A Cost Effective IoT-Assisted Framework Coupled with Fog Computing for Smart Agriculture

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Abstract
Organisations must efficiently handle as well as interpret a massive influx of data because of the emergence of technologies like the Internet of Things (IoT) including fog computing. A production strategy known as "smart agriculture" uses technology-enabled knowledge and interaction to monitor fields. Almost 60% of India’s companies, to use an analogy, are agriculturally dependent. Improving existing agronomic systems and transforming them into smart agriculture represents the most efficient approach for dealing with agriculture’s difficulties. The smart agriculture approach provides useful data collecting, incredibly accurate controls, and automated monitoring tech-niques. This study put out a fog-based model with IoT additional support which thus is promising to provide a smart agriculture infrastructure that is widely available. Fog platform includes proper data processing of information produced by IoT gadgets used in connected agriculture by bringing computing and data storage close as possible to the network’s outermost boundaries. The findings suggests the use of the Web of Science database’s literature search for the advancement of the IoT-Fog training sample in the creation of smart agricultural production. When properly implemented and compared to current IoT-based farm systems, the suggested method is more efficient. The outcome indicated that the recommended system enhances the precision of that same existing systems geometrically while reducing system performance, computational efficiency, and statistical significance to substantial levels.

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