Intelligent Orchard monitoring: IoT integrated Fuzzy Logic based real-time apple disease prediction encompassing environmental factors

Orchid disease prediction using IoT

Authors

  • Karuna Sheel Lovely Professional University
  • Anil Sharma Lovely Professional University

DOI:

https://doi.org/10.62110/sciencein.jist.2024.v12.795

Keywords:

Internet of Things (IoT), Apple Disease Detection, Environmental Factors, Fuzzy Logic, Real-time Monitoring

Abstract

This work presents a novel methodology for apple disease detection based on environmental factors, integrating the capabilities of the Internet of Things (IoT). Advanced sensors are placed in apple orchards to continuously monitor various environmental factors such as temperature, humidity, pressure, and light. The data gathered from these sensors is analyzed using the Mamdani fuzzy inference system (MFIS) to predict possible apple diseases. The use of advanced sensors, cloud storage, and the Mamdani fuzzy inference system proved effective in timely disease detection along with inclusion of environmental factors. According to predicted outcomes, a recommendation system is also presented in the mobile application. Initial experiments in Shimla, India, showed that this system is effective and efficient, with minimal delays in different stages. The study also compares this new approach with current advanced methods in disease detection.

URN:NBN:sciencein.jist.2024.v12.795

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Author Biographies

  • Karuna Sheel, Lovely Professional University

    School of Computer Science and Engineering

  • Anil Sharma, Lovely Professional University

    School of Computer Science and Engineering

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Published

2024-01-20

Issue

Section

Computer Sciences and Mathematics

URN

How to Cite

Sheel, K., & Sharma, A. (2024). Intelligent Orchard monitoring: IoT integrated Fuzzy Logic based real-time apple disease prediction encompassing environmental factors. Journal of Integrated Science and Technology, 12(4), 795. https://doi.org/10.62110/sciencein.jist.2024.v12.795

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