AUTHORS:
Dina Alshaibi Electrical-Computer Engineering, King Abdulaziz University, Jeddah, Saudi Arabia
Hind Alrashed Electrical-Computer Engineering, King Abdulaziz University, Jeddah, Saudi Arabia
Marwah Bakoor Electrical-Computer Engineering, King Abdulaziz University, Jeddah, Saudi Arabia
Dr.Thangam Palaniswamy Electrical-Computer Engineering, King Abdulaziz University, Jeddah, Saudi Arabia

ABSTRACT:
Agriculture has been present for many years; it has a long history and continues to be a major source of income and food to this day. However, the production process of the plant is difficult for people who do not have much experience in gardening. Therefore, this project aims to facilitate the cultivation process for home gardeners as a practical and easy-to-use solution. Soil moisture, air temperature, humidity, and soil salinity readings are used by the system to adjust the tomato’s environment. The system should monitor the tomato’s condition through sensors and make amendments to preserve those conditions, as well as detect tomato diseases through a deep learning model and cure them with the system if possible. All this will be facilitated by a mobile application. To implement the project, the following methods will be utilized: an SDI as the irrigation method, Wi-Fi as the type of communication, TensorFlow as the deep learning framework with transfer learning, and flutter for the app development.

Keywords: Proportional Integral Derivative (PID), Swarm Intelligence (SI), Renewable Energy (RE), Statistical Analysis

Conference Venue: Mövenpick Hotel & Apartments Bur Dubai, Dubai-UAE
Conference Date: 29-30 April 2023

ISBN Number: 978-625-00-1526-1
DOI Number: https://doi.org/10.53375/icmame.2023.120


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