YOLOv10-Enabled IoT Robot Car for Accurate Disease Detection in Strawberry Cultivation
This study addresses the growing need for effective disease management in strawberry cultivation, a crop vital for global nutrition. We present an innovative approach that combines the YOLOv10 model with a Remote-Controlled Robot Car to revolutionize strawberry disease detection. Our system merges d...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2024-01-01
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| Series: | ITM Web of Conferences |
| Online Access: | https://www.itm-conferences.org/articles/itmconf/pdf/2024/12/itmconf_maih2024_01011.pdf |
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| _version_ | 1841554681917079552 |
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| author | Bellout Abdelaaziz Zarboubi Mohamed Dliou Azzedine Latif Rachid Saddik Amine |
| author_facet | Bellout Abdelaaziz Zarboubi Mohamed Dliou Azzedine Latif Rachid Saddik Amine |
| author_sort | Bellout Abdelaaziz |
| collection | DOAJ |
| description | This study addresses the growing need for effective disease management in strawberry cultivation, a crop vital for global nutrition. We present an innovative approach that combines the YOLOv10 model with a Remote-Controlled Robot Car to revolutionize strawberry disease detection. Our system merges deep learning, IoT, and precision agriculture techniques to enable real-time monitoring of strawberry fields. This technology-driven solution offers a proactive and data-based method for identifying diseases early. Our findings show the potential of this advanced system to significantly improve agricultural practices and support sustainable food production. The YOLOv10n model achieved a 96.78% mAP-50 ratio for accurately locating diseased leaves. By integrating IoT capabilities, the system allows for remote control and continuous monitoring, eliminating the need for daily on-site expert inspections. This approach not only enhances disease management efficiency but also has the potential to increase crop yields and reduce pesticide use, contributing to more sustainable farming practices. |
| format | Article |
| id | doaj-art-0b6c3c8b8a6d439c89c23e0280cfdca0 |
| institution | Kabale University |
| issn | 2271-2097 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | ITM Web of Conferences |
| spelling | doaj-art-0b6c3c8b8a6d439c89c23e0280cfdca02025-01-08T10:58:54ZengEDP SciencesITM Web of Conferences2271-20972024-01-01690101110.1051/itmconf/20246901011itmconf_maih2024_01011YOLOv10-Enabled IoT Robot Car for Accurate Disease Detection in Strawberry CultivationBellout Abdelaaziz0Zarboubi Mohamed1Dliou Azzedine2Latif Rachid3Saddik Amine4LISTI, ENSA, IBN ZOHR UNIVERSITYLISAD, ENSA, IBN ZOHR UNIVERSITYLISTI, ENSA, IBN ZOHR UNIVERSITYLISTI, ENSA, IBN ZOHR UNIVERSITYLISTI, ENSA, IBN ZOHR UNIVERSITYThis study addresses the growing need for effective disease management in strawberry cultivation, a crop vital for global nutrition. We present an innovative approach that combines the YOLOv10 model with a Remote-Controlled Robot Car to revolutionize strawberry disease detection. Our system merges deep learning, IoT, and precision agriculture techniques to enable real-time monitoring of strawberry fields. This technology-driven solution offers a proactive and data-based method for identifying diseases early. Our findings show the potential of this advanced system to significantly improve agricultural practices and support sustainable food production. The YOLOv10n model achieved a 96.78% mAP-50 ratio for accurately locating diseased leaves. By integrating IoT capabilities, the system allows for remote control and continuous monitoring, eliminating the need for daily on-site expert inspections. This approach not only enhances disease management efficiency but also has the potential to increase crop yields and reduce pesticide use, contributing to more sustainable farming practices.https://www.itm-conferences.org/articles/itmconf/pdf/2024/12/itmconf_maih2024_01011.pdf |
| spellingShingle | Bellout Abdelaaziz Zarboubi Mohamed Dliou Azzedine Latif Rachid Saddik Amine YOLOv10-Enabled IoT Robot Car for Accurate Disease Detection in Strawberry Cultivation ITM Web of Conferences |
| title | YOLOv10-Enabled IoT Robot Car for Accurate Disease Detection in Strawberry Cultivation |
| title_full | YOLOv10-Enabled IoT Robot Car for Accurate Disease Detection in Strawberry Cultivation |
| title_fullStr | YOLOv10-Enabled IoT Robot Car for Accurate Disease Detection in Strawberry Cultivation |
| title_full_unstemmed | YOLOv10-Enabled IoT Robot Car for Accurate Disease Detection in Strawberry Cultivation |
| title_short | YOLOv10-Enabled IoT Robot Car for Accurate Disease Detection in Strawberry Cultivation |
| title_sort | yolov10 enabled iot robot car for accurate disease detection in strawberry cultivation |
| url | https://www.itm-conferences.org/articles/itmconf/pdf/2024/12/itmconf_maih2024_01011.pdf |
| work_keys_str_mv | AT belloutabdelaaziz yolov10enablediotrobotcarforaccuratediseasedetectioninstrawberrycultivation AT zarboubimohamed yolov10enablediotrobotcarforaccuratediseasedetectioninstrawberrycultivation AT dliouazzedine yolov10enablediotrobotcarforaccuratediseasedetectioninstrawberrycultivation AT latifrachid yolov10enablediotrobotcarforaccuratediseasedetectioninstrawberrycultivation AT saddikamine yolov10enablediotrobotcarforaccuratediseasedetectioninstrawberrycultivation |