AI-IoT based smart agriculture pivot for plant diseases detection and treatment
Abstract There are some key problems faced in modern agriculture that IoT-based smart farming. These problems such shortage of water, plant diseases, and pest attacks. Thus, artificial intelligence (AI) technology cooperates with the Internet of Things (IoT) toward developing the agriculture use cas...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-05-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-98454-6 |
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| author | Amin S. Ibrahim Saeed Mohsen I. M. Selim Roobaea Alroobaea Majed Alsafyani Abdullah M. Baqasah Mohamed Eassa |
| author_facet | Amin S. Ibrahim Saeed Mohsen I. M. Selim Roobaea Alroobaea Majed Alsafyani Abdullah M. Baqasah Mohamed Eassa |
| author_sort | Amin S. Ibrahim |
| collection | DOAJ |
| description | Abstract There are some key problems faced in modern agriculture that IoT-based smart farming. These problems such shortage of water, plant diseases, and pest attacks. Thus, artificial intelligence (AI) technology cooperates with the Internet of Things (IoT) toward developing the agriculture use cases and transforming the agriculture industry into robustness and ecologically conscious. Various IoT smart agriculture techniques are escalated in this field to solve these challenges such as drop irrigation, plant diseases detection, and pest detection. Several agriculture devices were installed to perform these techniques on the agriculture field such as drones and robotics but in expense of their limitations. This paper proposes an AI-IoT smart agriculture pivot as a good candidate for the plant diseases detection and treatment without the limitations of both drones and robotics. Thus, it presents a new IoT system architecture and a hardware pilot based on the existing central pivot to develop deep learning (DL) models for plant diseases detection across multiple crops and controlling their actuators for the plant diseases treatment. For the plant diseases detection, the paper augments a dataset of 25,940 images to classify 11-classes of plant leaves using a pre-trained ResNet50 model, which scores the testing accuracy of 99.8%, compared to other traditional works. Experimentally, the F1-score, Recall, and Precision, for ResNet50 model were 99.91%, 99.92%, and 100%, respectively. |
| format | Article |
| id | doaj-art-cd724e490931460b8fcda744036fcabf |
| institution | OA Journals |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-cd724e490931460b8fcda744036fcabf2025-08-20T02:31:58ZengNature PortfolioScientific Reports2045-23222025-05-0115111610.1038/s41598-025-98454-6AI-IoT based smart agriculture pivot for plant diseases detection and treatmentAmin S. Ibrahim0Saeed Mohsen1I. M. Selim2Roobaea Alroobaea3Majed Alsafyani4Abdullah M. Baqasah5Mohamed Eassa6Electronics and Communication Department, Faculty of Engineering, Ahram Canidian University (ACU)Department of Electronics and Communications Engineering, Al-Madinah Higher Institute for Engineering and TechnologyFaculty of Computer and Artificial Intelligence, Sadat City UniversityDepartment of Computer Science, College of Computers and Information Technology, Taif UniversityDepartment of Computer Science, College of Computers and Information Technology, Taif UniversityDepartment of Information Technology, College of Computers and Information Technology, Taif UniversityDepartment of Computer Science, Faculty of Information Systems and Computer Science, October 6 UniversityAbstract There are some key problems faced in modern agriculture that IoT-based smart farming. These problems such shortage of water, plant diseases, and pest attacks. Thus, artificial intelligence (AI) technology cooperates with the Internet of Things (IoT) toward developing the agriculture use cases and transforming the agriculture industry into robustness and ecologically conscious. Various IoT smart agriculture techniques are escalated in this field to solve these challenges such as drop irrigation, plant diseases detection, and pest detection. Several agriculture devices were installed to perform these techniques on the agriculture field such as drones and robotics but in expense of their limitations. This paper proposes an AI-IoT smart agriculture pivot as a good candidate for the plant diseases detection and treatment without the limitations of both drones and robotics. Thus, it presents a new IoT system architecture and a hardware pilot based on the existing central pivot to develop deep learning (DL) models for plant diseases detection across multiple crops and controlling their actuators for the plant diseases treatment. For the plant diseases detection, the paper augments a dataset of 25,940 images to classify 11-classes of plant leaves using a pre-trained ResNet50 model, which scores the testing accuracy of 99.8%, compared to other traditional works. Experimentally, the F1-score, Recall, and Precision, for ResNet50 model were 99.91%, 99.92%, and 100%, respectively.https://doi.org/10.1038/s41598-025-98454-6Artificial intelligence (AI)Internet of Things (IoT)Smart agricultureUnmanned aerial vehicle (UAV)PivotPlant diseases detection |
| spellingShingle | Amin S. Ibrahim Saeed Mohsen I. M. Selim Roobaea Alroobaea Majed Alsafyani Abdullah M. Baqasah Mohamed Eassa AI-IoT based smart agriculture pivot for plant diseases detection and treatment Scientific Reports Artificial intelligence (AI) Internet of Things (IoT) Smart agriculture Unmanned aerial vehicle (UAV) Pivot Plant diseases detection |
| title | AI-IoT based smart agriculture pivot for plant diseases detection and treatment |
| title_full | AI-IoT based smart agriculture pivot for plant diseases detection and treatment |
| title_fullStr | AI-IoT based smart agriculture pivot for plant diseases detection and treatment |
| title_full_unstemmed | AI-IoT based smart agriculture pivot for plant diseases detection and treatment |
| title_short | AI-IoT based smart agriculture pivot for plant diseases detection and treatment |
| title_sort | ai iot based smart agriculture pivot for plant diseases detection and treatment |
| topic | Artificial intelligence (AI) Internet of Things (IoT) Smart agriculture Unmanned aerial vehicle (UAV) Pivot Plant diseases detection |
| url | https://doi.org/10.1038/s41598-025-98454-6 |
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