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Occupancy inference using infrastructure elements in indoor environment: a multi-sensor data fusion
Gathering occupancy information in indoor environments has gained extensive research interest due to its potential use in energy savings, user...
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A Feature and Classifier Study for Appliance Event Classification
The shift towards advanced electricity metering infrastructure gained traction because of several smart meter roll-outs during the last decade. This...
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Residential electricity current and appliance dataset for AC-event detection from Indian dwellings
Air Conditioners (ACs) have become a major contributor to residential electricity consumption in India. Non-intrusive Load Monitoring (NILM) can be...
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Detecting Air Conditioning Usage in Households Using Unsupervised Machine Learning on Smart Meter Data
This article presents an unsupervised machine learning approach for the problem of detecting use of air conditioning in households, during the...
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Machine Learning Techniques for Regression in Energy Disaggregation
Non-Intrusive Load Monitoring (NILM) or Energy disaggregation may be the holy grail of energy efficiency. The impact of energy disaggregation at the...
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Load Quality Analysis and Forecasting for Power Data Set on Cloud Platform
In the era of big data, The prediction management system combined with cloud computing platform can start from massive structured, semi-structured...
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Gauging the utility of ambient displays by measuring cognitive load
Ambient Displays, a sub-class of ubiquitous computing, aim to present non-critical information using peripheral visualisation with minimal...
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Advances in Machine-Learning Based Disaggregation of Building Heating Loads: A Review
This review article investigates the methods proposed for disaggregating the space heating units’ load from the aggregate electricity load of...
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PUMPNET: a deep learning approach to pump operation detection
Non-urgent high energy-consuming residential appliances, such as pool pumps, may significantly affect the peak to average ratio (PAR) of energy...
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MFGAD-INT: in-band network telemetry data-driven anomaly detection using multi-feature fusion graph deep learning
As the cloud services market grows, cloud management tools that detect network anomalies in a non-intrusive manner are critical to improve users’...
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Towards measuring cognitive load through multimodal physiological data
Cognitive load plays an important role during learning and working, as it has been linked to well-functioning cognitive processes, performance,...
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Offline Runtime Verification
The fact that the monitoring and verification code shares and utilises resources which would have otherwise been exclusively available to the system...
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LstSim-Extended: Towards Monitoring Interaction and Beyond in Web-Based Control Room Simulations
Control room operators rely on a range of technologies to communicate crucial information and dependably coordinate a disparate collection of tasks...
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Intelligent energy aware approaches for residential buildings: state-of-the-art review and future directions
In the past decade, the world’s energy consumption is increasing largely, while residential buildings are the primary sector consuming about a...
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A Versatile High Frequency Electricity Monitoring Framework for Our Future Connected Home
In our homes a lot of devices are powered by electricity without us knowing the specific amount. As electricity production has a large, negative...
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Research on Residential Power Consumption Behavior Based on Typical Load Pattern
According to the current analysis of residents’ electricity consumption behavior, with the popularization of smart meters, to a certain extent,...
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NILM-based approach for energy efficiency assessment of household appliances
This paper presents a novel Non-Intrusive Load Monitoring (NILM) approach focusing on the Energy Efficiency (EE) assessment of residential...
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Towards a comprehensive damage identification of structures through populations of competing models
Model-based damage identification for structural health monitoring (SHM) remains an open issue in the literature. Along with the computational...
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Ergonomic Principles in Designing Assistive Systems
This investigation highlights the crucial application of ergonomic principles in the design of assistive systems, as outlined by the DIN EN 92419...
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Weakly Supervised Transfer Learning for Multi-label Appliance Classification
Non-intrusive Load Monitoring refers to the techniques for providing detailed information on appliances’ states or their energy consumption by...