Application of Smart Techniques, Internet of Things and Data Mining for Resource Use Efficient and Sustainable Crop Production
Articolo
Data di Pubblicazione:
2023
Citazione:
Application of Smart Techniques, Internet of Things and Data Mining for Resource Use Efficient and Sustainable Crop Production / A. Ali, T. Hussain, N. Tantashutikun, N. Hussain, G. Cocetta. - In: AGRICULTURE. - ISSN 2077-0472. - 13:2(2023), pp. 397.1-397.22. [10.3390/agriculture13020397]
Abstract:
Technological advancements have led to an increased use of the internet of things (IoT) to
enhance the resource use efficiency, productivity, and cost-effectiveness of agricultural production sys-
tems, particularly under the current scenario of climate change. Increasing world population, climate
variations, and propelling demand for the food are the hot discussions these days. Keeping in view
the importance of the abovementioned issues, this manuscript summarizes the modern approaches
of IoT and smart techniques to aid sustainable crop production. The study also demonstrates the
benefits of using modern IoT approaches and smart techniques in the establishment of smart- and
resource-use-efficient farming systems. Modern technology not only aids in sustaining productivity
under limited resources, but also can help in observing climatic variations, monitoring soil nutrients,
water dynamics, supporting data management in farming systems, and assisting in insect, pest, and
disease management. Various type of sensors and computer tools can be utilized in data recording
and management of cropping systems, which ensure an opportunity for timely decisions. Digital
tools and camera-assisted cropping systems can aid producers to monitor their crops remotely. IoT
and smart farming techniques can help to simulate and predict the yield production under forecasted
climatic conditions, and thus assist in decision making for various crop management practices, in-
cluding irrigation, fertilizer, insecticide, and weedicide applications. We found that various neural
networks and simulation models could aid in yield prediction for better decision support with an
average simulation accuracy of up to 92%. Different numerical models and smart irrigation tools
help to save energy use by reducing it up to 8%, whereas advanced irrigation helped in reducing
the cost by 25.34% as compared to soil-moisture-based irrigation system. Several leaf diseases on
various crops can be managed by using image processing techniques using a genetic algorithm with
90% precision accuracy. Establishment of indoor vertical farming systems worldwide, especially
in the countries either lacking the supply of sufficient water for the crops or suffering an intense
urbanization, is ultimately helping to increase yield as well as enhancing the metabolite profile of the
plants. Hence, employing the advanced tools, a modern and smart agricultural farming system could
be used to stabilize and enhance crop productivity by improving resource use efficiency of applied
resources i.e., irrigation water and fertilizers.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
smart farming; sensors; precision farming; yield prediction; IoT; vertical farming
Elenco autori:
A. Ali, T. Hussain, N. Tantashutikun, N. Hussain, G. Cocetta
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