An Intelligent Greenhouse Monitoring Framework for Automated Mushroom Cultivatiom

  • Unique Paper ID: 210162
  • Volume: 13
  • Issue: 6
  • PageNo: 26-30
  • Abstract:
  • Mushroom cultivation requires careful monitoring of environmental conditions and growth stages to maintain crop quality and productivity. Traditional cultivation practices often depend on manual observation, which can delay the identification of abnormal conditions and make cultivation management difficult. This paper presents an intelligent greenhouse monitoring framework for mushroom cultivation that combines artificial intelligence (AI), image-based analysis, environmental condition assessment, and cultivation guidance. The proposed framework includes mushroom image uploading and analysis, growth-stage identification, crop health assessment, a climate simulation module, a mushroom species library, cultivation history, and an AI-based assistance interface. The system provides stage-dependent cultivation recommendations and supports the monitoring of parameters such as temperature, relative humidity, light intensity, and carbon dioxide concentration. The software framework is designed to support future integration with Internet of Things (IoT) sensors and automated environmental control devices. The proposed approach aims to improve the accessibility of cultivation information and support informed decisions during mushroom production. Its practical effectiveness must be established through systematic testing using representative mushroom images, environmental measurements, and cultivation trials.

Copyright & License

Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{210162,
        author = {Poojitha J and Pradeepika M and Priyanka S and Selva Kiruthika U and Soniya Lakshmi K and Anandhi B},
        title = {An Intelligent Greenhouse Monitoring Framework for Automated Mushroom Cultivatiom},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {6},
        pages = {26-30},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=210162},
        abstract = {Mushroom cultivation requires careful monitoring of environmental conditions and growth stages to maintain crop quality and productivity. Traditional cultivation practices often depend on manual observation, which can delay the identification of abnormal conditions and make cultivation management difficult. This paper presents an intelligent greenhouse monitoring framework for mushroom cultivation that combines artificial intelligence (AI), image-based analysis, environmental condition assessment, and cultivation guidance. The proposed framework includes mushroom image uploading and analysis, growth-stage identification, crop health assessment, a climate simulation module, a mushroom species library, cultivation history, and an AI-based assistance interface. The system provides stage-dependent cultivation recommendations and supports the monitoring of parameters such as temperature, relative humidity, light intensity, and carbon dioxide concentration. The software framework is designed to support future integration with Internet of Things (IoT) sensors and automated environmental control devices. The proposed approach aims to improve the accessibility of cultivation information and support informed decisions during mushroom production. Its practical effectiveness must be established through systematic testing using representative mushroom images, environmental measurements, and cultivation trials.},
        keywords = {Artificial intelligence, automated cultivation, greenhouse monitoring, Internet of Things, mushroom cultivation, growth-stage identification, environmental monitoring.},
        month = {November},
        }

Cite This Article

J, P., & M, P., & S, P., & U, S. K., & K, S. L., & B, A. (2026). An Intelligent Greenhouse Monitoring Framework for Automated Mushroom Cultivatiom. International Journal of Innovative Research in Technology (IJIRT), 13(6), 26–30.

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