International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Crop Recommendation System Using Machine Learning and IoT for Precision Farming

Abstract

Agriculture is a crucial sector that significantly contributes to the economy of many countries. However, the increasing global population and climate changes have made agricultural productivity more challenging. This paper presents a Crop Recommendation System (CRS) utilizing Machine Learning (ML) and Internet of Things (IoT) technologies to assist farmers in making informed decisions about suitable crops for cultivation. The system uses real-time environmental data, such as soil moisture, temperature, pH levels, and rainfall, to predict the best-suited crops for a given region. Various ML algorithms, including Decision Trees, Random Forest, and Support Vector Machines, are employed to enhance prediction accuracy. IoT-enabled sensors collect real-time data, which is then processed and analyzed to recommend optimal crops. The proposed system aims to improve agricultural yield and sustainability while reducing resource wastage.

Country : India

1 Uday Kumar Kori2 Puligilla Nikitha3 Panthula Lakshmi Gayathri4 Sayali Prabhakar Ingale5 P. Anusha

  1. Student B.Tech, Department of CSE, Guru Nanak Institute of Technology, Hyderabad, Telangana, India
  2. Student B.Tech, Department of CSE, Guru Nanak Institute of Technology, Hyderabad, Telangana, India
  3. Student B.Tech, Department of CSE, Guru Nanak Institute of Technology, Hyderabad, Telangana, India
  4. Student B.Tech, Department of CSE, Guru Nanak Institute of Technology, Hyderabad, Telangana, India
  5. Assistant Professor, Department of CSE, Guru Nanak Institute of Technology, Hyderabad, Telangana, India

IRJIET, Volume 9, Special Issue of INSPIRE’25 April 2025 pp. 141-145

doi.org/10.47001/IRJIET/2025.INSPIRE23

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