Related papers: Active Collaborative Sensing for Energy Breakdown
Non-intrusive load monitoring (NILM) focuses on disaggregating total household power consumption into appliance-specific usage. Many advanced NILM methods are based on neural networks that typically require substantial amounts of labeled…
The need for reducing our energy consumption footprint and the increasing number of electric devices in today's homes is calling for new solutions that allow users to efficiently manage their energy consumption. Real-time feedback at device…
Residential smart meters have been widely installed in urban houses nationwide to provide efficient and responsive monitoring and billing for consumers. Studies have shown that providing customers with device-level usage information can…
The data collected by smart meters contain a lot of useful information. One potential use of the data is to track the energy consumptions and operating statuses of major home appliances.The results will enable homeowners to make sound…
This paper describes the design, implementation, and testing of a wireless sensor and actuator network for monitoring the energy use of electric appliances in a home environment. The network includes energy measurement nodes and a central…
With the growth of smart building applications, occupancy information in residential buildings is becoming more and more significant. In the context of the smart buildings' paradigm, this kind of information is required for a wide range of…
Energy disaggregation is the task of segregating the aggregate energy of the entire building (as logged by the smartmeter) into the energy consumed by individual appliances. This is a single channel (the only channel being the smart-meter)…
Electricity consumed by residential consumers counts for a significant part of global electricity consumption and utility companies can collect high-resolution load data thanks to the widely deployed advanced metering infrastructure. There…
As sensor networks for health monitoring become more prevalent, so will the need to control their usage and consumption of energy. This paper presents a method which leverages the algorithm's performance and energy consumption. By utilising…
Energy disaggregation, a.k.a. Non-Intrusive Load Monitoring, aims to separate the energy consumption of individual appliances from the readings of a mains power meter measuring the total energy consumption of, e.g. a whole house. Energy…
Human population are striving against energy-related issues that not only affects society and the development of the world, but also causes global warming. A variety of broad approaches have been developed by both industry and the research…
Active sensing refers to the process of choosing or tuning a set of sensors in order to track an underlying system in an efficient and accurate way. In a wireless environment, among the several kinds of features extracted by traditional…
Internet of Things forms the backbone of modern building applications. Wireless sensors are being increasingly adopted for their flexibility and reduced cost of deployment. However, most wireless sensors are powered by batteries today and…
Energy disaggregation in a non-intrusive way estimates appliance level electricity consumption from a single meter that measures the whole house electricity demand. Recently, with the ongoing increment of energy data, there are many…
Energy disaggregation is a promising solution to access detailed information on energy consumption in a household, by itemizing its total energy consumption. However, in real-world applications, overfitting remains a challenging problem for…
A smart home energy dataset that records miscellaneous energy consumption data is publicly offered. The proposed energy activity dataset (EAD) has a high data type diversity in contrast to existing load monitoring datasets. In EAD, a simple…
This paper discusses how usage patterns and preferences of inhabitants can be learned efficiently to allow smart homes to autonomously achieve energy savings. We propose a frequent sequential pattern mining algorithm suitable for real-life…
Energy disaggregation is to discover the energy consumption of individual appliances from their aggregated energy values. To solve the problem, most existing approaches rely on either appliances' signatures or their state transition…
An effective way to oppose global warming and mitigate climate change is to electrify our energy sectors and supply their electric power from renewable wind and solar. Spatio-temporal predictions of electric load become increasingly…
Given its substantial contribution of 40\% to global power consumption, the built environment has received increasing attention to serve as a source of flexibility to assist the modern power grid. In that respect, previous research mainly…