Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Classification of Systems-I01:26

Classification of Systems-I

348
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
348
Design Example: Sustainability in Concrete Building01:26

Design Example: Sustainability in Concrete Building

238
As the construction industry moves towards more eco-friendly practices, concrete's adaptability and its ability to incorporate sustainable features make it a key material in the drive towards greener building solutions.
There are multiple approaches to achieve sustainability in a commercial concrete building. For instance, construct a concrete parking area under the building, utilizing pervious concrete paver blocks in open areas to facilitate rainwater collection through an underground...
238
Classification of Systems-II01:31

Classification of Systems-II

253
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
253
Energy and Power Signals01:17

Energy and Power Signals

703
In an electrical system with a resistor, voltage and current signals facilitate the measurement of power and energy across the resistor. For a continuous-time signal, the total energy over a time interval is defined as the integral of the square of the signal's magnitude over that interval. Mathematically, this is expressed as:
703
Energy Conservation and Bernoulli's Equation01:16

Energy Conservation and Bernoulli's Equation

9.6K
Applying the conservation of energy principle or the work-energy theorem to an incompressible, inviscid fluid in laminar, steady, irrotational flow leads to Bernoulli's equation. It states that the sum of the fluid pressure, potential, and kinetic energy per unit volume is constant along a streamline.
All the terms in the equation have the dimension of energy per unit volume. The kinetic energy per unit volume is called the kinetic energy density, and the potential energy per unit volume is...
9.6K
Distribution Reliability and Automation01:25

Distribution Reliability and Automation

173
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
173

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Alcohol Advertising Across Spanish and English Television and Radio Networks in New York City.

Journal of urban health : bulletin of the New York Academy of Medicine·2025
Same author

Identification of Olives Using In-Field Hyperspectral Imaging with Lightweight Models.

Sensors (Basel, Switzerland)·2024
Same author

Data Acquisition for Condition Monitoring in Tactical Vehicles: On-Board Computer Development.

Sensors (Basel, Switzerland)·2023
Same author

A General-Purpose Distributed Analytic Platform Based on Edge Computing and Computational Intelligence Applied on Smart Grids.

Sensors (Basel, Switzerland)·2023
Same author

Design and Evaluation of a Heterogeneous Lightweight Blockchain-Based Marketplace.

Sensors (Basel, Switzerland)·2022
Same author

Surgical-orthodontic retreatment of a severe skeletal Class III malocclusion following an orthodontic camouflage.

Dental press journal of orthodontics·2021

Related Experiment Video

Updated: Oct 2, 2025

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
10:36

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Published on: November 3, 2023

1.7K

Decision Support System to Classify and Optimize the Energy Efficiency in Smart Buildings: A Data Analytics Approach.

Manuel Peña1, Félix Biscarri1, Enrique Personal1

  • 1Electronic Technology Department, School of Computer Science and Engineering, University of Seville, Av. Reina Mercedes S/N, 41012 Seville, Spain.

Sensors (Basel, Switzerland)
|February 26, 2022
PubMed
Summary

This study introduces an intelligent data analysis method for smart building energy efficiency. It uses Data Analytics (DA) to create a Decision Support System (DSS) for optimizing energy use and detecting anomalies.

Keywords:
data analyticsdecision support systemenergy efficiencyenergy optimizationsmart building

More Related Videos

Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.9K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

4.3K

Related Experiment Videos

Last Updated: Oct 2, 2025

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
10:36

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Published on: November 3, 2023

1.7K
Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.9K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

4.3K

Area of Science:

  • Building Energy Management
  • Data Science Applications
  • Smart Building Technology

Background:

  • Smart buildings generate vast amounts of data crucial for operational efficiency.
  • Optimizing energy efficiency in buildings is a key challenge for sustainability and cost reduction.
  • Existing methods may lack the sophistication to identify subtle patterns and anomalies in energy consumption.

Purpose of the Study:

  • To propose an intelligent data analysis method for modeling and optimizing energy efficiency in smart buildings.
  • To develop a Decision Support System (DSS) for experts to quantify and enhance building energy efficiency.
  • To enable early detection of anomalous behaviors impacting energy consumption.

Main Methods:

  • Utilizing Data Analytics (DA) on historical building data and Energy Efficiency Indicators (EEIs).
  • Extracting knowledge from behavioral patterns to develop a classification method for diverse daily features and seasons.
  • Analyzing clusters to infer key features for predicting and quantifying energy efficiency.

Main Results:

  • The method successfully analyzed historical data to identify behavioral patterns.
  • A classification approach was developed to compare and group days based on various characteristics.
  • Key features were inferred to predict energy efficiency for similar but potentially different daily behaviors.
  • Insights were revealed highlighting inefficiencies and correlating anomalous behaviors with energy efficiency (EE).

Conclusions:

  • The proposed intelligent data analysis method provides valuable insights for smart building energy management.
  • The Decision Support System (DSS) aids experts in optimizing energy efficiency and detecting anomalies.
  • The approach demonstrated effectiveness on the BlueNet building and integration with commercial tools like Eugene.