The sector of agriculture has undergone a transformation thanks to the integration of synthetic Artificial intelligence (AI) and The Internet of Things. This has made it conceivable to move towards smart agriculture and promote the evolution of sustainable farming methods. In-depth study of the uses, approaches, difficulties, and potential applications IoT and AI in intelligent agriculture and sustainable farming is offered in this survey report. We examine the several AI approaches that are being used to optimise crop management, resource utilisation, pest control, and environmental condition monitoring. These approaches include machine learning, deep learning, and data analytics, in addition to IoT devices and sensors. We also go over how AI and IoT are helping to make precision agriculture, yield optimization through predictive analytics, and farmer decision support systems possible. We also explore the socio-economic and environmental implications of these technologies, emphasising How they could enhance the quality of meals security, lessen the consequences of climate change, and encourage sustainable farming methods. We also discuss the issues that prevent the mainstream application of AI and IoT technologies in agriculture, such as adoption obstacles, interoperability, scalability, and data privacy concerns. Lastly, we list the future directions for research and the technological developments that is going to be required to fully utilise AI and IoT for smart agriculture and sustainable farming, opening the door to a more resilient and fruitful agricultural ecosystem.

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1. Zuraida Muhammad, Muhammad Azri Asyraf Mohd Hafez, Nor Adni MatLeh, Zakiah Mohd Yusoff , Shabinar Abd Hamid on “Smart Agriculture using Internet of Things with Raspberry Pi”
2. Divya J., Divya M.,Janani V.”IoT based Smart Soil Monitoring System for Agricultural Production” 2017
3. G.C.R.Laksiri, H.A.C.Dharmagunawardhana, J.V.Wijayakulasooriya ”Design and Optimization of loT Based Smart Irrigation System in Sri Lanka”2019
4. Anushree Math, Layak Ali, Pruthviraj U ” Development of Smart Drip Irriga- tion System Using IoT” 2018.
5. Roux, C. Escriba, J. Fourniols, And G. Soto-romero, ‘‘A New Bi-frequency Soil Smart Sensing Moisture And Salinity For Connected Sustainable Agriculture,’’ J. Sensor Technol., Vol. 9, Pp. 4–35, Sep. 2019.
6. Nóbrega, P. Gonçalves, P. Pedreiras, And J. Pereira,‘‘An Iot-based Solution For Intelligent Farming,’’ Sensors, Vol.19, No. 3, P. 603, Jan. 2019.
7. Gai, M. Qiu, H. Zhao, L. Tao, And Z. Zong, ‘‘Dynamic Energy-aware Cloudlet-based Mobile Cloud Computing Model For Green Computing,’’ J. Netw. Comput. Appl., Vol. 59, Pp. 46–54, Jan. 2016.
8. Aminu, A. Sugathakumari and Deepthi Raveendrababu, & Dynamic soil moisture control system for irrigation using GSM & Sustain. Res. Innov. Conf., pp. 122-129, 2018.
9. Arun, K. Lakshmi Sudha “Agricultural Management using Wireless Sensor Networks – A Survey”2nd International Conference on Environment Science and Biotechnology IPCBEE vol.48 (2012) © (2012) IACSIT Press, Singapore 2012.
10. [10] Shrihari M, ”A Smart Wireless System to Automate Production of Crops and Stop Intrusion Using Deep Learning” 2020.

The sector of agriculture has undergone a transformation thanks to the integration of synthetic Artificial intelligence (AI) and The Internet of Things. This has made it conceivable to move towards smart agriculture and promote the evolution of sustainable farming methods. In-depth study of the uses, approaches, difficulties, and potential applications IoT and AI in intelligent agriculture and sustainable farming is offered in this survey report. We examine the several AI approaches that are being used to optimise crop management, resource utilisation, pest control, and environmental condition monitoring. These approaches include machine learning, deep learning, and data analytics, in addition to IoT devices and sensors. We also go over how AI and IoT are helping to make precision agriculture, yield optimization through predictive analytics, and farmer decision support systems possible. We also explore the socio-economic and environmental implications of these technologies, emphasising How they could enhance the quality of meals security, lessen the consequences of climate change, and encourage sustainable farming methods. We also discuss the issues that prevent the mainstream application of AI and IoT technologies in agriculture, such as adoption obstacles, interoperability, scalability, and data privacy concerns. Lastly, we list the future directions for research and the technological developments that is going to be required to fully utilise AI and IoT for smart agriculture and sustainable farming, opening the door to a more resilient and fruitful agricultural ecosystem.

🔒 This is a subscription article

Full text is available to subscribers and institutional members. Please choose an option below to access it.

1. Zuraida Muhammad, Muhammad Azri Asyraf Mohd Hafez, Nor Adni MatLeh, Zakiah Mohd Yusoff , Shabinar Abd Hamid on “Smart Agriculture using Internet of Things with Raspberry Pi”
2. Divya J., Divya M.,Janani V.”IoT based Smart Soil Monitoring System for Agricultural Production” 2017
3. G.C.R.Laksiri, H.A.C.Dharmagunawardhana, J.V.Wijayakulasooriya ”Design and Optimization of loT Based Smart Irrigation System in Sri Lanka”2019
4. Anushree Math, Layak Ali, Pruthviraj U ” Development of Smart Drip Irriga- tion System Using IoT” 2018.
5. Roux, C. Escriba, J. Fourniols, And G. Soto-romero, ‘‘A New Bi-frequency Soil Smart Sensing Moisture And Salinity For Connected Sustainable Agriculture,’’ J. Sensor Technol., Vol. 9, Pp. 4–35, Sep. 2019.
6. Nóbrega, P. Gonçalves, P. Pedreiras, And J. Pereira,‘‘An Iot-based Solution For Intelligent Farming,’’ Sensors, Vol.19, No. 3, P. 603, Jan. 2019.
7. Gai, M. Qiu, H. Zhao, L. Tao, And Z. Zong, ‘‘Dynamic Energy-aware Cloudlet-based Mobile Cloud Computing Model For Green Computing,’’ J. Netw. Comput. Appl., Vol. 59, Pp. 46–54, Jan. 2016.
8. Aminu, A. Sugathakumari and Deepthi Raveendrababu, & Dynamic soil moisture control system for irrigation using GSM & Sustain. Res. Innov. Conf., pp. 122-129, 2018.
9. Arun, K. Lakshmi Sudha “Agricultural Management using Wireless Sensor Networks – A Survey”2nd International Conference on Environment Science and Biotechnology IPCBEE vol.48 (2012) © (2012) IACSIT Press, Singapore 2012.
10. [10] Shrihari M, ”A Smart Wireless System to Automate Production of Crops and Stop Intrusion Using Deep Learning” 2020.