Integrating artificial intelligence and Internet of Things (IoT) for enhanced crop monitoring and management in precision agriculture
The integration of Artificial Intelligence (AI) and Internet of Things (IoT) technologies is transforming precision agriculture by enhancing crop monitoring and management. This review explores cutting-edge methodologies and innovations in modern agriculture, including high-throughput phenotyping, r...
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KeAi Communications Co., Ltd.
2024-01-01
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| Series: | Sensors International |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666351124000147 |
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| author | Kushagra Sharma Shiv Kumar Shivandu |
| author_facet | Kushagra Sharma Shiv Kumar Shivandu |
| author_sort | Kushagra Sharma |
| collection | DOAJ |
| description | The integration of Artificial Intelligence (AI) and Internet of Things (IoT) technologies is transforming precision agriculture by enhancing crop monitoring and management. This review explores cutting-edge methodologies and innovations in modern agriculture, including high-throughput phenotyping, remote sensing, and automated agricultural robots (AgroBots). These technologies automate tasks such as harvesting, sorting, and weed detection, significantly reducing labor costs and environmental impacts. High-throughput phenotyping leverages remote sensing, spectral imaging, and robotics to collect data on plant traits, enabling informed decisions on fertilization, irrigation, and pest management. DGPS and remote sensing offer precise, real-time data essential for soil condition assessment and crop health monitoring. Advanced image segmentation techniques ensure accurate detection of plants and fruits, overcoming challenges posed by varying lighting conditions and complex backgrounds. Case studies like the PACMAN SCRI project for apple crop load management and Project PANTHEON's SCADA system for hazelnut orchard management demonstrate the transformative potential of AI and IoT in optimizing agricultural practices. The upcoming integration of 5G and future 6G mobile networks promises to address connectivity challenges, promoting the widespread adoption of smart agricultural practices. However, several research gaps remain. Integrating diverse datasets, ensuring scalability for small and medium-sized farms, and enhancing real-time decision-making need further investigation. Developing robust AI models and IoT devices for varied agricultural conditions, creating user-friendly interfaces for farmers, and addressing privacy and security concerns are essential. Addressing these gaps can enhance the effectiveness and adoption of AI and IoT in precision agriculture, leading to more sustainable and productive farming practices. |
| format | Article |
| id | doaj-art-d57976dae95547acaa162ec8c4783e6a |
| institution | Kabale University |
| issn | 2666-3511 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | KeAi Communications Co., Ltd. |
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| series | Sensors International |
| spelling | doaj-art-d57976dae95547acaa162ec8c4783e6a2025-01-04T04:57:10ZengKeAi Communications Co., Ltd.Sensors International2666-35112024-01-015100292Integrating artificial intelligence and Internet of Things (IoT) for enhanced crop monitoring and management in precision agricultureKushagra Sharma0Shiv Kumar Shivandu1Department of Horticulture (Fruit Science), Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur, Madhya Pradesh, 482004, IndiaDepartment of Horticulture (Fruit Science), College of Horticulture, Dr YS Parmar University of Horticulture and Forestry, Nauni, Solan, Himachal Pradesh, 173230, India; Corresponding author.The integration of Artificial Intelligence (AI) and Internet of Things (IoT) technologies is transforming precision agriculture by enhancing crop monitoring and management. This review explores cutting-edge methodologies and innovations in modern agriculture, including high-throughput phenotyping, remote sensing, and automated agricultural robots (AgroBots). These technologies automate tasks such as harvesting, sorting, and weed detection, significantly reducing labor costs and environmental impacts. High-throughput phenotyping leverages remote sensing, spectral imaging, and robotics to collect data on plant traits, enabling informed decisions on fertilization, irrigation, and pest management. DGPS and remote sensing offer precise, real-time data essential for soil condition assessment and crop health monitoring. Advanced image segmentation techniques ensure accurate detection of plants and fruits, overcoming challenges posed by varying lighting conditions and complex backgrounds. Case studies like the PACMAN SCRI project for apple crop load management and Project PANTHEON's SCADA system for hazelnut orchard management demonstrate the transformative potential of AI and IoT in optimizing agricultural practices. The upcoming integration of 5G and future 6G mobile networks promises to address connectivity challenges, promoting the widespread adoption of smart agricultural practices. However, several research gaps remain. Integrating diverse datasets, ensuring scalability for small and medium-sized farms, and enhancing real-time decision-making need further investigation. Developing robust AI models and IoT devices for varied agricultural conditions, creating user-friendly interfaces for farmers, and addressing privacy and security concerns are essential. Addressing these gaps can enhance the effectiveness and adoption of AI and IoT in precision agriculture, leading to more sustainable and productive farming practices.http://www.sciencedirect.com/science/article/pii/S2666351124000147Precision agricultureArtificial Intelligence (AI)Internet of Things (IoT)Crop monitoringSmart farming |
| spellingShingle | Kushagra Sharma Shiv Kumar Shivandu Integrating artificial intelligence and Internet of Things (IoT) for enhanced crop monitoring and management in precision agriculture Sensors International Precision agriculture Artificial Intelligence (AI) Internet of Things (IoT) Crop monitoring Smart farming |
| title | Integrating artificial intelligence and Internet of Things (IoT) for enhanced crop monitoring and management in precision agriculture |
| title_full | Integrating artificial intelligence and Internet of Things (IoT) for enhanced crop monitoring and management in precision agriculture |
| title_fullStr | Integrating artificial intelligence and Internet of Things (IoT) for enhanced crop monitoring and management in precision agriculture |
| title_full_unstemmed | Integrating artificial intelligence and Internet of Things (IoT) for enhanced crop monitoring and management in precision agriculture |
| title_short | Integrating artificial intelligence and Internet of Things (IoT) for enhanced crop monitoring and management in precision agriculture |
| title_sort | integrating artificial intelligence and internet of things iot for enhanced crop monitoring and management in precision agriculture |
| topic | Precision agriculture Artificial Intelligence (AI) Internet of Things (IoT) Crop monitoring Smart farming |
| url | http://www.sciencedirect.com/science/article/pii/S2666351124000147 |
| work_keys_str_mv | AT kushagrasharma integratingartificialintelligenceandinternetofthingsiotforenhancedcropmonitoringandmanagementinprecisionagriculture AT shivkumarshivandu integratingartificialintelligenceandinternetofthingsiotforenhancedcropmonitoringandmanagementinprecisionagriculture |