Published March 30, 2021 | Version v1
Journal article Open

Arduino Based Machine Learning and IoT Smart Irrigation System

  • 1. , Researcher, Robotics, Artificial Intelligence, IoT, USA
  • 2. Professor, Don Bosco Institute of Technology, Bangalore, India.
  • 1. Publisher


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.



Files (315.1 kB)

Name Size Download all
315.1 kB Preview Download

Additional details

Related works

Is cited by
Journal article: 2231-2307 (ISSN)


Retrieval Number