Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Absolute Motion Analysis- General Plane Motion

Absolute Motion Analysis- General Plane Motion

Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the...

You might also read

Related Articles

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

Sort by

Same author

SMS Scam Detection Application Based on Optical Character Recognition for Image Data Using Unsupervised and Deep Semi-Supervised Learning.

Sensors (Basel, Switzerland)·2024

Same author

A Framework for Prediction of Oncogenomic Progression Aiding Personalized Treatment of Gastric Cancer.

Diagnostics (Basel, Switzerland)·2023

Same author

Multi-population Black Hole Algorithm for the problem of data clustering.

PloS one·2023

Same author

Diabetes disease prediction system using HNB classifier based on discretization method.

Journal of integrative bioinformatics·2023

Same author

An AI-Inspired Spatio-Temporal Neural Network for EEG-Based Emotional Status.

Sensors (Basel, Switzerland)·2023

Same author

Review of Learning-Based Robotic Manipulation in Cluttered Environments.

Sensors (Basel, Switzerland)·2022

Search research articles

Related Experiment Video

Updated: Aug 29, 2025

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Published on: August 27, 2021

A Comprehensive Collection and Analysis Model for the Drone Forensics Field.

Fahad Mazaed Alotaibi¹, Arafat Al-Dhaqm², Yasser D Al-Otaibi³

¹Faculty of Computing and Information Technology (FCIT), King Abdulaziz University, Jeddah 22254, Saudi Arabia.

Sensors (Basel, Switzerland)

|September 9, 2022

Summary

This summary is machine-generated.

This study introduces a new comprehensive collection and analysis forensic model (CCAFM) for unmanned aerial vehicles (UAVs). CCAFM provides a standardized approach for drone forensics, ensuring evidence integrity and aiding criminal investigations.

Keywords:

UAV design science research drone forensics smart cities

More Related Videos

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Published on: February 25, 2021

Related Experiment Videos

Last Updated: Aug 29, 2025

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Published on: August 27, 2021

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Published on: February 25, 2021

Area of Science:

Computer Science
Digital Forensics
Cybersecurity

Background:

Unmanned aerial vehicles (UAVs) are increasingly used in smart cities for tasks like traffic monitoring and public safety.
Drone-based evidence is crucial, necessitating effective forensic processes for collection and analysis.
Current drone forensic models are often scenario-specific, lacking standardization and a unified approach.

Purpose of the Study:

To address the lack of a standardized model in drone forensics.
To propose a novel, comprehensive collection and analysis forensic model (CCAFM) for UAVs.
To review machine learning applications and existing forensic models in drone data analysis.

Main Methods:

Literature review of machine learning in drone data analysis for criminal actions.
Analysis of existing drone forensic models.
Application of the design science research approach to develop the CCAFM.

Main Results:

Identified limitations in current drone forensic models, highlighting the need for standardization.
Developed the Comprehensive Collection and Analysis Forensic Model (CCAFM).
CCAFM integrates acquisition, preservation, reconstruction, analysis, and post-investigation processes for drone evidence.

Conclusions:

The proposed CCAFM offers a standardized, comprehensive framework for digital forensic investigators handling drone evidence.
CCAFM ensures the integrity of volatile and non-volatile data from UAVs using scientific forensic techniques.
This model facilitates knowledge sharing and improves drone forensic investigation practices.