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

Pipe Flowrate Measurement01:28

Pipe Flowrate Measurement

1.1K
In pipe flow measurement, orifice, nozzle, and Venturi meters are commonly used to determine fluid flowrates by constricting the flow area, which increases fluid velocity and reduces pressure. This pressure difference, governed by Bernoulli's principle and adjusted for real-world conditions, is essential for calculating flowrate. Each meter type is suited to specific applications based on accuracy, efficiency, and compatibility with various flow conditions.
The orifice meter is a simple,...
1.1K
Measurement of Fluid Pressure01:16

Measurement of Fluid Pressure

563
Fluid pressure is commonly measured using devices called manometers, which rely on liquid columns to indicate pressure differences. The height of a liquid column in a manometer reflects the pressure exerted by the fluid, providing a simple yet effective means of measurement. Different types of manometers serve specific purposes based on their configurations and the type of fluids involved.
A basic form of manometer is the piezometer, a vertical tube open at the top and filled with the same...
563
Pipe Flowrate Measurement: Problem Solving01:28

Pipe Flowrate Measurement: Problem Solving

785
A spray tank system is engineered to uniformly distribute a pest-control liquid across plants by using a pressurized mechanism. The tank, pressurized to 150 kPa, holds the pesticide at a height of 0.80 meters. Liquid flows from the tank through a 1.9 meter pipe with a diameter of 0.015 meters, angled at 0.698 radians, ultimately reaching a 0.007 meter nozzle that sprays the pesticide. Accurate calculation of the system's flow rate is crucial to ensure uniform application, and this is achieved...
785
Multiple Pipe Systems01:21

Multiple Pipe Systems

1.1K
Multipipe systems consist of complex configurations of interconnected pipes designed to transport fluids efficiently across intricate networks. They are essential in engineering applications requiring precise control over flow distribution, pressure, and head loss. They are categorized into series, parallel, loop, and network configurations, each distinguished by unique flow characteristics and applications.
Series Configuration
In a series configuration, fluid flows sequentially from one pipe...
1.1K
Pressure of Fluids01:14

Pressure of Fluids

21.4K
There are many examples of pressure in fluids in everyday life, such as in relation to blood (high or low blood pressure) and in relation to weather (high- and low-pressure weather systems). A given force can have a significantly different effect, depending on the area over which the force is exerted. For instance, a force applied to an area of 1 mm2 has a pressure that is 100 times greater than the same force applied to an area of 1 cm2. That's why a sharp needle is able to poke through...
21.4K
Fluid Pressure01:14

Fluid Pressure

1.1K
In mechanical engineering, fluid pressure plays a critical role in designing systems that utilize liquid flow, such as hydraulic systems, pumps, and valves. When designing these systems, engineers must ensure they can withstand the forces created by fluid pressure to avoid damage or failure.
According to Pascal's law, a fluid at rest will generate equal pressure in all directions. This pressure is measured as a force per unit area, and its magnitude depends on the fluid's specific...
1.1K

You might also read

Related Articles

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

Sort by
Same author

User-Centric Cell-Free Massive Multiple-Input-Multiple-Output System with Noisy Channel Gain Estimation and Line of Sight: A Beckmann Distribution Approach.

Entropy (Basel, Switzerland)·2025
Same author

A Novel Design of a Torsional Shape Memory Alloy Actuator for Active Rudder.

Sensors (Basel, Switzerland)·2024
Same author

Solar Tracking Control Algorithm Based on Artificial Intelligence Applied to Large-Scale Bifacial Photovoltaic Power Plants.

Sensors (Basel, Switzerland)·2024
Same author

Uncertainty Evaluation of a Gas Turbine Model Based on a Nonlinear Autoregressive Exogenous Model and Monte Carlo Dropout.

Sensors (Basel, Switzerland)·2024
Same author

System Identification Methodology of a Gas Turbine Based on Artificial Recurrent Neural Networks.

Sensors (Basel, Switzerland)·2023
Same author

Fuzzy Control of Pressure in a Water Supply Network Based on Neural Network System Modeling and IoT Measurements.

Sensors (Basel, Switzerland)·2022

Related Experiment Video

Updated: Jan 9, 2026

High-precision Electromagnetic Flowmeter with Empty Pipe Detection via Complex Programmable Logic Device-based Waveform Recognition
05:11

High-precision Electromagnetic Flowmeter with Empty Pipe Detection via Complex Programmable Logic Device-based Waveform Recognition

Published on: June 27, 2025

596

Smart Water Management: An Energetically Autonomous IoT-Based Application for Pressure and Flow Monitoring in Water

Jonatha B Silva1, Lucas D de Oliveira1, Rafael M Duarte2

  • 1Renewable and Alternatives Energies Center (CEAR), Electrical Engineering Department (DEE), Campus I, Federal University of Paraiba (UFPB), João Pessoa 58051-900, Brazil.

Sensors (Basel, Switzerland)
|December 11, 2025
PubMed
Summary

This study developed an autonomous Internet of Things (IoT) node for monitoring water pressure and flow in urban supply networks. The collected data trains artificial neural networks to accurately predict real-time water flow.

Keywords:
TEDAartificial neural networksinternet of thingsoutlierwater supply

More Related Videos

Vegetated Treatment Systems for Removing Contaminants Associated with Surface Water Toxicity in Agriculture and Urban Runoff
08:49

Vegetated Treatment Systems for Removing Contaminants Associated with Surface Water Toxicity in Agriculture and Urban Runoff

Published on: May 15, 2017

11.1K
Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds
06:37

Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds

Published on: November 13, 2017

9.6K

Related Experiment Videos

Last Updated: Jan 9, 2026

High-precision Electromagnetic Flowmeter with Empty Pipe Detection via Complex Programmable Logic Device-based Waveform Recognition
05:11

High-precision Electromagnetic Flowmeter with Empty Pipe Detection via Complex Programmable Logic Device-based Waveform Recognition

Published on: June 27, 2025

596
Vegetated Treatment Systems for Removing Contaminants Associated with Surface Water Toxicity in Agriculture and Urban Runoff
08:49

Vegetated Treatment Systems for Removing Contaminants Associated with Surface Water Toxicity in Agriculture and Urban Runoff

Published on: May 15, 2017

11.1K
Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds
06:37

Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds

Published on: November 13, 2017

9.6K

Area of Science:

  • Environmental Engineering
  • Water Resource Management
  • Sensor Networks

Background:

  • Urban water distribution faces challenges in pipeline maintenance, pressure/flow control, and water quality monitoring.
  • Accurate measurement of flow rate and pressure is crucial for optimizing city water distribution systems.
  • Emerging technologies like smart sensors and wireless sensor networks offer solutions to these challenges.

Purpose of the Study:

  • To detail the development of an autonomous Internet of Things (IoT) node for monitoring pressure and flow in water supply networks.
  • To address the challenges and present solutions for creating such an IoT node.
  • To utilize collected data for predicting system flow using artificial neural networks.

Main Methods:

  • Development of a low-cost, autonomous IoT node with low energy consumption for real-time data communication over the Internet.
  • Data preprocessing to remove outliers from measurements collected by IoT nodes.
  • Training an artificial neural network model using the processed data to predict water flow.

Main Results:

  • The developed IoT node successfully collects pressure and flow data from water supply networks.
  • The artificial neural network model, trained on IoT data, demonstrates the capability to predict system flow.
  • The study validates the feasibility of using IoT nodes for real-time flow prediction in urban water distribution.

Conclusions:

  • Autonomous IoT nodes provide a viable, low-cost solution for monitoring urban water distribution systems.
  • The integration of IoT data with artificial neural networks enables accurate real-time flow prediction.
  • This technology enhances the efficiency and management of water supply networks.