Applying Big Data for Intelligent Agriculture-Based Crop Selection Analysis

• Main Authors: Fan-Hsun Tseng, Hsin-Hung Cho, Hsin-Te Wu
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Access
• Subjects: Big data; intelligent agriculture; internet of things; agricultural engineering; data mining
• Online Access: https://ieeexplore.ieee.org/document/8801889/

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.