2026-10-14T02:36:14Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34029948 2026-09-30T05:15:53Z category_26941 item_type_12 month_year_09_2026

Explanatory Modeling of Cross-Sensor Communication Breakdown in Heterogeneous Industrial IoT Networks for Air Quality Monitoring Davina Liberata Dallo (25141658) Environmental management air quality monitoring; industrial IoT; communication breakdown; fault diagnosis; temporal synchronization; explanatory framework. <h2 dir="ltr">Air quality monitoring in industrial environments now depends on networks of heterogeneous sensors: metal-oxide gas detectors, process telemetry, meteorological stations, and citizen reports. These systems are usually evaluated by how accurately their constituents measure. This article argues that their decisive failure mode is different and less well theorized cross-sensor communication breakdown, the process by which streams that individually remain valid cease to agree with one another. Existing research addresses the detection and tolerance of faults : node failures, link failures, energy depletion, packet loss. That work has produced mature diagnostic taxonomies and fault-tolerant routing schemes, but detection is not explanation. We develop an explanatory framework that reconstitutes communication breakdown as a violation of an interaction contract : an exchange succeeds only when the receiver can reconstruct the time, place, uncertainty, and provenance of an observation, and fails whenever that reconstruction fails, whether or not the packet arrived. The framework organizes causal mechanisms across four strata radio-physical, energetic, temporal, and semantic-organizational and specifies two propagation mechanisms. Cascade occurs when a disturbance in one stratum displaces the operating point of another; masquerade occurs when the signature of one stratum becomes indistinguishable from that of another. We derive four testable propositions and state the practical consequence : under masquerade, an absence of data is systematically misread as an absence of pollution. The framework reframes monitoring reliability as an explanatory problem rather than a detection problem, with direct implications for how industrial networks are instrumented, diagnosed, and procured.</h2> 2026-08-31T00:00:00Z Text Preprint 10.6084/m9.figshare.34029948.v1 https://figshare.com/articles/preprint/_b_Explanatory_Modeling_of_Cross-Sensor_Communication_Breakdown_in_Heterogeneous_Industrial_IoT_Networks_for_Air_Quality_Monitoring_b_/34029948 CC BY 4.0