A5005631393- Data Quality and Management
- Semantic Web and Ontologies
- Scientific Computing and Data Management
- Big Data Technologies and Applications
- IoT and Edge/Fog Computing
- Embedded Systems Design Techniques
- Context-Aware Activity Recognition Systems
- Technology and Data Analysis
- Advanced Clustering Algorithms Research
- Research Data Management Practices
- Advanced Data Storage Technologies
- Blockchain Technology Applications and Security
- Service-Oriented Architecture and Web Services
- Business Process Modeling and Analysis
- Computational Physics and Python Applications
- Nutrition, Health and Food Behavior
- Topic Modeling
RWTH Aachen University
2021-2024
The building sector is undergoing a deep transformation to contribute meeting the climate neutrality goals set by policymakers worldwide. This process entails transition towards smart energy-aware buildings that have lower consumptions and better efficiency performance. Digitalization key part of this process. A huge amount data currently generated sensors, meters multitude other devices sources, trend expected exponentially increase in near future. Exploiting these for different use cases...
With the ongoing digital transformation and multi-domain interaction occurring in buildings, a huge amount of heterogeneous data is generated stored on daily basis. To take advantage gathered help better decision makings, suitable methods are needed to meet demand for building operations reinvestment planning. Ontology, which provides not only vocabulary certain domain but also relationship between each other has been used multiple engineering fields manage data. A plethora ontology...
The increase in heterogeneous data the building energy domain creates a difficult challenge for integration. Schema matching, which maps raw from to generic model, is necessary step integration and provides unique representation. Only small amount of labeled schema matching exists it time-consuming labor-intensive manually label data. This paper applies semantic-similarity methods automatic schema-mapping process by combining knowledge natural language processing, reduces manual effort...
Abstract Data integration in the energy sector, which refers to process of combining and harmonizing data from multiple heterogeneous sources, is becoming increasingly difficult due growing volume data. Schema matching plays a crucial role this by giving each representation unique identity raw generic model. This study uses an domain language model automate schema matching, reducing manual effort integrating We developed two models, Energy BERT Sentence Bert, trained them using open-source...
ENTIRETY 1 is a web application for governing and provisioning IoT devices. Due to the rapid evolution digitization of energy systems, domain ontology required manage data in structured way. This paper presents ontology-based 2, which updated version 1. provides an interface collection transmission. The collected by device are provided ICT platform according ontology. 2 overcomes challenges mapping between different network protocols automates generation JSON-LD based on files. Therefore,...
The integration of renewable energy sources, the decentralization system, and increasing digitization energy-related processes require a wide range data. In this context, data sharing platform can serve as hub for exchanging developing innovative solutions to improve efficiency sustainability system. However, especially because involvement industry in such poses several challenges related protection, intellectual property, business interests. This paper presents framework ensuring...