Volume 12, Number 13, July 2022

A Big Data Driven System to Improve Residential Irrigation Efficiency using Machine Learning and AI

  Authors

Kai Segimoto¹, Nelly Segimoto¹ and Yu Sun², ¹USA, ²California State Polytechnic University, USA

  Abstract

California has been prone to drought; starting in 2011, there were 376 consecutive weeks of drought [1]. More effective tools are necessary to combat water scarcity, in particular in irrigation systems [3]. This paper designs an application to modify current water-saving techniques to create a more environmentally friendly irrigation system [2]. We developed a Big Data Driven System to Improve Residential Irrigation Efficiency. Our design uses the raspberry Pi controller based on an IoT system with a database connected to the cloud. We designed a mobile app to interact with the system and collect the data and a machine learning algorithm to analyze and generate recommendations based on the given data [4]. We applied our application to the irrigation systems of California Residents and conducted a qualitative evaluation of the approach. The results show that trend-based water saving techniques were effective in reducing water usage without sacrificing the health of the plants being irrigated.

  Keywords

Data mining, Cloud computing, Machine Learning, IoT system.