Countable safety: facts and numbers about two opposite safety control approaches
Everyone knows that Personal Protective Equipment (PPE) plays a key role in preventing and reducing many occupational fatalities, injuries, infections and diseases resulting from a physical, mechanical, electrical, chemical or radiological contact and protects people against damage or death.
But the last US Bureau of Labor Statistics report says that 84% of head injuries were caused by not wearing a helmet. And 99% of workers who suffered facial injuries were not using face protection. 98% of workers said they have seen others not wearing PPE when they should have been and 30% of them said that it is normal practice. Look at the number below:
It is possible to prevent most of these injuries by implementing a system for monitoring of PPE compliance.
So what about automation?
PPE is the equipment developed to protect users against health or safety risks. It includes safety helmets, gloves, eye protection, hazmat suits, high-visibility clothing, safety footwear, safety harnesses, ear plugs, ear defenders and respiratory protective equipment (RPE).
Using PPE at a workplace strongly decreases the chances of injuries, infections and many other damages and financial losses due to fines for injuries and death of workers by not wearing gloves, hairnets, shoe covers, etc. The automation of PPE detection and control helps companies to reduce the risk of accidents to the employee, reduce employer liability, improve operational efficiency and provide analytics on the safety of the workplace.
AI automation collects and analyzes data for employers responsible for the safety of their staff. This allows not to waste a lot of time for manually monitoring work sites. Using ML algorithms in business and healthcare will reduce injury and incident rates by over 50%.
PPE is only needed where the hazard cannot be totally removed or controlled in such a way that damage is unlikely. For example, in cases when it is impossible to isolate the hazard or reduce the risk at source to an acceptable level.
There are several reasons for this approach:
PPE protects only the person using it, whereas measures controlling the risk at source can protect everyone at the workplace;
Effective protection can only be achieved by equipment which is correctly fitted, maintained and properly used at all times;
PPE may restrict the wearer by limiting mobility, visibility or by requiring additional weight to be carried.
Using PPE may alter employees’ perception of the hazards they are dealing with.
But PPE is critically important as it is only used in cases where other measures are insufficient.
Artificial intelligence for PPE compliance control: why YES?
The safety of employees at the workplace is important for any business. Workers are being better protected by the law than ever before. But, despite of it, workplace accidents still make serious threats to businesses’ financial viability. So, how can the application of artificial intelligence and machine learning help with video monitoring of PPE compliance?
Using PPE is important especially in industries that operate in potentially hazardous environments. Companies may well have extensive rules and regulations governing the use of such equipment, but it can be difficult to enforce correct usage. No matter how often you run through safety drills or training talks, some workers will always forget basic precautions, including PPE.
According to hse.gov.uk statistics, there is about a £14.9 billion per year overall cost of work-related injury and 31.2 million days lost due to non-fatal accidents and ill health. So, the key challenges facing businesses that need to stay compliant in terms of personal protective equipment (PPE) as follows:
43 % - Meeting legal obligations of PPE
38 % - Employee non-compliance
36 % - Educating the workforce in the correct use of PPE
36 % - Monitoring correct usage of PPE
It looks like compliance and the correct usage of PPE is a serious issue among the workforce. Compliance of employees continues to be a big concern moving forward, with over a third (35%) believing that their main focus in the next 1 to 5 years will need to be the continued monitoring of their growing workforce.
Increasing standards and stricter legislation involving PPE is the greatest worry to respondents (51%), as they try to minimise their liability for workplace incidents. After all, if employers responsible for implementing PPE are unaware of the latest legislation, it could cost the company hundreds of thousands in injury claims and insurance.
Solutions for PPE compliance monitoring and control
Here are typical examples of AI and ML based automated solutions that are available to address PPE-related concerns:
The solutions that can use AI video-monitoring which can identify PPE non-compliance in real time. These types of systems can provide a single answer to a lot of PPE challenges in one go; whether these be issues with employee non-compliance, workforce monitoring or legal obligations.
The solutions that prevent workplace injuries, by using wearable technology that can monitor vitals including heart-rate and body temperature.
In industries where employees may be damaged or infected any time, simple errors can lead to serious consequences. This is why the Health and Safety sectors are starving for innovations and technological evolution.Especially in new pandemic reality.
Humans make mistakes – especially if they have to monitor thousands of employees at the same time during a day. Products like AI-based PPE compliance monitoring systems that can monitor any number of people continuously and constantly, never get tired or bored and are more accurate at spotting issues. Additionally, the time that AI can save collecting and analysing data allows Site and Safety Managers to focus on new strategic and innovative ways to improve safety for everyone in the workplace, instead of non-stop checking in on employees.
VITech Lab Manufacturing offers a PPE detector that checks and verifies if employees are wearing any required personal protective equipment (PPE) in real-time
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