Titlebook: Energy Informatics; 4th Energy Informati Bo Nørregaard Jørgensen,Zheng Grace Ma,Sarjiya Sar Conference proceedings 2025 The Editor(s) (if a

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Conference proceedings 2025Indonesia, during October 23–25, 2024...The 40 full papers and 8 short papers included in these proceedings were carefully reviewed and selected from 64 submissions. They are categorized under the topical sections as follows:..Part I: IoT Edge Computing, and Software Innovations in Energy, Big Data

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https://doi.org/10.1007/978-1-4684-8995-8EVM)-compatible platforms to determine the most cost-efficient options for implementing these systems. Our findings suggest that the integration of these technologies can enhance the management and trading of renewable energy, ensuring secure and efficient operations.

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Securing Renewable Energy Transactions: Blockchain, RSA-Encrypted NFTs, and IPFS IntegrationEVM)-compatible platforms to determine the most cost-efficient options for implementing these systems. Our findings suggest that the integration of these technologies can enhance the management and trading of renewable energy, ensuring secure and efficient operations.

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0302-9743 ibility and Energy Conservation Strategies, Optimization of Energy Systems and Renewable Integration and Energy System Resilience and Reliability..978-3-031-74740-3978-3-031-74741-0Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Microbial Services for Cereal Crops the UFH that is negatively perceived by the occupants who are used to feeling the warm floor. The paper highlights that the UFH, in combination with occupant’s comfort preferences, can be the reason for NZEBs to operate with elevated indoor temperatures and to use more energy than anticipated. Resu

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Julie Kinzelman,David Kay,Kathy Pondn of the household’s annual electricity consumption among the monitored appliances. Moreover, it was observed that the refrigerator and geyser were used frequently throughout the year, while the air conditioner and the space heater were used only in the extreme summer and winter, respectively. In su

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José M. Luengo,Elías R. Oliveradatasets from a collection of European buildings’ most common HVAC systems, serialize them, and pass them to a pre-trained LLM (DistilBERT). By fine-tuning the model with a large number of labeled input data, we enable classification into either binary cases (faulty/fault-free) or multiple fault cla

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