دورية أكاديمية
IoT-Based Cotton Plant Pest Detection and Smart-Response System
| العنوان: | IoT-Based Cotton Plant Pest Detection and Smart-Response System |
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| المؤلفون: | Saeed Azfar, Adnan Nadeem, Kamran Ahsan, Amir Mehmood, Hani Almoamari, Saad Said Alqahtany |
| المصدر: | Applied Sciences, Vol 13, Iss 3, p 1851 (2023) |
| بيانات النشر: | MDPI AG, 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Technology LCC:Engineering (General). Civil engineering (General) LCC:Biology (General) LCC:Physics LCC:Chemistry |
| مصطلحات موضوعية: | IoT-based pest management, sensors, cotton pest detection, smart response system, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999 |
| الوصف: | IoT technology and drones are indeed a step towards modernization. Everything from field monitoring to pest identification is being conducted through these technologies. In this paper, we consider the issue of smart pest detection and management of cotton plants which is an important crop for an agricultural country. We proposed an IoT framework to detect insects through motion detection sensors and then receive an automatic response using drones based targeted spray. In our proposed method, we also explored the use of drones to improve field surveillance and then proposed a predictive algorithm for a pest detection response system using a decision-making theory. To validate the working behavior of our framework, we have included the simulation results of the tested scenarios in the cup-carbon IoT simulator. The purpose of our work is to modernize pest management so that farmers can not only attain higher profits but can also increase the quantity and quality of their crops. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2076-3417 |
| Relation: | https://www.mdpi.com/2076-3417/13/3/1851; https://doaj.org/toc/2076-3417 |
| DOI: | 10.3390/app13031851 |
| URL الوصول: | https://doaj.org/article/aa7db86897ed44499a78fa0f5281fda3 |
| رقم الأكسشن: | edsdoj.7db86897ed44499a78fa0f5281fda3 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 20763417 |
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| DOI: | 10.3390/app13031851 |