Related papers: Analysis and Knowledge Discovery from Sensors Data…
With the press of global climate change, extreme weather and sudden weather changes are becoming increasingly common. To maintain a comfortable indoor environment and minimize the contribution of the building to climate change as much as…
Buildings form an essential part of modern life; people spend a significant amount of their time in them, and they consume large amounts of energy. A variety of systems provide services such as lighting, air conditioning and security which…
Buildings consume over 40% of the total energy in modern societies, and improving their energy efficiency can significantly reduce our energy footprint. In this paper, we present \texttt{WattScale}, a data-driven approach to identify the…
We propose in this paper to study the energy-, thermal- and performance-aware resource management in heterogeneous datacenters. Witnessing the continuous development of heterogeneity in datacenters, we are confronted with their different…
This report considers the class of applications of sensor networks in which each sensor node makes measurements, such as temperature or humidity, at the precise location of the node. Such spot-sensing applications approximate the physical…
Rapid advancements in the Internet of Things (IoT) have facilitated more efficient deployment of smart environment solutions for specific user requirement. With the increase in the number of IoT devices, it has become difficult for the user…
A number of governments and organizations around the world agree that the first step to address national and international problems such as energy independence, global warming or emergency resilience, is the redesign of electricity…
Research on energy efficiency of today's buildings focuses on the monitoring of a building's behavior while in operation. But without a formalized description of the data measured, including their correlations and in particular the expected…
This paper addresses the use of smart-home sensor streams for continuous prediction of energy loads of individual households which participate as an agent in local markets. We introduces a new device level energy consumption dataset…
Enabling deep penetration of distributed energy resources (DERs) requires comprehensive monitoring and control of the distribution network. Increasing observability beyond the substation and extending it to the edge of the grid is required…
The development of current building energy system operation has benefited from: 1. Informational support from the optimal design through simulation or first-principles models; 2. System load and energy prediction through machine learning…
Energy systems generate vast amounts of data in extremely short time intervals, creating challenges for efficient data management. Traditional data management methods often struggle with scalability and accessibility, limiting their…
Before a building can participate in a demand response program, its facility managers must characterize the site's ability to reduce load. Today, this is often done through manual audit processes and prototypical control strategies. In this…
The Internet of Things (IoT) has important applications in our daily lives including health and fitness tracking, environmental monitoring and transportation. However, sensor nodes in IoT suffer from the limited lifetime of batteries…
Context: Information Technology consumes up to 10\% of the world's electricity generation, contributing to CO2 emissions and high energy costs. Data centers, particularly databases, use up to 23% of this energy. Therefore, building an…
Due to recent advancements in machine learning, recommender systems use increasingly more energy for training, evaluation, and deployment. However, the recommender systems community often does not report the energy consumption of their…
Due to growing population and technological advances, global electricity consumption, and consequently also CO2 emissions are increasing. The residential sector makes up 25% of global electricity consumption and has great potential to…
Smart meters are increasingly used worldwide. Smart meters are the advanced meters capable of measuring energy consumption at a fine-grained time interval, e.g., every 15 minutes. Smart meter data are typically bundled with social economic…
The paper describes a dataset comprising indoor environmental factors such as temperature, humidity, air quality, and noise levels. The data was collected from 10 sensing devices installed in various locations within three single-family…
Smart grids technologies are enablers of new business models for domestic consumers with local flexibility (generation, loads, storage) and where access to data is a key requirement in the value stream. However, legislation on personal data…