Abstract
With the growth of the human population comes the constantly rising demand for agricultural products. Nevertheless, as the world experiences climate change, many crops are often damaged by weather conditions.This study utilizes Intelligent Agriculture IoT equipment to monitor the environmental factors on a farm. The collected data underwent 3D cluster analysis to yield analysis of the environmental factors of that farm. The proposed scheme bears the following features: (1) data normalization is achieved via the combination of moving average and average variance; (2) we applied 3D cluster analysis to analyze the relation between environmental factors and subsequently examine the rules of thumb held by the farmers; (3) the system determines whether a selected crop has been placed in the appropriate cluster; and (4) the system sets a critical value in the cluster based on future environments and provides advice on whether a crop is suitable for the farm. We placed Intelligent Agriculture IoT equipment in the farm for monitoring purposes and ran an actual-scenario analysis using the algorithm in our study; results confirm that our proposed scheme is indeed feasible.
Highlights
With the growth of the human population comes the constantly rising demand for agricultural products
This study proposes big data analysis of farms based on Intelligent Agriculture
Our proposed big data analysis approach includes the following concepts: (1) data normalization via the combination of moving average and average variance; (2) application of 3D cluster analysis to analyze the relation between different environmental factors and subsequently examine the rules of thumb held by the farmers; (3) determination of whether a selected crop has been placed in the appropriate cluster; and (4) setting a critical value in the cluster based on future environments and providing advice on whether a crop is suitable for the farm
Summary
With the growth of the human population comes the constantly rising demand for agricultural products. We must utilize the Internet of Things and big data to analyze farm soil and environment in order to provide farmers with suitable crop options and keep track of their cultivation techniques as well as environmental factors at their farms. Our proposed big data analysis approach includes the following concepts: (1) data normalization via the combination of moving average and average variance; (2) application of 3D cluster analysis to analyze the relation between different environmental factors and subsequently examine the rules of thumb held by the farmers; (3) determination of whether a selected crop has been placed in the appropriate cluster; and (4) setting a critical value in the cluster based on future environments and providing advice on whether a crop is suitable for the farm. Our proposed big data analysis method has undergone simulation and helped analyze whether the locally grown crop is a suitable choice; experiment results show that the proposed scheme is feasible and helps farmers understand their farm environmental through the environmental indices of their farms
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