Manjunatha, B and Moorthy, K. Sankara and Srinivasan, Vellayan and Awasthi, Manuj and Ashok, Merugu and Suresh, M. (2023) Machine Learning and Internet of Things for infection Prediction in Fruits and Vegetables. In: UNSPECIFIED.
Full text not available from this repository.Abstract
Future agriculture will depend heavily on connected devices, detectors and the Internet of Things (IoT) to be more productive and sustainable. WSNs Technology-based communications and data can be used to solve the majority of the critical challenges in economics, technology, and environmental protection. Increasing the number of connected devices produces a significant amount of data in many different modalities. Additionally, geographical and temporal factors contribute to the rise in the number of networked devices. After being carefully processed and analyzed, this enormous volume of data will offer a deeper understanding that motivation enhances future forecasting, executive, and management of sensor compulsion. © 2023 Elsevier B.V., All rights reserved.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Agricultural and Biological Sciences > Agricultural Sciences |
| Divisions: | Engineering and Technology > Vinayaka Mission's Kirupananda Variyar Engineering College, Salem > Mechanical Engineering |
| Depositing User: | Unnamed user with email techsupport@mosys.org |
| Last Modified: | 01 Dec 2025 05:45 |
| URI: | https://vmuir.mosys.org/id/eprint/2536 |
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