Publication2024
Identification and Mitigation Process for the Air Quality Using Machine Learning Techniques
The record
- Type
- Publication
- Date
- 1 January 2024
- Level
- National
- Journal
- Lecture Notes in Networks and Systems
- Volume
- 914 LNNS
- Pages
- 281-293
- Published
- 1 January 2024
- DOI
- 10.1007/978-981-97-0573-3_23
- Scopus ID
- 85201016279
- ISSN
- 23673370
- Authors
- 3
- Open access
- No
- Citations
- 0
- 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
13 Take urgent action to combat climate change and its impacts
Machine learning identification and mitigation of air pollutants including PM2.5, NO2 and SO2 contributes to climate action and atmospheric quality improvement.
- 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
3 Ensure healthy lives and promote well-being for all at all ages
Air quality monitoring and control directly affects respiratory health outcomes of affected populations.
- 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-2.5 Green economy, energy transition and climate resilience
Environmental pollution control supports green economy and climate resilience.
- 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. “Identification and Mitigation Process for the Air Quality Using Machine Learning Techniques”. Kortex.