How Can Technology Improve Workplace Safety?
Technological advancements in the workplace are not limited to ensuring worker productivity, driving innovation, and increasing profit margins. Among other things, it helps promote and improve the wellness of both employees and employers by reducing the amount of accidents on the job site, thus preventing litigation and cutting on direct and indirect costs of worker injuries.
With the advance of artificial intelligence (AI) and machine learning (ML), organizations in industries as diverse as manufacturing, construction, oil & gas, food processing, forestry, and services are exploring the capabilities of sophisticated AI solutions to create a safe and protected environment for workers.
New Technology in Safety: Five Real-World Applications of AI
While trying to keep their employees safe, businesses also seek to reduce their liability through OSHA compliance. AI, ML, and Big Data are just some of the new tools in their arsenal. Below are several examples of how AI and ML are used for safety.
#1 Access Control
Worker safety starts at turnstiles. Intelligent access control systems powered by computer vision and image analysis algorithms can be installed at the entrance to check the ID of workers entering the job site, to prevent unauthorized access, and to scan their safety attire to ensure PPE compliance. Security staff or safety engineers are alerted if any violations are detected.
Personal protective equipment (PPE) is essential to keeping workers safe. It reduces a worker’s exposure to hazards, when administrative and engineering controls cannot reduce the risks to acceptable levels.
AI and machine learning considerably augment traditional video surveillance systems. They collect and analyze video footage in real time to automatically alert safety managers if a worker violates OSHA guidelines for PPE. Safety staff can take corrective measures and improve their safety drills for more efficient injury prevention.
One of the most beneficial applications of AI in manufacturing, predictive maintenance is strongly positioned on the border of health and safety technology, one the one hand, and production efficiency technology, on the other.
Business-wise, by taking advantage of AI-powered predictive maintenance systems, it is possible to determine the condition of equipment and predict when maintenance should be performed. According to PWC’ Predictive Maintenance 4.0 white paper, this leads to:
12% improvement in cost savings
14% reduction in safety, health, environment, and quality risks
20% longer time-of-use for production equipment
9% better equipment uptime
Safety-wise, however, predictive maintenance can be of help, too. By collecting data from IoT devices, organizations can monitor the state of the machinery and prevent failures that may lead to worker injuries ahead of time. When a piece of equipment needs maintenance, it is automatically shut off and access to it gets blocked by AI.
AI-driven hazards identification is one of the few safety technology examples that combines computer vision, image analysis, and predictive analytics in one. By taking advantage of this powerful cocktail of technology, organizations can not just reduce, but totally eliminate both fatal and non-fatal injuries.
Here’s how it works. High-resolution cameras and IoT devices collect visual and other types of data points, and stream it to a machine learning-aware data lake; data is processed and analyzed in real time. When an equipment malfunction is predicted or hazardous activities are detected on the job site (i.e. unregulated forklift traffic, clutter in the workplace, missing PPE, etc.), workers are notified about the danger individually; notifications are sent to safety personnel as well.
Falls are the leading cause of worker deaths in private sector and constitute no less than 42% of fatal accidents. No wonder that organizations in construction, transportation, oil & gas, manufacturing, mining, and agriculture are looking for ways to drastically reduce the amount of falls through AI.
They are exploring the capabilities of computer vision to closely monitor scaffolds, handrails, barriers, and movable platforms that protect workers employed at heights, as well as keep track of the workers’ PPE like full-body harnesses, lanyards, and retractable lifelines. Thanks to real-time analysis, violations are detected and immediately reported to safety managers, allowing them to avoid any potential accidents and damage.
To sum up
Using technology for safety is vital for organizations in such hazardous industries as construction, manufacturing, oil & gas, mining, logging, and agriculture. By utilizing artificial intelligence and machine learning, they can significantly reduce the number of accidents and worker injuries in the workplace. In that, businesses improve their workers’ wellness, avoid costly litigation, and minimize other costs related to fatal and non-fatal injuries.
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