The IoT and AI in Agriculture: The Time Is Now—A Systematic Review of Smart Sensing Technologies
The integration of the Internet of Things (IoT) and artificial intelligence (AI) has reshaped modern agriculture by enabling precision farming, real-time monitoring, and data-driven decision-making. This systematic review, conducted in accordance with the PRISMA methodology, provides a comprehensive...
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MDPI AG
2025-06-01
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| author | Tymoteusz Miller Grzegorz Mikiciuk Irmina Durlik Małgorzata Mikiciuk Adrianna Łobodzińska Marek Śnieg |
| author_facet | Tymoteusz Miller Grzegorz Mikiciuk Irmina Durlik Małgorzata Mikiciuk Adrianna Łobodzińska Marek Śnieg |
| author_sort | Tymoteusz Miller |
| collection | DOAJ |
| description | The integration of the Internet of Things (IoT) and artificial intelligence (AI) has reshaped modern agriculture by enabling precision farming, real-time monitoring, and data-driven decision-making. This systematic review, conducted in accordance with the PRISMA methodology, provides a comprehensive overview of recent advancements in smart sensing technologies for arable crops and grasslands. We analyzed the peer-reviewed literature published between 2020 and 2024, focusing on the adoption of IoT-based sensor networks and AI-driven analytics across various agricultural applications. The findings reveal a significant increase in research output, particularly in the use of optical, acoustic, electromagnetic, and soil sensors, alongside machine learning models such as SVMs, CNNs, and random forests for optimizing irrigation, fertilization, and pest management strategies. However, this review also identifies critical challenges, including high infrastructure costs, limited interoperability, connectivity constraints in rural areas, and ethical concerns regarding transparency and data privacy. To address these barriers, recent innovations have emphasized the potential of Edge AI for local inference, blockchain systems for decentralized data governance, and autonomous platforms for field-level automation. Moreover, policy interventions are needed to ensure fair data ownership, cybersecurity, and equitable access to smart farming tools, especially in developing regions. This review is the first to systematically examine AI-integrated sensing technologies with an exclusive focus on arable crops and grasslands, offering an in-depth synthesis of both technological progress and real-world implementation gaps. |
| format | Article |
| id | doaj-art-e2aaa219318e453ca02bc7eb80808aae |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
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| spelling | doaj-art-e2aaa219318e453ca02bc7eb80808aae2025-08-20T03:27:43ZengMDPI AGSensors1424-82202025-06-012512358310.3390/s25123583The IoT and AI in Agriculture: The Time Is Now—A Systematic Review of Smart Sensing TechnologiesTymoteusz Miller0Grzegorz Mikiciuk1Irmina Durlik2Małgorzata Mikiciuk3Adrianna Łobodzińska4Marek Śnieg5Institute of Marine and Environmental Sciences, University of Szczecin, Wąska 13, 71-415 Szczecin, PolandDepartment of Horticulture, Faculty of Environmental Management and Agriculture, West Pomeranian University of Technology in Szczecin, Słowackiego 17, 71-434 Szczecin, PolandFaculty of Navigation, Maritime University of Szczecin, Waly Chrobrego 1-2, 70-500 Szczecin, PolandDepartment of Bioengineering, Faculty of Environmental Management and Agriculture, West Pomeranian University of Technology in Szczecin, Słowackiego 17, 71-434 Szczecin, PolandInstitute of Biology, University of Szczecin, 71-415 Szczecin, PolandDepartment of Agroengineering, Faculty of Environmental Management and Agriculture, West Pomeranian University of Technology in Szczecin, Słowackiego 17, 71-434 Szczecin, PolandThe integration of the Internet of Things (IoT) and artificial intelligence (AI) has reshaped modern agriculture by enabling precision farming, real-time monitoring, and data-driven decision-making. This systematic review, conducted in accordance with the PRISMA methodology, provides a comprehensive overview of recent advancements in smart sensing technologies for arable crops and grasslands. We analyzed the peer-reviewed literature published between 2020 and 2024, focusing on the adoption of IoT-based sensor networks and AI-driven analytics across various agricultural applications. The findings reveal a significant increase in research output, particularly in the use of optical, acoustic, electromagnetic, and soil sensors, alongside machine learning models such as SVMs, CNNs, and random forests for optimizing irrigation, fertilization, and pest management strategies. However, this review also identifies critical challenges, including high infrastructure costs, limited interoperability, connectivity constraints in rural areas, and ethical concerns regarding transparency and data privacy. To address these barriers, recent innovations have emphasized the potential of Edge AI for local inference, blockchain systems for decentralized data governance, and autonomous platforms for field-level automation. Moreover, policy interventions are needed to ensure fair data ownership, cybersecurity, and equitable access to smart farming tools, especially in developing regions. This review is the first to systematically examine AI-integrated sensing technologies with an exclusive focus on arable crops and grasslands, offering an in-depth synthesis of both technological progress and real-world implementation gaps.https://www.mdpi.com/1424-8220/25/12/3583artificial intelligenceedge computinginternet of thingsprecision agricultureremote sensingsensor networks |
| spellingShingle | Tymoteusz Miller Grzegorz Mikiciuk Irmina Durlik Małgorzata Mikiciuk Adrianna Łobodzińska Marek Śnieg The IoT and AI in Agriculture: The Time Is Now—A Systematic Review of Smart Sensing Technologies Sensors artificial intelligence edge computing internet of things precision agriculture remote sensing sensor networks |
| title | The IoT and AI in Agriculture: The Time Is Now—A Systematic Review of Smart Sensing Technologies |
| title_full | The IoT and AI in Agriculture: The Time Is Now—A Systematic Review of Smart Sensing Technologies |
| title_fullStr | The IoT and AI in Agriculture: The Time Is Now—A Systematic Review of Smart Sensing Technologies |
| title_full_unstemmed | The IoT and AI in Agriculture: The Time Is Now—A Systematic Review of Smart Sensing Technologies |
| title_short | The IoT and AI in Agriculture: The Time Is Now—A Systematic Review of Smart Sensing Technologies |
| title_sort | iot and ai in agriculture the time is now a systematic review of smart sensing technologies |
| topic | artificial intelligence edge computing internet of things precision agriculture remote sensing sensor networks |
| url | https://www.mdpi.com/1424-8220/25/12/3583 |
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