Publication2023
IoT-Enabled Soil Nutrient Analysis and Crop Recommendation Model for Precision Agriculture
- Zero Hunger
- Industry, Innovation and Infrastructure
- Thriving and Sustainable Economy
The record
- Type
- Publication
- Date
- 1 March 2023
- Level
- National
- Journal
- Computers
- Volume
- 12
- Issue
- 3
- Published
- 1 March 2023
- DOI
- 10.3390/computers12030061
- Scopus ID
- 85150974645
- ISSN
- 2073431X
- Authors
- 3
- Open access
- Yes
- Citations
- 221
- 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
2.3 Double the agricultural productivity and incomes of small-scale food producers
IoT-enabled soil nutrient analysis and machine learning crop recommendation model supports precision agriculture and sustainable farming decisions.
- 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
Multi-sensor system with cloud integration and hybrid machine learning algorithm represents agricultural technology innovation for smallholder farmers.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-2 Thriving and Sustainable Economy
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 2 label. IoT-enabled soil nutrient analysis and machine learning crop recommendation model supports precision agriculture and sustainable farming decisions.
- 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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Provenance
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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. “IoT-Enabled Soil Nutrient Analysis and Crop Recommendation Model for Precision Agriculture”. Kortex.