Related papers: Data Aggregation, Fusion and Recommendations for S…
Despite many decades of research, economically grounded models that analyse energy consumption and energy-efficiency adoption within a unified framework remain underdeveloped. This article addresses this gap by proposing a model of…
The activity-based workspace (ABW) paradigm is becoming more popular in commercial office spaces. In this strategy, occupants are given a choice of spaces to do their work and personal activities on a day-to-day basis. This paper shows the…
Cities create potential for individuals from different backgrounds to interact with one another. It is often the case, however, that urban infrastructure obfuscates this potential, creating dense pockets of affluence and poverty throughout…
Balanced and efficient information flow is essential for optimizing language generation models. In this work, we propose Entropy-UID, a new token selection method that balances entropy and Uniform Information Density (UID) principles for…
Climate change has become a major problem for humanity in the last two decades. One of the reasons that caused it, is our daily energy waste. People consume electricity in order to use home/work appliances and devices and also reach certain…
A subjective expected utility policy making centre, managing complex, dynamic systems, needs to draw on the expertise of a variety of disparate panels of experts and integrate this information coherently. To achieve this, diverse supporting…
Energy efficient buildings require high quality standards for all their technical equipment to enable their efficient and successful operation and management. Building simulations enable engineers to design integrated HVAC systems with…
Building energy modeling plays a vital role in optimizing the operation of building energy systems by providing accurate predictions of the building's real-world conditions. In this context, various techniques have been explored, ranging…
This report presents our SmartSpace event handling framework for managing smart-grids and renewable energy installations. SmartSpace provides decision support for human stakeholders. Based on different datasources that feed into our…
This study exploits information fusion in IoT systems and uses a clustering method to identify similarities in behaviours and key characteristics within each cluster. This approach facilitates early detection of behaviour changes and…
The combination of Internet of Things (IoT) and Edge Computing (EC) can assist in the delivery of novel applications that will facilitate end users activities. Data collected by numerous devices present in the IoT infrastructure can be…
In this paper, the modeling of building end-use energy profile is comprehensively investigated. Top-down and Bottom-up approaches are discussed with a focus on the latter for better integration with occupant information. Compared to the…
This paper examines how decentralized energy systems can be enhanced using collaborative Edge Artificial Intelligence. Decentralized grids use local renewable sources to reduce transmission losses and improve energy security. Edge AI…
Renewables are key enablers in the plight to reduce greenhouse gas emissions and cope with anthropogenic global warming. The intermittent nature and limited storage capabilities of renewables culminate in new challenges that power system…
Data center providers seek to minimize their total cost of ownership (TCO), while power consumption has become a social concern. We present formulations to minimize server energy consumption and server cost under three different data center…
Users often have to integrate information about entities from multiple data sources. This task is challenging as each data source may represent information about the same entity in a distinct form, e.g., each data source may use a different…
The recent advances in artificial intelligence namely in machine learning and deep learning, have boosted the performance of intelligent systems in several ways. This gave rise to human expectations, but also created the need for a deeper…
Energy consumption reserves a large portion of the budget for school buildings. At the same time, the students that use such facilities are the adults of the years to come and thus, should they embrace energy-aware behaviors, then…
Next activity prediction in predictive business process monitoring is crucial for operational efficiency and informed decision-making. While machine learning and Artificial Intelligence have achieved promising results, challenges remain in…
AI4EF, Artificial Intelligence for Energy Efficiency, is an advanced, user-centric tool designed to support decision-making in building energy retrofitting and efficiency optimization. Leveraging machine learning (ML) and data-driven…