Technologies for a Diagnostic Technique for HVAC Systems Using IoT and Cloud-Based Architecture
Author:
Affiliation:
1. University of Rostock,Chair of Business Information Systems,Rostock,Germany
Funder
University of Rostock
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10124378/10124396/10124398.pdf?arnumber=10124398
Reference11 articles.
1. Development of a diagnostic technique for air conditioning systems;huhs;in International Interdisciplinary PhD Workshop (IIPhDW),2023
2. Novel real-time model-based fault detection method for automatic identification of abnormal energy performance in building ventilation units
Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Next-Gen HVAC Technologies with K-Nearest Neighbors for Cloud-Optimized Allergen Filtration for Healthier Living Spaces;2024 International Conference on Inventive Computation Technologies (ICICT);2024-04-24
2. A Modeling Approach Supporting Digital Twin Engineering: Optimizing the Energy Consumption of Air Conditioning Facilities;2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C);2023-10-01
3. Development of a Diagnosis Technique for Air Conditioning Systems;2023 International Interdisciplinary PhD Workshop (IIPhDW);2023-05-03
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