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Climate science has become more ambitious in recent years as global awareness about the environment has grown. To better understand climate, historical climate (e.g. archived meteorological variables such as temperature, wind, water, etc.)…
In this work we study an application of machine learning to the construction industry and we use classical and modern machine learning methods to categorize images of building designs into three classes: Apartment building, Industrial…
In this paper, we investigate the issue of integrated sensing, computation and communication (SCC) in beyond fifth-generation (B5G) cellular internet of things (IoT) networks. According to the characteristics of B5G cellular IoT, a…
An increasing amount of information is generated from the rapidly increasing number of sensor networks and smart devices. A wide variety of sources generate and publish information in different formats, thus highlighting interoperability as…
While 3D LiDAR sensor technology is becoming more advanced and cheaper every day, the growth of digitalization in the AEC industry contributes to the fact that 3D building information models (BIM models) are now available for a large part…
In this article, we tackle the problem of standard interoperability across different standardization frameworks, and devise a knowledge-driven approach that allows for the description of standards and standardization frameworks into an…
The future grid will be highly complex and decentralized, requiring sophisticated coordination across numerous human and software agents that manage distributed resources such as Demand Response (DR). Realizing this vision demands…
Within clinical, biomedical, and translational science, an increasing number of projects are adopting graphs for knowledge representation. Graph-based data models elucidate the interconnectedness between core biomedical concepts, enable…
We present a scalable solution to link entities across mobility datasets using their spatio-temporal information. This is a fundamental problem in many applications such as linking user identities for security, understanding privacy…
When data on building features is unavailable, the task of determining how to improve that building in terms of carbon emissions becomes infeasible. We show that from only a set of images, a Large Language Model with appropriate prompt…
Contemporary product analytics systems require users to pose explicit queries, such as writing SQL, configuring dashboards, or constructing funnels, before insights can surface. This pull-based paradigm creates a bottleneck: it requires…
Several synergistic trends, subsumed under the phrase "Internet of things (IoT)" massively drive the increasing importance of networking applications. In the past, the exponential growth of the Internet was mainly due to semantically…
Enterprise knowledge graphs combine business data and organizational knowledge by means of a semantic network of concepts, properties, individuals and relationships. The graph-based integration of previously unconnected information with…
Collecting intensive longitudinal thermal preference data from building occupants is emerging as an innovative means of characterizing the performance of buildings and the people who use them. These techniques have occupants giving…
The proliferation of interconnected devices in the Internet of Things (IoT) has led to an exponential increase in data, commonly known as Big IoT Data. Efficient retrieval of this heterogeneous data demands a robust indexing mechanism for…
The combination of the infrastructure provided by the Internet of Things (IoT) with numerous processing nodes present at the Edge Computing (EC) ecosystem opens up new pathways to support intelligent applications. Such applications can be…
Building patterns are important urban structures that reflect the effect of the urban material and social-economic on a region. Previous researches are mostly based on the graph isomorphism method and use rules to recognize building…
Modern distributed decision-making systems face significant challenges arising from data heterogeneity, dynamic environments, and the need for decentralized coordination. This paper introduces the Knowledge Sharing paradigm as an innovative…
Disconnected data silos within enterprises obstruct the extraction of actionable insights, diminishing efficiency in areas such as product development, client engagement, meeting preparation, and analytics-driven decision-making. This paper…
Disaggregation and rack-scale systems have the potential of drastically decreasing TCO and increasing utilization of cloud datacenters, while maintaining performance. While the concept of organising resources in separate pools and…