Abstract
With the implementation of the Internet of Things, the agricultural domain has become data-driven, allowing for well-timed and cost-effective farm management while remaining environmentally sustainable. Thus, the incorporation of Internet of Things in the agricultural domain is the need of the hour for developing countries whose gross domestic product primarily depends on the farming sector. It is worth highlighting that developing nations lack the infrastructure for precision agriculture; therefore, it has become necessary to come up with a methodological paradigm which can accommodate a complete model to connect ground sensors to the compute nodes in a cost-effective way by keeping the data processing limitations and constraints in consideration. In this regard, this review puts forward an overview of the state-of-the-art technologies deployed in precision agriculture for soil assessment and pollutant monitoring with respect to heavy metal in agricultural soil using various sensors. Secondly, this manuscript illustrates the processing of data generated from the sensors. In this regard, an optimized method of data processing derived from cloud computing has been shown, which is called edge computing. In addition to this, a new model of high-performance-based edge computing is also shown for efficient offloading of data with smooth workflow optimization. In a nutshell, this manuscript aims to open a new corridor for the farming sector in developing nations by tackling challenges and providing substantial consideration.
Highlights
The agricultural sector in developing countries has multiple challenges, i.e., if we look at the production side, the first challenge which the farmer faces is the productivity challenge, as it becomes evident that developing countries are very low in productivity, i.e., for any crop, the particular developing country could be the highest producer but at the same time its productivity could be very low
The scope of the current paper is to introduce and pave the way for smart sensing with edge computing technology in the developing nations, whose gross domestic product relies substantially on agriculture
Prototypes of edge computing systems have already been developed by many researchers for specific agricultural domains; the interpretability of edge computing techniques with various sensing units still remains a challenge
Summary
The agricultural sector in developing countries has multiple challenges, i.e., if we look at the production side, the first challenge which the farmer faces is the productivity challenge, as it becomes evident that developing countries are very low in productivity, i.e., for any crop, the particular developing country could be the highest producer but at the same time its productivity could be very low. The second challenge which the farmer faces is with respect to climate change, industrial pollution, and pest attacks, as they can damage crops substantially. From the economic perspective of the developing country, it is a boon if more facility in nature and regulatory support has to be given for people who are looking to export outside their country or who are looking to have a value-added product across the globe. This mismanagement in the agricultural sector can potentially lead to food security risk.
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