← Search

Data · dataset · 2026

<b>Decoding Olfactory Sensor Degradation Mechanisms in Harsh Industrial Ecosystems An Explanatory IoT Reliability Framework</b>

Listed in ZivaHub and Deakin Research Online — shown once because both records carry DOI 10.6084/m9.figshare.34029894.v1

<p dir="ltr"><i>Metal-oxide and polymer gas sensors deployed in industrial environments degrade, and the field knows this well enough to have built an extensive compensation literature.

Description

What it lacks is an explanation of degradation that connects the physical mechanism to the inferential consequence. Compensation methods are validated by an accuracy metric computed on labelled reference data, which means they are evaluated on their ability to recover a known mapping rather than on their effect upon the meaning of a measurement made after the mapping has moved.

This article develops an explanatory framework that reconstitutes sensor degradation as the progressive invalidation of an observation's declared contract : the sensor continues to report, but the terms under which its report may be relied upon have silently expired. We distinguish three strata physico-chemical alteration, operational and environmental influence, and instrumental-network reliability and show that their signatures converge on two outcomes that compensation practice does not address.

Read the rest (2 more)

The first is </i><i>convergent ambiguity</i><i> : drifting sensors and genuinely shifting pollution regimes generate indistinguishable divergence, and the discriminator is not the signal but the drift model's own residual. The second is </i><i>reference erosion</i><i> : because drift is directionally structured rather than random, the variance directions that compensation removes are the same directions in which sustained regime change would appear.

We derive four testable propositions and specify what self-calibration must report to remain verifiable with an emphasis on quantities obtainable at negligible cost, such as self-declared reliability transmitted without additional communication overhead</i></p>

Links

Where it is published

Catalogue records · 1

Topics

Inferred from text
Climate change science 70%
Provenance · 2 source records, 8 field assertions
SourceKeyLast seenRaw
ZivaHuboai:figshare.com:article/3402989413 d agoJSON v1
Deakin Research Onlineoai:figshare.com:article/3402989413 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0
concepts[field].anzsrc:group:3702enrichment · zivahub uct ac zataxonomy-embedding@1.1.0title+keywords+description (70%)
concepts[field].local:field:earth-environmentalmapping · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0
concepts[field].local:field:earth-environmentalmapping · dro deakin edu auconnector:dro_deakin_edu_au@1.0.0
descriptionsource · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0/metadata/dc/description
licensesource · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0/metadata/dc/rights
publication_datesource · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0
titlesource · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0/metadata/dc/title