Systematic Analysis of Environmental Issues on Ecological Smart Bee Farm by Linear Regression Model

Abstract

Environmental food and nutritional protection primarily depend on pollination from bees. Historically, beekeeping has been performed in different locations as part of the local food community. Beekeeping is increasing rapidly these days due to the high demand for honey and farmers are taking various forms of beekeeping methods to achieve high yield. Honey production also depends on different types of environmental factors. The main principle of this study is to show the analysis results of various types of environmental factors for three different bee farms by the linear regression model to figure out the best farm among all three farms. To improve the production of honey, farmers have to consider different types of environmental factors and this is the elevated time to support farmers by technology. This study analyzed different types of environmental factors like farm outside temperature, farm inside temperature, farm humidity for three different smart bee farms by using a linear regression model to know about their environmental conditions. The performance of prediction models is measured by R 2 error, Root Mean Squared Error (RMSE), Standard Error values (SE), and Mean Absolute Error (MAE). Based on the outcome, it is observed that the best results giving farm is farm 3 that has been able to give R 2 value 0.95,0.95, and 0.72 for the farm outside temperature, inside temperature, and farm humidity.