Distributed and Analogous simulation framework for the control of pests and diseases in plants using IoT Technology
In contemporary society, agriculture is progressively embracing technological innovations called Precision Agriculture. The utilization of various pest control and disease management strategies is of considerable importance in the surveillance of plants. The current framework encounters multiple cha...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2024-01-01
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| Series: | BIO Web of Conferences |
| Online Access: | https://www.bio-conferences.org/articles/bioconf/pdf/2024/01/bioconf_msnbas2024_05017.pdf |
| _version_ | 1797353069056360448 |
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| author | Dashand Sushree Sasmita Kumar Pawan |
| author_facet | Dashand Sushree Sasmita Kumar Pawan |
| author_sort | Dashand Sushree Sasmita |
| collection | DOAJ |
| description | In contemporary society, agriculture is progressively embracing technological innovations called Precision Agriculture. The utilization of various pest control and disease management strategies is of considerable importance in the surveillance of plants. The current framework encounters multiple challenges. The pest control and disease surveillance system employs a solitary Graphical Processing Unit (GPU) to manage the diverse array of connected sensors. Hence, this paper proposes utilizing the Distributed and Analogous Simulation Framework (DASF) in conjunction with the Internet of Things (IoT) to address the issue of pest control and diseases in plants. The approach reduces the strain on a specific GPU, effectively allocates the computational tasks across all accessible GPUs concurrently, and ensures continuous data transmission to the dashboards even in the event of GPU malfunction. The implementation of this procedure is anticipated to result in a reduction in overall system performance. In the DASF multi-threading framework, the allocation of tasks to particular auxiliary cores is performed by each GPU unit. The execution of the different functions within this system is allocated among four levels: disease management, pest recognition and control, output operations, and input functions. The data is analyzed concurrently and managed in a proficient and regulated manner. The proposed system demonstrates a significant enhancement in performance measures, with a value of 99.05%. |
| first_indexed | 2024-03-08T13:25:52Z |
| format | Article |
| id | doaj.art-b8174fd699384a0db23e93ab3a233922 |
| institution | Directory Open Access Journal |
| issn | 2117-4458 |
| language | English |
| last_indexed | 2024-03-08T13:25:52Z |
| publishDate | 2024-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | BIO Web of Conferences |
| spelling | doaj.art-b8174fd699384a0db23e93ab3a2339222024-01-17T14:58:26ZengEDP SciencesBIO Web of Conferences2117-44582024-01-01820501710.1051/bioconf/20248205017bioconf_msnbas2024_05017Distributed and Analogous simulation framework for the control of pests and diseases in plants using IoT TechnologyDashand Sushree Sasmita0Kumar Pawan1Faculty of CS & IT, Kalinga UniversityFaculty of CS & IT, Kalinga UniversityIn contemporary society, agriculture is progressively embracing technological innovations called Precision Agriculture. The utilization of various pest control and disease management strategies is of considerable importance in the surveillance of plants. The current framework encounters multiple challenges. The pest control and disease surveillance system employs a solitary Graphical Processing Unit (GPU) to manage the diverse array of connected sensors. Hence, this paper proposes utilizing the Distributed and Analogous Simulation Framework (DASF) in conjunction with the Internet of Things (IoT) to address the issue of pest control and diseases in plants. The approach reduces the strain on a specific GPU, effectively allocates the computational tasks across all accessible GPUs concurrently, and ensures continuous data transmission to the dashboards even in the event of GPU malfunction. The implementation of this procedure is anticipated to result in a reduction in overall system performance. In the DASF multi-threading framework, the allocation of tasks to particular auxiliary cores is performed by each GPU unit. The execution of the different functions within this system is allocated among four levels: disease management, pest recognition and control, output operations, and input functions. The data is analyzed concurrently and managed in a proficient and regulated manner. The proposed system demonstrates a significant enhancement in performance measures, with a value of 99.05%.https://www.bio-conferences.org/articles/bioconf/pdf/2024/01/bioconf_msnbas2024_05017.pdf |
| spellingShingle | Dashand Sushree Sasmita Kumar Pawan Distributed and Analogous simulation framework for the control of pests and diseases in plants using IoT Technology BIO Web of Conferences |
| title | Distributed and Analogous simulation framework for the control of pests and diseases in plants using IoT Technology |
| title_full | Distributed and Analogous simulation framework for the control of pests and diseases in plants using IoT Technology |
| title_fullStr | Distributed and Analogous simulation framework for the control of pests and diseases in plants using IoT Technology |
| title_full_unstemmed | Distributed and Analogous simulation framework for the control of pests and diseases in plants using IoT Technology |
| title_short | Distributed and Analogous simulation framework for the control of pests and diseases in plants using IoT Technology |
| title_sort | distributed and analogous simulation framework for the control of pests and diseases in plants using iot technology |
| url | https://www.bio-conferences.org/articles/bioconf/pdf/2024/01/bioconf_msnbas2024_05017.pdf |
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