## 4 Conclusions  
The storage enclosure offers a buffering capacity that moderates micro-environmental temperature and RH fluctuations, enabling energy savings by relaxing macro-environmental control in the room. Nevertheless, there is a practical barrier in implementing physical sensors for each enclosure to achieve real-time conformity monitoring of the micro-environment to ensure compliance with preventive conservation specifications. To address this limitation, this study developed a coupled heat and mass transfer model. This model served to establish acceptable macro-environmental conditions while ensuring compliance of the micro-environment with preventive conservation specifications. Additionally, the data generated from the heat and mass simulation were utilized to train an ANN model. This ANN model was successfully deployed in a real-world application, demonstrating promising results for real-time conformity monitoring of the micro-environment. The key conclusions are outlined as follows. (1) The coupled heat and mass model effectively captured the hygothermal interaction between macro- and micro-environments with high accuracy and acceptable agreement. It can reproduce the variation trends and fluctuation periods in the measurement conditions to determine an acceptable macro-environment. (2) The acceptable macro-environment can be relaxed from 40 to 60 %RH with a \(\pm\)10 %RH 24-h fluctuation to 3-65 %RH with a \(\pm\)16 %RH fluctuation, while ensuring the compliance of micro-environment with the specifications of preventive conservation. (3) The ANN-based prediction can achieve high accuracy 24 h time-sequence prediction of micro-environment within 5 s. This prediction demonstrates satisfactory robustness in real-time conformity monitoring, further facilitating the implementation of the relaxing control strategy for sustainable practices in preventive conservation. These efforts leverage the advantage of ANN-based approach to overcome the limitation of real-time conformity monitoring of the micro-environment without disrupting on-site operation of the air conditioning system in the NLS. In a practical application, using real-time prediction for the micro-environment temperature and RH eliminates the necessity for monitoring sensors inside each enclosure and offers an easy way to map the micro-environmental conditions inside a multitude of enclosures in the large storage space. This particular predictive capacity could enable monitoring the micro-environment within the enclosures against the desirable condition under various control accuracies in the storage room, the macro-environment, consequently testing the control levels that save energy in the service system and are safe for the collections inside the enclosures without detrimental effect on the collections stored inside the enclosures. This study provides valuable insights and offers a promising solution for monitoring micro-environmental conformity and implementing a relaxed control strategy in the macro-environment without compromising the integrity of the collections stored inside the enclosures. However, it is based on a limited dataset for ANN training, which constrains its prediction ability to generalize across the physical discrepancies. Future work should focus on continuous data training, updating the current network with new data to enhance prediction accuracy and ensure the safeguarding of collection care. Additionally, the work will also focus on explicitly modeling temperature-RH interaction under scenarios with significant temperature fluctuations to enhance the ANN's ability to handle coupled thermal-hygrometric stress and support even broader operational flexibility for preventive conservation. Conceptualization, F.W. and J.B.; Methodology, B.H. and F.W. ; Validation, B.H. ; Formal analysis, B.H. ; Investigation, B.H. ; Resources, J.B., L.M. and N.K.T. ; Data curation, B.H. ; Writing--original draft, B.H. ; Writing--review & editing, B.H., F.W., J.B. and N.K.T. ; Supervision, F.W. and N.K.T. ; Project administration, F.W.