Enbat: Automated Farm Monitoring and Controlling System for Sustainable Agriculture
Sarah A. Al-SalahiCollege Student, Computer Science Department, College of Science and Humanities, Imam Abdulrahman Bin Faisal University, Jubail, Saudi Arabia. 2200001151@iau.edu.sa0009-0004-6561-2857
Fatimah J. AlhmoodCollege Student, Computer Science Department, College of Science and Humanities, Imam Abdulrahman Bin Faisal University, Jubail, Saudi Arabia. 2200004124@iau.edu.sa0009-0002-6196-9854
Khaowlah A. ZakariyaCollege Student, Computer Science Department, College of Science and Humanities, Imam Abdulrahman Bin Faisal University, Jubail, Saudi Arabia. 2200002105@iau.edu.sa0009-0008-1803-693X
Sahar A. Al-MuhaishiCollege Student, Computer Science Department, College of Science and Humanities, Imam Abdulrahman Bin Faisal University, Jubail, Saudi Arabia. 2200005060@iau.edu.sa0009-0002-7089-8891
Dr. Thowiba E. AhmedAssistant Professor, Computer Science Department, College of Science and Humanities, Imam Abdulrahman Bin Faisal University, Jubail, Saudi Arabia. teahmed@iau.edu.sa0000-0002-3738-6731
Reem H. Al-ShammariLecturer, Computer Science Department, College of Science and Humanities, Imam Abdulrahman Bin Faisal University, Jubail, Saudi Arabia. ralshammari@iau.edu.sa0000-0001-6444-4178
Dr. Asma A. AlshammariAssistant Professor, Computer Science Department, College of Science and Humanities, Imam Abdulrahman Bin Faisal University, Jubail, Saudi Arabia. ahshammari@iau.edu.sa0009-0009-9156-8593
Dr. Enas E. El-SharawyAssistant Professor, Computer Science Department, College of Science and Humanities, Imam Abdulrahman Bin Faisal University, Jubail, Saudi Arabia. eeelsharawy@iau.edu.sa0000-0002-9826-2900
In modern agriculture, challenges along with aid optimization, climate trade model, and the growing demand for food production require modern solutions. Farmers, in particular those working in arid regions including Saudi Arabia, encounter sizeable demanding situations in identifying suitable water and soil assets for cultivating lots of plants, whilst concurrently striving to put into effect sustainable agricultural practices. This research gives an automated farm tracking and manage gadget that leverages Internet of Things (IoT) generation to deal with these challenges. The proposed device integrates computerized drip irrigation and dynamic sunlight shading to enrich crop productiveness, conserve water sources, and maintain healthful soil situations. By making use of temperature, humidity, and soil moisture sensors, the gadget continuously video displays units environmental situations and triggers automatic responses through an Arduino microcontroller (ESP32). The gathered records from the sensors are compared with predefined database values to optimize irrigation and shading mechanisms in real-time. Additionally, a mobile utility, advanced using Flutter, offers farmers with real-time farm facts, manage capabilities, and more suitable decision-making support. The device was tested through a prototype, demonstrating a 10.45% reduction in water intake and improved plant fitness. Compared to existing IoT-primarily based agricultural solutions, this system uniquely consists of a dynamic shading mechanism to protect crops from excessive heat, a feature not formerly addressed in similar studies. Conclusions indicate that this smart agricultural system can improve work effort, improve accurate agriculture while improving efficiency and stability, making it a promising solution for future sustainable agricultural development.