Mitigating post-harvest losses through IoT-based machine learning algorithms in smart farming
- Title
- Mitigating post-harvest losses through IoT-based machine learning algorithms in smart farming
- Creator
- Kanna R.R.; Priya T.M.; Sivakumar V.; Nataraj C.; Thomas J.
- Description
- This research paper explores the transformative potential of Internet of Things (IoT) technology in mitigating the longstanding issue of post-harvest losses within the agriculture sector. These losses, which encompass both quantitative and qualitative deterioration of food commodities from harvest to consumption, have posed persistent challenges, resulting in economic losses and food wastage. By delving into the current landscape of post-harvest losses and the application of IoT technology, the paper offers valuable insights into how IoT can be harnessed to reduce these losses effectively. It not only highlights the benefits and existing IoT solutions but also addresses the inherent challenges, providing recommendations for their resolution. Moreover, the research introduces a machine learning-based model, specifically Random Forest ML, to identify and prevent losses in tandem with IoT devices, empowering farmers with timely alert messages for informed decision-making, thus fostering a more sustainable and efficient agricultural ecosystem. 2024 Author(s).
- Source
- AIP Conference Proceedings, Vol-3161, No. 1
- Date
- 2024-01-01
- Publisher
- American Institute of Physics
- Coverage
- Kanna R.R., Department of Computer Science, CHRIST (Deemed to Be University), Bangalore, India; Priya T.M., Department of Computer Science, CHRIST (Deemed to Be University), Bangalore, India; Sivakumar V., School of Computing, Faculty of Computing Engineering and Technology, Asia Pacific University of Technology and Innovation, Kuala Lumpur, Malaysia; Nataraj C., School of Engineering, Faculty of Computing Engineering and Technology, Asia Pacific University of Technology and Innovation, Kuala Lumpur, Malaysia; Thomas J., Department of Sociology and Social Work, CHRIST (Deemed to Be University), Bangalore, India
- Rights
- Restricted Access
- Relation
- ISSN: 0094243X
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Kanna R.R.; Priya T.M.; Sivakumar V.; Nataraj C.; Thomas J., “Mitigating post-harvest losses through IoT-based machine learning algorithms in smart farming,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 26, 2025, https://archives.christuniversity.in/items/show/18952.