Potential of IoT System and Cloud Services for Predicting Agricultural Pests and Diseases

Ntihemuka Materne; Masahiro Inoue

doi:10.1109/TENCONSpring.2018.8691951

Potential of IoT System and Cloud Services for Predicting Agricultural Pests and Diseases

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Controlling the outbreaks of pests and diseases in agricultural environment, it is still a big challenge to the farmers due to the changing climatic conditions. In this paper we are proposing the alternative method of predicting occurrences of pest and diseases in the plantation, by combining the advantage of IoT farmland monitoring system and Amazon Machine Learning cloud-based services to find hidden patterns into data. Logistic regression algorithm used to train our IoT collected dataset and classify the data with acceptable model quality score, to estimate the diseases forecasting based on sensing technology.

Original language	English
Title of host publication	2018 IEEE Region 10 Symposium, Tensymp 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	298-299
Number of pages	2
ISBN (Electronic)	9781538669891
DOIs	https://doi.org/10.1109/TENCONSpring.2018.8691951
Publication status	Published - 2019 Apr 15
Externally published	Yes
Event	2018 IEEE Region 10 Symposium, Tensymp 2018 - Sydney, Australia Duration: 2018 Jul 1 → 2018 Jul 6

Publication series

Name	2018 IEEE Region 10 Symposium, Tensymp 2018

Conference

Conference	2018 IEEE Region 10 Symposium, Tensymp 2018
Country	Australia
City	Sydney
Period	18/7/1 → 18/7/6

Keywords

Agricultural pests and diseases
Cloud services
IoT
Machine learning

ASJC Scopus subject areas

Computer Science Applications
Artificial Intelligence
Computer Networks and Communications
Computer Vision and Pattern Recognition
Energy Engineering and Power Technology
Waste Management and Disposal
Health Informatics

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10.1109/TENCONSpring.2018.8691951

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Cite this

Potential of IoT System and Cloud Services for Predicting Agricultural Pests and Diseases. / Materne, Ntihemuka; Inoue, Masahiro.

2018 IEEE Region 10 Symposium, Tensymp 2018. Institute of Electrical and Electronics Engineers Inc., 2019. p. 298-299 8691951 (2018 IEEE Region 10 Symposium, Tensymp 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Materne, N & Inoue, M 2019, Potential of IoT System and Cloud Services for Predicting Agricultural Pests and Diseases. in 2018 IEEE Region 10 Symposium, Tensymp 2018., 8691951, 2018 IEEE Region 10 Symposium, Tensymp 2018, Institute of Electrical and Electronics Engineers Inc., pp. 298-299, 2018 IEEE Region 10 Symposium, Tensymp 2018, Sydney, Australia, 18/7/1. https://doi.org/10.1109/TENCONSpring.2018.8691951

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