Аннотация
Traditionally, preventive conservation of an archive on paper is ensured by recording threshold values of the microclimate in the storage facility or by periodic revision of the archive materials. None of these methods provides an updated forecast for each object regarding when it will require conservation. This article aims to fill this gap and proposes a condition assessment and forecasting module for a smart archive storage facility with support for the Internet of Things. The module combines two mechanisms of paper degradation into a preservation index for each object: a chemical “dose-effect” function that describes the breakdown of cellulose under the influence of temperature, relative humidity, and acidity, and a mechanical function that describes the damage that occurs during the handling of documents. Based on this index, the module calculates a forecast that determines the time remaining until the threshold of usability is reached and sends a notification when this time drops below the specified planning horizon. Unlike existing approaches, which are applied either at the storage level (preservation index / time‑weighted preservation index, commercial monitoring panels) or as a static one‑time calculation for the entire collection (damage function isochrones), the proposed architecture ensures continuous recalculation of the forecast based on sensor data in real time for each object. The computational core of the model was tested under accelerated aging conditions (ISO 5630‑3) and reproduced the degradation periods, which confirms the correctness of the implementation of the kinetic equation underlying the model. The mechanical component and the comprehensive condition index are still validated only theoretically and require additional verification using real telemetry data. The proposed module opens practical opportunities for creating archival equipment that not only maintains the specified climatic conditions but also actively assists institutions in planning conservation work.