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Journal ArticleDOI

Continuous monitoring of power consumption in urban buildings based on Internet of Things

TLDR
A large portion of energy consumption in buildings is due to improper use of electrical equipment, and energy efficiency in buildings has become a priority at every level within the building industry.
Abstract
Buildings consume a large portion of energy; the major consumption is due to improper use of electrical equipment. Thus, energy efficiency in buildings has become a priority at every level within t...

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Citations
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A novel design of switched boost action based multiport converter using dsPIC controller for renewable energy applications

TL;DR: In this article, the grid supplies only a particular voltage to the load, but today we are using n' number of loads with different voltage rating and converters, so, the conversion of the generated A...
Journal ArticleDOI

A machine-learning ensemble model for predicting energy consumption in smart homes

TL;DR: In this paper , the authors performed an overall analysis of energy consumption in smart homes by deploying machine learning models, such as Decision Trees (DT), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and k-Nearest Neighbor (KNN) for predicting the power consumption of multiple datasets.
Journal ArticleDOI

Implementation of Buckingham's Pi theorem using Python

TL;DR: In this paper , a python-based function has been developed and reported in this manuscript, which can be used to evaluate Pi terms (commonly called π terms) for any fluid flow problem.
References
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Journal ArticleDOI

IoT Considerations, Requirements, and Architectures for Smart Buildings—Energy Optimization and Next-Generation Building Management Systems

TL;DR: The technical opportunities offered and the technical challenges faced by the IoT in the smart building arena are reviewed, including power over Ethernet, as part of an IoT-based solution, which offers disruptive opportunities in revolutionizing the in-building connectivity of a large swath of devices.
Journal ArticleDOI

Fog Computing May Help to Save Energy in Cloud Computing

TL;DR: It is shown that nano servers in Fog computing can complement centralized DCs to serve certain applications, mostly IoT applications for which the source of data is in end-user premises, and lead to energy saving if the applications are off-loadable from centralizedDCs and run on nDCs.
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Estimation of energy consumption in machine learning

TL;DR: Energy consumption has been widely studied in the computer architecture field for decades, and while the adoption of energy as a metric in machine learning is emerging, the majority of research is stil ...
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A new generation of AI: A review and perspective on machine learning technologies applied to smart energy and electric power systems

TL;DR: This survey focuses on introducing and summarizing the mainstream uses of seven representative ML methods, including reinforcement learning, deep learning, transfer learning, parallel learning, hybrid learning, adversarial learning, and ensemble learning, in the SG and EI fields.
Journal ArticleDOI

Energy-Centered and QoS-Aware Services Selection for Internet of Things

TL;DR: An energy-centered and QoS-aware services selection algorithm (EQSA) is proposed for IoT services composition and shows clearly the good performances of the EQSA algorithm in terms of selection time, energy efficiency, composition lifetime, and optimality and its added value in comparison with algorithms dealing separately with QoS and energy consumption.
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