible impact on the future of vital sectors.

 

Website:

https://eiu.edu.ye

 

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