Jove
Visualize
Contact Us

Related Concept Videos

Types of Global Positioning System Surveys01:30

Types of Global Positioning System Surveys

53
GPS surveying methods vary in application, accuracy, and data collection techniques, catering to diverse surveying and mapping needs. Static GPS, kinematic GPS, and real-time kinematic (RTK) surveying are widely used. Each technique offers distinct advantages.Static GPS involves placing one receiver at a known reference point and another at the target point. It collects exact positional data by observing multiple satellite ranges over an extended period, achieving centimeter-level accuracy for...
53

You might also read

Related Articles

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

Sort by
Same author

LoRa-Based IoT Network Assessment in Rural and Urban Scenarios.

Sensors (Basel, Switzerland)·2023
Same author

Secure Polar Coding for the Primitive Relay Wiretap Channel.

Entropy (Basel, Switzerland)·2021
Same author

Optimization of Ultra-Dense Wireless Powered Networks.

Sensors (Basel, Switzerland)·2021
Same author

Game Theoretic Honeypot Deployment in Smart Grid.

Sensors (Basel, Switzerland)·2020
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 Experiment Video

Updated: Jun 15, 2025

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

2.7K

Passive Radar Sensing for Human Activity Recognition: A Survey.

Foteini Savvidou1, Sotiris A Tegos1, Panagiotis D Diamantoulakis1

  • 1Department of Electrical and Computer EngineeringAristotle University of Thessaloniki 54124 Thessaloniki Greece.

IEEE Open Journal of Engineering in Medicine and Biology
|August 26, 2024
PubMed
Summary
This summary is machine-generated.

This survey explores using passive radar for unobtrusive human activity recognition (HAR) in homes. It highlights radar

Keywords:
Activity recognitionassisted livinge-healthpassive radarwireless sensing

More Related Videos

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
06:49

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

8.9K
Harmonic Radar Tags for Insect Tracking: Lightweight, Low-cost, and Accessible
14:44

Harmonic Radar Tags for Insect Tracking: Lightweight, Low-cost, and Accessible

Published on: May 13, 2025

389

Related Experiment Videos

Last Updated: Jun 15, 2025

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

2.7K
Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
06:49

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

8.9K
Harmonic Radar Tags for Insect Tracking: Lightweight, Low-cost, and Accessible
14:44

Harmonic Radar Tags for Insect Tracking: Lightweight, Low-cost, and Accessible

Published on: May 13, 2025

389

Area of Science:

  • * Engineering and Computer Science: Focuses on signal processing, machine learning, and sensor technology for human activity recognition (HAR).

Background:

  • * Current human activity recognition (HAR) systems often rely on wearable devices or video surveillance, posing challenges related to user compliance and privacy concerns.
  • * Continuous monitoring is crucial for enhancing the quality of life and supporting independent living for the elderly and individuals with chronic conditions.

Purpose of the Study:

  • * To survey passive radar system architectures, signal processing, feature extraction, and machine learning applications for non-intrusive human activity sensing.
  • * To identify challenges and propose future research directions in wireless human activity sensing.

Main Methods:

  • * Overview of passive radar system architectures and signal processing techniques for HAR.
  • * Exploration of feature extraction methods and the role of machine learning in analyzing radar data for activity recognition.
  • * Discussion of leveraging existing communication systems (e.g., Wi-Fi) as illuminators of opportunity.

Main Results:

  • * Passive radar offers a privacy-preserving and non-intrusive alternative to existing HAR solutions.
  • * Integration of signal processing and machine learning is key to effective activity recognition using radar data.
  • * Existing communication infrastructure can be repurposed for sensing applications.

Conclusions:

  • * Passive radar technology holds significant potential for unobtrusive, long-term human activity recognition in domestic environments.
  • * Addressing challenges such as robustness, privacy, and multi-user scenarios is essential for widespread adoption.
  • * Future research should focus on the coexistence of sensing and communication, and the development of open datasets to advance the field.