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Smart Farming: An Approach for Disease Detection Implementing IoT and Image Processing

Author

Listed:
  • Hui Pang

    (Hebei University of Architecture, China)

  • Zheng Zheng

    (Tangshan Normal University, China)

  • Tongmiao Zhen

    (College of Information Engineering, Hebei University of Architecture, China)

  • Ashutosh Sharma

    (Institute of Computer Technology and Information Security, Southern Federal University, Russia)

Abstract

With the increasing demand on smart agriculture, the effective growth of a plant and increase its productivity are essential. To increase the yield and productivity, monitoring of a plant during its growth till its harvesting is a foremost requirement. In this article, an image processing-based algorithm is developed for the detection and monitoring of diseases in fruits from plantation to harvesting. The concept of artificial neural network is employed to achieve this task. Four diseases of tomato crop have been selected for the study. The proposed system uses two image databases. The first database is used for training of already infected images and second for the implementation of other query images. The weight adjustment for the training database is carried out by concept of back propagation. The experimental results present the classification and mapping of images to their respective categories. The images are categorized as color, texture, and morphology. The morphology gives 93% correct results which is more than the other two features. The designed algorithm is very effective in detecting the spread of disease. The practical implementation of the algorithm has been done using MATLAB.

Suggested Citation

  • Hui Pang & Zheng Zheng & Tongmiao Zhen & Ashutosh Sharma, 2021. "Smart Farming: An Approach for Disease Detection Implementing IoT and Image Processing," International Journal of Agricultural and Environmental Information Systems (IJAEIS), IGI Global, vol. 12(1), pages 55-67, January.
    • Handle: RePEc:igg:jaeis0:v:12:y:2021:i:1:p:55-67
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    Cited by:

    1. Fangsheng Wu & Changan Zhu & Jinxiu Xu & Mohammed Wasim Bhatt & Ashutosh Sharma, 2022. "Research on image text recognition based on canny edge detection algorithm and k-means algorithm," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 72-80, March.
    2. Ashutosh Sharma & Elizaveta Podoplelova & Gleb Shapovalov & Alexey Tselykh & Alexander Tselykh, 2021. "Sustainable Smart Cities: Convergence of Artificial Intelligence and Blockchain," Sustainability, MDPI, vol. 13(23), pages 1-16, November.
    3. Awais Ali & Tajamul Hussain & Noramon Tantashutikun & Nurda Hussain & Giacomo Cocetta, 2023. "Application of Smart Techniques, Internet of Things and Data Mining for Resource Use Efficient and Sustainable Crop Production," Agriculture, MDPI, vol. 13(2), pages 1-22, February.

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