SELLYWARE SOFTWARE FOR INDUSTRIAL SAFETY EQUIPMENT DETECTION

Introduction:

Many people work at job sites under unsafe conditions and thousands of them lose their lives every year. Actually, the U.S. construction industry suffers from the highest number of fatalities among all industries, i.e., one out of five workers who died in the private industry in 2014 were from the construction industry.
In most of the fall incidents, the workers fall from heights and hit their heads on hard floors. In one study that investigated the number of construction fatalities and the use of safety equipment, the results showed that 47.3% of fatally injured victims either had not used safety equipment (e.g., helmet, Shoes, Gloves, Glass, etc.) or had not used them properly.
Since the head is the most critical area of a human body and is the most vulnerable to an impact that could cause serious injury or death. The use of a protective helmet in a construction worksite is required. However, the construction workers would not always follow the Occupational Safety and Health Administration (OSHA) Regulations to wear head protection (e.g., helmet) whenever OSHA regulations require that they do so (e.g., under conditions of elevation). Therefore, methods to improve safety performance measurement on construction sites is of paramount importance.

What Sellyware Software Does:

Our Sellyware Software is developed in Artificial Intelligence Technology. It uses the latest Vision-Based Artificial Intelligence (AI) Technology and detects the set of equipment/clothes which are mandatory to wear by the workers while on site. Using our Sellyware software, the manager or the moderator will be able to detect the person not wearing particular mandatory clothes/equipment.

Applications:
• Construction Sites
• Power Plants.
• During Electricity Work.
• Factory and heavy industries.
• Hotels (kitchen)
• Hospitals

Features:
• Safety Helmet Detection
• Safety Hand Gloves Detection
• Safety shoe Detection
• Safety Glass Detection

Future Enhancement:

Currently, our system can detect helmets, Gloves, Shoes, and glasses. As an extension of this work, we aim to make the system scalable to detect helmets with other colors.
In the future, the system will be made well capable of differentiating between normal cap and helmet, as the proposed system shows low performance in this case. Also, we aim to apply some deep learning techniques for
improving the overall accuracy of the system. Also, applying the upper body searching algorithm instead of detecting while humans as an object of interest can improve helmet detection accuracy.

Advantages:

• Safety of Personal Working On The Sites.
• Protecting From Fatal Accidents.
• Managing Employee Health and Protection
• Safety Over Some Things That Hurt on Head.
• Time Saver.
• Overhead Cost Reduction.
• It can work 24 x 7
• It Can Work In Any Type Of Dynamic Environments.
• Social And Corporate Responsibility.

FAQs:
(1) What should be the cost of the project?
• Cost For this project will be less as compared to others.
(2) What should be Equipment used?
• High configuration Computer
• Sufficient Training Data set
• High-Resolution AI camera
(3) Where We Can Use This Application?
• This is used to detect if the workers are wearing their safety equipment or not.