View Proposal

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Proposer

Drishty Sobnath

Title

PPE Detection with Computer Vision AI

Goal

The main aim of the project is to enforce PPE compliance in the workplace by using computer vision techniques at the workplace to increase work safety and reduce accidents and fatalities at a work site. Employers also avoid additional insurance costs in the long-term.

Description

Industrial and manufacturing are two of the most high-risk sectors for workers. According to the U.S. Bureau of Labor Statistics, there were 2.8 million nonfatal workplace injuries and illnesses in 2019. This includes over 400,000 nonfatal injuries and illnesses in the manufacturing sector. Safety is of paramount concern for both employees and employers at any workplace, and the wearing of Personal Protective Equipment (PPE) like helmets, gloves, masks, vests, etc., by workers is a cornerstone of workplace safety. By analyzing images/videos, the project will explore how computer vision can be used to create safer workplaces by ensuring PPE compliance and detecting any violations in real-time.

Resources

Python programming, Statistical modelling, Computer Vision, Machine learning, PPE safety documentation, Data Science

Background

Url

Difficulty Level

Variable

Ethical Approval

None

Number Of Students

1

Supervisor

Drishty Sobnath

Keywords

Degrees

Bachelor of Science in Computer Science
Bachelor of Science in Computer Systems
Master of Engineering in Software Engineering
Master of Science in Artificial Intelligence
Master of Science in Computing (2 Years)
Master of Science in Data Science
Master of Science in Information Technology (Software Systems)
Master of Science in Software Engineering
Bachelor of Science in Computing Science
Postgraduate Diploma in Artificial Intelligence
Bachelor of Science in Statistical Data Science