MATRYCS—A Big Data Architecture for Advanced Services in the Building Domain
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Molina-Solana, Miguel & Ros, María & Ruiz, M. Dolores & Gómez-Romero, Juan & Martin-Bautista, M.J., 2017. "Data science for building energy management: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 598-609.
- Vangelis Marinakis, 2020. "Big Data for Energy Management and Energy-Efficient Buildings," Energies, MDPI, vol. 13(7), pages 1-18, March.
- Natalia Lasarte & Peru Elguezabal & Maialen Sagarna & Iñigo Leon & Juan Pedro Otaduy, 2021. "Challenges for Digitalisation in Building Renovation to Enhance the Efficiency of the Process: A Spanish Case Study," Sustainability, MDPI, vol. 13(21), pages 1-25, November.
- Panagiotis Kapsalis & Giorgos Kormpakis & Konstantinos Alexakis & Dimitrios Askounis, 2022. "Leveraging Graph Analytics for Energy Efficiency Certificates," Energies, MDPI, vol. 15(4), pages 1-12, February.
- Massimiliano Manfren & Benedetto Nastasi, 2020. "Parametric Performance Analysis and Energy Model Calibration Workflow Integration—A Scalable Approach for Buildings," Energies, MDPI, vol. 13(3), pages 1-14, February.
- Jenny von Platten & Claes Sandels & Kajsa Jörgensson & Viktor Karlsson & Mikael Mangold & Kristina Mjörnell, 2020. "Using Machine Learning to Enrich Building Databases—Methods for Tailored Energy Retrofits," Energies, MDPI, vol. 13(10), pages 1-22, May.
- Peng, Yuzhen & Rysanek, Adam & Nagy, Zoltán & Schlüter, Arno, 2018. "Using machine learning techniques for occupancy-prediction-based cooling control in office buildings," Applied Energy, Elsevier, vol. 211(C), pages 1343-1358.
- Yang, Lei & Nagy, Zoltan & Goffin, Philippe & Schlueter, Arno, 2015. "Reinforcement learning for optimal control of low exergy buildings," Applied Energy, Elsevier, vol. 156(C), pages 577-586.
- Gema Hernández-Moral & Sofía Mulero-Palencia & Víctor Iván Serna-González & Carla Rodríguez-Alonso & Roberto Sanz-Jimeno & Vangelis Marinakis & Nikos Dimitropoulos & Zoi Mylona & Daniele Antonucci & H, 2021. "Big Data Value Chain: Multiple Perspectives for the Built Environment," Energies, MDPI, vol. 14(15), pages 1-21, July.
- Rasa Apanaviciene & Andrius Vanagas & Paris A. Fokaides, 2020. "Smart Building Integration into a Smart City (SBISC): Development of a New Evaluation Framework," Energies, MDPI, vol. 13(9), pages 1-19, May.
- Ke, Ming-Tsun & Yeh, Chia-Hung & Su, Cheng-Jie, 2017. "Cloud computing platform for real-time measurement and verification of energy performance," Applied Energy, Elsevier, vol. 188(C), pages 497-507.
- Sofia Agostinelli & Fabrizio Cumo & Giambattista Guidi & Claudio Tomazzoli, 2021. "Cyber-Physical Systems Improving Building Energy Management: Digital Twin and Artificial Intelligence," Energies, MDPI, vol. 14(8), pages 1-25, April.
- Antonio Attanasio & Marco Savino Piscitelli & Silvia Chiusano & Alfonso Capozzoli & Tania Cerquitelli, 2019. "Towards an Automated, Fast and Interpretable Estimation Model of Heating Energy Demand: A Data-Driven Approach Exploiting Building Energy Certificates," Energies, MDPI, vol. 12(7), pages 1-25, April.
- Roberto Chiosa & Marco Savino Piscitelli & Alfonso Capozzoli, 2021. "A Data Analytics-Based Energy Information System (EIS) Tool to Perform Meter-Level Anomaly Detection and Diagnosis in Buildings," Energies, MDPI, vol. 14(1), pages 1-28, January.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Zhiyu Pan & Guanchen Pan & Antonello Monti, 2022. "Semantic-Similarity-Based Schema Matching for Management of Building Energy Data," Energies, MDPI, vol. 15(23), pages 1-23, November.
- Cezar-Petre Simion & Cătălin-Alexandru Verdeș & Alexandra-Andreea Mironescu & Florin-Gabriel Anghel, 2023. "Digitalization in Energy Production, Distribution, and Consumption: A Systematic Literature Review," Energies, MDPI, vol. 16(4), pages 1-30, February.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Gautham Krishnadas & Aristides Kiprakis, 2020. "A Machine Learning Pipeline for Demand Response Capacity Scheduling," Energies, MDPI, vol. 13(7), pages 1-25, April.
- Benedetto Nastasi & Massimiliano Manfren & Michel Noussan, 2020. "Open Data and Energy Analytics," Energies, MDPI, vol. 13(9), pages 1-3, May.
- Ru-Guan Wang & Wen-Jen Ho & Kuei-Chun Chiang & Yung-Chieh Hung & Jen-Kuo Tai & Jia-Cheng Tan & Mei-Ling Chuang & Chi-Yun Ke & Yi-Fan Chien & An-Ping Jeng & Chien-Cheng Chou, 2023. "Analyzing Long-Term and High Instantaneous Power Consumption of Buildings from Smart Meter Big Data with Deep Learning and Knowledge Graph Techniques," Energies, MDPI, vol. 16(19), pages 1-24, September.
- Benedetto Nastasi & Massimiliano Manfren & Michel Noussan, 2021. "Open Data and Models for Energy and Environment," Energies, MDPI, vol. 14(15), pages 1-2, July.
- Liu, Yang & Yu, Nanpeng & Wang, Wei & Guan, Xiaohong & Xu, Zhanbo & Dong, Bing & Liu, Ting, 2018. "Coordinating the operations of smart buildings in smart grids," Applied Energy, Elsevier, vol. 228(C), pages 2510-2525.
- Lei, Yue & Zhan, Sicheng & Ono, Eikichi & Peng, Yuzhen & Zhang, Zhiang & Hasama, Takamasa & Chong, Adrian, 2022. "A practical deep reinforcement learning framework for multivariate occupant-centric control in buildings," Applied Energy, Elsevier, vol. 324(C).
- Zhang, Liang & Wen, Jin & Li, Yanfei & Chen, Jianli & Ye, Yunyang & Fu, Yangyang & Livingood, William, 2021. "A review of machine learning in building load prediction," Applied Energy, Elsevier, vol. 285(C).
- Mustaffa, Nur Kamaliah & Kudus, Sakhiah Abdul, 2022. "Challenges and way forward towards best practices of energy efficient building in Malaysia," Energy, Elsevier, vol. 259(C).
- Tiantian Gu & Shuyu Liu & Xuefan Liu & Yujia Shan & Enyang Hao & Miaomiao Niu, 2023. "Evaluation of the Smart City and Analysis of Its Spatial–Temporal Characteristics in China: A Case Study of 26 Cities in the Yangtze River Delta Urban Agglomeration," Land, MDPI, vol. 12(10), pages 1-23, September.
- Jing, Gang & Cai, Wenjian & Zhang, Xin & Cui, Can & Yin, Xiaohong & Xian, Huacai, 2019. "An energy-saving oriented air balancing strategy for multi-zone demand-controlled ventilation system," Energy, Elsevier, vol. 172(C), pages 1053-1065.
- Panagiotis Michailidis & Iakovos Michailidis & Dimitrios Vamvakas & Elias Kosmatopoulos, 2023. "Model-Free HVAC Control in Buildings: A Review," Energies, MDPI, vol. 16(20), pages 1-45, October.
- Chen, Zhelun & O’Neill, Zheng & Wen, Jin & Pradhan, Ojas & Yang, Tao & Lu, Xing & Lin, Guanjing & Miyata, Shohei & Lee, Seungjae & Shen, Chou & Chiosa, Roberto & Piscitelli, Marco Savino & Capozzoli, , 2023. "A review of data-driven fault detection and diagnostics for building HVAC systems," Applied Energy, Elsevier, vol. 339(C).
- Yassine Chemingui & Adel Gastli & Omar Ellabban, 2020. "Reinforcement Learning-Based School Energy Management System," Energies, MDPI, vol. 13(23), pages 1-21, December.
- Wadim Strielkowski & Anna Sherstobitova & Patrik Rovny & Tatiana Evteeva, 2021. "Increasing Energy Efficiency and Modernization of Energy Systems in Russia: A Review," Energies, MDPI, vol. 14(11), pages 1-19, May.
- Vangelis Marinakis & Themistoklis Koutsellis & Alexandros Nikas & Haris Doukas, 2021. "AI and Data Democratisation for Intelligent Energy Management," Energies, MDPI, vol. 14(14), pages 1-14, July.
- Gokhale, Gargya & Claessens, Bert & Develder, Chris, 2022. "Physics informed neural networks for control oriented thermal modeling of buildings," Applied Energy, Elsevier, vol. 314(C).
- Capozzoli, Alfonso & Piscitelli, Marco Savino & Brandi, Silvio & Grassi, Daniele & Chicco, Gianfranco, 2018. "Automated load pattern learning and anomaly detection for enhancing energy management in smart buildings," Energy, Elsevier, vol. 157(C), pages 336-352.
- Davide Coraci & Silvio Brandi & Marco Savino Piscitelli & Alfonso Capozzoli, 2021. "Online Implementation of a Soft Actor-Critic Agent to Enhance Indoor Temperature Control and Energy Efficiency in Buildings," Energies, MDPI, vol. 14(4), pages 1-26, February.
- Severinsen, A. & Myrland, Ø., 2022. "ShinyRBase: Near real-time energy saving models using reactive programming," Applied Energy, Elsevier, vol. 325(C).
- Aleksandra Kuzior & Marek Staszek, 2021. "Energy Management in the Railway Industry: A Case Study of Rail Freight Carrier in Poland," Energies, MDPI, vol. 14(21), pages 1-21, October.
More about this item
Keywords
high-level architecture; building services; building value chain; big data; Internet of Things; data analytics;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:7:p:2568-:d:784979. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.