Publication2026
IoT-Powered Predictive Maintenance: Harnessing AI for Industrial Equipment
- Decent Work and Economic Growth
- Industry, Innovation and Infrastructure
- Partnerships for the Goals
- Innovation, Science and Technology
The record
- Type
- Publication
- Date
- 1 January 2026
- Level
- International — held abroad
- Journal
- 6th International Conference on Recent Trends in Computer Science and Technology Icrtcst 2026 Proceedings
- Pages
- 952-957
- Published
- 1 January 2026
- DOI
- 10.1109/icrtcst68392.2026.11545451
- Scopus ID
- 105042589935
- Authors
- 6
- Open access
- No
- Citations
- 0
- International co-authorship
- Yes
- Co-author countries
- ET, IN, US
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
9 Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
IoT and machine learning-enabled predictive maintenance framework reduces equipment downtime and extends operational life of industrial machinery, supporting sustainable manufacturing and industrial productivity.
- 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
8 Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all
Predictive maintenance approach improves labor productivity and economic efficiency of industrial operations through reduced unplanned equipment failures.
- 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
17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing
Structural signal: co-authorship outside India.
- Rule-derived
- Emitted by a deterministic rule from structural signals rather than judged from the record’s text. The rule carries a version, so rule-derived and judged labels stay separable.
- Produced by
- sdg17-structural-v1, under kortex-publication-v1
Viksit Bharat @2047
vb-3 Innovation, Science and Technology
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 9 label. IoT and machine learning-enabled predictive maintenance framework reduces equipment downtime and extends operational life of industrial machinery, supporting sustainable manufacturing and industrial productivity.
- 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.
Evidence
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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-Powered Predictive Maintenance: Harnessing AI for Industrial Equipment”. Kortex.