Publication2024
Crop Prediction by Implementing Machine Learning in an IoT-Based System
The record
- Type
- Publication
- Date
- 1 January 2024
- Level
- National
- Journal
- Optimized Computational Intelligence Driven Decision Making Theory Application and Challenges
- Pages
- 107-130
- Published
- 1 January 2024
- DOI
- 10.1002/9781394242566.ch6
- Scopus ID
- 85206147216
- Authors
- 2
- Open access
- No
- Citations
- 2
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
2 End hunger, achieve food security and improved nutrition and promote sustainable agriculture
Machine learning crop prediction model integrated with IoT sensors and data analytics improves agricultural productivity and sustainability through precision farming optimization.
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
IoT and machine learning integration for agriculture represents innovation in agricultural technology research capacity.
- Moderate confidence
- The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-2.1 Agriculture and the rural economy
Precision agriculture using AI and IoT directly supports agricultural productivity and rural economy development.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “Crop Prediction by Implementing Machine Learning in an IoT-Based System”. Kortex.