IoT and Neural Network-Based Water Pumping Control System For Smart Irrigation

Abstract

This article aims at saving the wasted water in the process of irrigation using the Internet of Things (IoT) based on a set of sensors and Multi-Layer Perceptron (MLP) neural network. The developed system handles the sensor data using the Arduino board to control the water pump automatically. The sensors measure the environmental factors; namely temperature, humidity, and soil moisture to estimate the required time for the operation of water irrigation. The water pump control system consists of software and hardware tools such as Arduino Remote XY interface and electronic sensors in the framework of IoT technology. The machine learning algorithm such as the MLP neural network plays an important role to support the decision of automatic control of IoT-based irrigation system, managing the water consumption effectively.

IoT and ML‐based automatic irrigation system for smart agriculture system

“…However, the system needs to analyze the data and disseminate quantitative impact results. Karar et al (2020) used ML algorithms such as MLP neural network to support the decision of automatic control of IoT-based irrigation system to manage the water consumption effectively. This irrigation system supports the farmers to save wasted water, time, and effort to increase the productivity of their crops.…”

“…Keswani et al. (2019) used a self‐contained IoT‐enabled wireless sensor network (WSN) architecture to collect real‐time farm data using multipoint measurements of soil moisture, soil temperature, ambient temperature, and environmental humidity. The anticipated observation strategy includes all freestanding IoT‐enabled WSN nodes used for accurate data collection and archiving of agricultural information.…”

“…The system needs to analyze the data and disseminate quantitative impact results Karar et al (2020) MLP neural network…”

Precision Irrigation Management Using Machine Learning and Digital Farming Solutions

“…When the model's forecast was compared to a state-of-the-art irrigation controller, the volume of water wasted by weather-aware runoff prevention irrigation control (WaRPIC) was only 2.6% that of the state-of-the-art. Also, working toward a water-saving irrigation system, a multilayer perceptron neural network was used to train sensor data collected using IoT to predictively control the duration of pumping of water, and was demonstrated using a laboratory prototype [90].…”