Arduino based Machine Learning and IoT Smart Irrigation System

Author:

Kanade Prakash1,Prasad Jai Prakash2

Affiliation:

1. Robotics, Artificial Intelligence, IoT, USA.

2. Don Bosco Institute of Technology, Bangalore, India.

Abstract

We all depend on farmers in today's world. But is anybody aware of who the farmers rely on? They don't suffer from various irrigation issues, such as over-irrigation, under irrigation, underwater depletion, floods, etc. We are trying to build a project to solve some of the problems that will help farmers overcome the challenges. Owing to inadequate distribution or lack of control, irrigation happens because of waste water, chemicals, which can contribute to water contamination. Under irrigation, only enough water is provided to the plant, which gives low soil salinity, leading to increased soil salinity with a consequent build-up of toxic salts in areas with high evaporation on the soil surface. This requires either leaching to remove these salts or a drainage system to remove the salts. We have developed a project using IoT (Internet of Things) and ML to solve these irrigation problems (machine learning). The hardware consists of different sensors, such as the temperature sensor, the humidity sensor, the pH sensor, the raspberry pi or Arduino module controlled pressure sensor and the bolt IOT module. Our temperature sensor will predict the area's weather condition, through which farmers will make less use of field water. At a regular interval, our pH sensor can sense the pH of the soil and predict whether or not this soil needs more water. Our main aim is to automatically build an irrigation system and to conserve water for future purposes

Publisher

Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP

Subject

Computer Science Applications,History,Education

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Developing a Hybrid Irrigation System for Smart Agriculture Using IoT Sensors and Machine Learning in Sri Ganganagar, Rajasthan;Journal of Sensors;2024-01-29

2. Intelligent Machine Learning Based Internet of Things (IoT) Resource Allocation;RAiSE-2023;2023-12-19

3. Crop Yield and Soil Moisture Prediction Using Machine Learning Algorithms;Machine Learning Applications;2023-12-11

4. Introduction to ML and IoT for Water Management;Innovations in Machine Learning and IoT for Water Management;2023-11-27

5. Precision Agriculture Using LORA Radar Based SmartIrrigation Monitoring System;2023 IEEE 5th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA);2023-10-07

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