Cost-effective IoT-based intelligent irrigation system

C. S. Anagha, Pranav M. Pawar, P. S. Tamizharasan

Research output: Contribution to journalArticlepeer-review


Agriculture contributes to the growth of human civilization. An adequate amount of water (irrigation) is needed for healthy crops and to increase productivity. Water scarcity is a major problem the world faces, where agriculture consumes a significant portion of freshwater. Many researchers concentrate on imparting intelligence in irrigation systems using machine learning (ML) in recent days. With the emergence of Internet of Things (IoT) technology, devices can communicate with each other. It makes systems like IoT and ML a successful solution for precision agriculture to reduce human intervention in plant irrigation. The paper presented a detailed comparative review of state-of-the-art work in the intelligent automated irrigation system, and contributed the IoT based cost-effective intelligent irrigation system. The developed system uses temperature, soil moisture, humidity, and weather forecast data to take intelligent decisions to automate irrigation using an ML algorithm. The proposed system shows 99.6% accuracy for the accurate prediction of soil moisture as compared with state-of-the-art. The proposed system is also cost-efficient in terms of time (by reducing the time require for training a model), and money (by saving power and human labour requirement).

Original languageEnglish
Pages (from-to)263-274
Number of pages12
JournalInternational Journal of System Assurance Engineering and Management
StatePublished - Mar 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2023, The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden.


  • Agriculture
  • IoT
  • Irrigation system
  • Machine learning


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