Newton Backward Difference Application for Automating Fertilizer Distribution in Agriculture using Wireless Sensor Networks

Abstract

Background: The Indian economy and population have been largely influenced by the green revolution which has caused a big change in India. Yet farmers are not able to make full-blown usage of technology to improve crop cultivation. As Indian economy and per capita income, in trade terms, CAPEX (Capital Expenses); is based on agro products, to rejuvenate the demand-supply chain of the food sector, farmers are using fertilizers to increase yield. Due to the excessive use of these puissance fertilizers, soil fertility is adversely impacted. It is hazardous for direct consumption by people. The current study was aimed to optimize the use of fertilizer as per crop requirement using Newton backward difference (NBD) method. Methods: The experiment was conducted for the last three years (2017-2020) in the Agrotech farm of MIT Academy of Engineering, Pune. The tomato crop was used for taking the readings. Using the NBD, we compared the values between standard, conventional and actual which gives the optimized value and saves the wastage of fertilizer and farmers’ burden economically. These NBD can lead to a reduction in the number of sensor nodes in the farm field. The reduction in sensor nodes saves the overall working cost. Result: The implemented system saves the quantity of nitrogen (N), phosphorus (P) and potassium (K) only by providing the required amount of fertilizer to the crop in comparison with a conventional approach.

A Lagrange Interpolation Application for Automating Fertilizer Distribution in Agriculture using Wireless Sensor Networks

“…We can optimize the use of fertilizer in the farm using the Newton Backward Difference (NBD) which reduced working cost and economic burden on the farmers (Warpe et al 2022). The implemented system demonstrates that how Newton Forward Difference (NFD) approach saves the quantity of N/P/K with the aid of imparting required value to the crop in assessment with the traditional method (Warpe et al 2020).…”