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

Threats to Biodiversity

Threats to Biodiversity

There have been five major extinction events throughout geological history, resulting in the elimination of biodiversity, followed by a rebound of species that adapted to the new conditions. In the current geological epoch, the Holocene, there is a sixth extinction event in progress. This mass extinction has been attributed to human activities and is thus provisionally called the Anthropocene. In 2019 the human population reached 7.7 billion people and is projected to comprise 10 billion by...

Elastic Collisions: Case Study

Elastic Collisions: Case Study

Elastic collision of a system demands conservation of both momentum and kinetic energy. To solve problems involving one-dimensional elastic collisions between two objects, the equations for conservation of momentum and conservation of internal kinetic energy can be used. For the two objects, the sum of momentum before the collision equals the total momentum after the collision. An elastic collision conserves internal kinetic energy, and so the sum of kinetic energies before the collision equals...

You might also read

Related Articles

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

Sort by

Same author

Radio Astronomical Antennas in the Central African Region to Improve the Sampling Function of the VLBI Network in the SKA Era?

Sensors (Basel, Switzerland)·2022

Same author

Transfer Learning for the Detection and Diagnosis of Types of Pneumonia including Pneumonia Induced by COVID-19 from Chest X-ray Images.

Diagnostics (Basel, Switzerland)·2021

See all related articles

Search research articles

Related Experiment Video

Updated: Sep 27, 2025

A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents

A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents

Published on: May 16, 2025

Intelligent Systems Using Sensors and/or Machine Learning to Mitigate Wildlife-Vehicle Collisions: A Review,

Irene Nandutu¹, Marcellin Atemkeng¹, Patrice Okouma¹

¹Department of Mathematics, Rhodes University, Artillery Rd., Grahamstown 6139, South Africa.

Sensors (Basel, Switzerland)

|April 12, 2022

Summary

Wildlife-vehicle collisions (WVCs) cause significant losses. This review finds that current animal detection systems often lack advanced machine learning and datasets, hindering WVC mitigation efforts.

Keywords:

animal behavior animal detection systems human behavior human–wildlife intelligent systems machine learning machine learning datasets sensor wildlife–vehicle collisions

More Related Videos

A Novel Single Animal Motor Function Tracking System Using Simple, Readily Available Software

A Novel Single Animal Motor Function Tracking System Using Simple, Readily Available Software

Published on: August 31, 2018

A Precise and Autonomous System for the Detection of Insect Emergence Patterns

A Precise and Autonomous System for the Detection of Insect Emergence Patterns

Published on: January 9, 2019

Related Experiment Videos

Last Updated: Sep 27, 2025

A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents

A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents

Published on: May 16, 2025

A Novel Single Animal Motor Function Tracking System Using Simple, Readily Available Software

A Novel Single Animal Motor Function Tracking System Using Simple, Readily Available Software

Published on: August 31, 2018

A Precise and Autonomous System for the Detection of Insect Emergence Patterns

A Precise and Autonomous System for the Detection of Insect Emergence Patterns

Published on: January 9, 2019

Area of Science:

Environmental Science
Computer Science
Transportation Engineering

Background:

Wildlife-vehicle collisions (WVCs) pose a global threat to human safety, wildlife populations, and property.
Mitigation strategies for WVCs are increasingly adopting Artificial Intelligence (AI) due to its versatility and efficiency.

Purpose of the Study:

To systematically review and bibliometrically analyze intelligent systems for WVC mitigation.
To investigate factors contributing to human-wildlife conflicts and evaluate current datasets and machine learning approaches.

Main Methods:

Systematic literature review.
Bibliometric analysis of intelligent systems for WVC mitigation.
Investigation of contributing factors, datasets, and machine learning techniques.

Main Results:

Most animal detection systems (excluding autonomous vehicles) do not utilize state-of-the-art datasets or recent machine learning breakthroughs.
Current systems face challenges including failure to detect hotspot areas and limitations in training data.

Conclusions:

Adopting the latest datasets and machine learning techniques can significantly improve animal detection accuracy and reduce false positives.
Future research should focus on real-time animal detection algorithms and developing robust systems within a continuous product development lifecycle.