Publication2026
AI in Wildlife Conservation
- Industry, Innovation and Infrastructure
- Life on Land
- Partnerships for the Goals
- Thriving and Sustainable Economy
The record
- Type
- Publication
- Date
- 1 January 2026
- Level
- International — held abroad
- Journal
- Immersive Technologies and Human Centric Innovation in the Industry 5 0 Era
- Pages
- 267-296
- Published
- 1 January 2026
- DOI
- 10.4018/979-8-2600-0013-7.ch008
- Scopus ID
- 105040281190
- Authors
- 4
- Open access
- Yes
- Citations
- 0
- International co-authorship
- Yes
- Co-author countries
- ID, IN, TW
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
15 Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss
Explicitly addresses wildlife species monitoring, habitat mapping, and conservation through AI-enabled technologies for biodiversity protection.
- Certain confidence
- The record states the subject matter explicitly. A reader shown only the title and this goal would agree without hesitation. Example: a workshop titled "Renewable Energy and Smart Grid" against SDG 7.
- 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
Develops advanced AI and remote sensing methods for environmental monitoring and conservation applications.
- 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.
- 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.
- 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-2 Thriving and Sustainable Economy
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 15 label. Explicitly addresses wildlife species monitoring, habitat mapping, and conservation through AI-enabled technologies for biodiversity protection.
- 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
Kortex hosts no documents. Evidence is an outbound link to the authority that holds it.
No outbound evidence link is recorded for this activity. The record below states which source it came from and when it was last read.
Provenance
Which source system this record came from, how many source rows were resolved into it, and when each was last read.
- Source rows resolved into this record
- 1
Each record carries the date Kortex last read it from its source system. That is a freshness date and not a verification: Kortex records what its sources say and when it read them, and it does not check those statements against any external authority. No claim on this site is described as verified, because none is.
Citing this record
This URL is stable. A record’s permalink is frozen when it is published and is not regenerated if its title is later corrected.
KIIT Deemed to be University. “AI in Wildlife Conservation”. Kortex.