Proceedings of the Second International Conference on Emerging Trends in Engineering (ICETE 2023)

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IoT Based Crop Recommendation System Using Machine Learning for Smart Agriculture

Authors
S. Siva Priyanka1, *, M. Raju2, G. Smitha3, J. Lahari3, G. Akash Reddy3, P. Mani Vinay3
1Department of ECE, CBIT, Gandipet, Hyderabad, India
2Department of ECE, Kakatiya Institute of Technology and Science, Warangal, India
3Department of ECE (Student), Kakatiya Institute of Technology and Science, Warangal, India
*Corresponding author. Email: sivapriyankas_ece@cbit.ac.in
Corresponding Author
S. Siva Priyanka
Available Online 9 November 2023.
DOI
10.2991/978-94-6463-252-1_90How to use a DOI?
Keywords
Crop Recommendation; Machine Learning; Firebase Cloud; Kodular Creator
Abstract

In India, agriculture is one of the most significant sources of income. For the survival of the human race, agriculture is essential. These days, the climatic conditions are unpredictable and irregular, which in turn impacts the agriculture industry a lot more than any other industry. A change in the climatic condition affects the nutrients in the soil, which, therefore, affects the type of crop to be sown for the best result. This paper help farmers for recommending suitable crops to yield based on the input parameters using Machine Learning algorithm. Temperature and humidity are collected through the DHT11 sensor using NodeMCU, and NPK, pH, (are directly fed from soil analysis report) and rainfall values. To make it a farmer-friendly application a mobile application is built using Kodular Creator and it communicates with the Firebase cloud platform. To measure the accuracy for crop recommendation, different performance metrics are evaluated: Precision Score, Recall Score, and F1 Score. The proposed method shows better performance compared to the various other existing methods.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the Second International Conference on Emerging Trends in Engineering (ICETE 2023)
Series
Advances in Engineering Research
Publication Date
9 November 2023
ISBN
978-94-6463-252-1
ISSN
2352-5401
DOI
10.2991/978-94-6463-252-1_90How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - S. Siva Priyanka
AU  - M. Raju
AU  - G. Smitha
AU  - J. Lahari
AU  - G. Akash Reddy
AU  - P. Mani Vinay
PY  - 2023
DA  - 2023/11/09
TI  - IoT Based Crop Recommendation System Using Machine Learning for Smart Agriculture
BT  - Proceedings of the Second International Conference on Emerging Trends in Engineering (ICETE 2023)
PB  - Atlantis Press
SP  - 893
EP  - 904
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-252-1_90
DO  - 10.2991/978-94-6463-252-1_90
ID  - SivaPriyanka2023
ER  -