Machine learning and IA benefit worker safety in industry

The irruption of Industry 4.0 has meant that the results of the technological advances that are taking place are even more evident. But the effects of these are not limited to just ensuring worker productivity, driving innovation and increasing profit margins.

In addition to these aspects, they help promote and improve the well-being of employees and employers by reducing the number of accidents in the workplace, thus avoiding not only legal problems, but also reducing the costs of workers’ injuries .

With the advancement of Artificial Intelligence and machine learning, industries as diverse as manufacturing, construction, oil and gas, and food processing are exploring the capabilities of sophisticated solutions that enable AI and machine learning and thus being able to create a safe environment for workers.

In an attempt to increase employee safety, industrial companies are increasingly putting themselves in the hands of experts to take advantage of tools such as AI, machine learning, and Big Data, among others. Here are some examples of how these tools are used for worker safety.

Access controls

Worker safety begins at the entrance lathes themselves. For some time now, some industries have been installing intelligent access control systems at their entrances with artificial vision technology and image analysis algorithms to verify the identification of workers entering the workplace, to avoid unwanted access. authorized and to scan safety clothing, so as to ensure compliance with personal protective equipment (PPE). In the event that an anomaly is detected, the company’s security managers receive an alert to correct it.

PPE compliance

Personal protective equipment is essential to bring worker safety closer to desirable levels. Minimizes the exposure of a worker to the dangers that may be encountered in the performance of their work, especially in those aspects that the company’s own controls are not able to reach.

Artificial Intelligence and machine learning significantly increase the capabilities of traditional video surveillance systems. They collect and analyze video footage in real time to automatically alert safety officers if a worker violates mandatory guidelines. As a consequence, corrective measures can be taken and, for example, improved safety drills for more efficient accident prevention.

Predictive Maintenance

One of the most beneficial applications of new technologies in the manufacturing industry is predictive maintenance, which also has a lot to do with everything related to health and safety technology, on the one hand, and production efficiency technology, on the other hand.

From a business point of view, by taking advantage of predictive maintenance systems powered by Artificial Intelligence, it is possible to determine the health of the equipment at all times and predict when the necessary maintenance must be performed. A predictive maintenance report in Industry 4.0 leads to improvements in cost savings, reductions in safety, health, environmental, and quality risks, and longer usage times of production equipment.

From a safety point of view, predictive maintenance can also help. By collecting data from IIoT devices, industries are able to monitor the health of production equipment and prevent early failures that can cause injury to workers. When a piece of equipment needs maintenance, it automatically shuts down and Artificial Intelligence blocks access.

Identifying dangerous situations

Hazard identification powered by Artificial Intelligence is one of the examples of safety technology that combines machine vision, image analysis and predictive analytics all in one. By leveraging this powerful cocktail of technology, companies can not only reduce, but totally eliminate the injuries that may occur.

High-resolution cameras and IIoT devices collect visual and other data and transmit it to a machine-learning-capable databank. The data is processed and analyzed in real time. When equipment malfunctions are predicted or dangerous activities are detected in the workplace, individual workers are notified of the danger and notifications are also sent to safety officers.

Fall prevention

Falls are the leading cause of worker death and account for about 40 percent of fatal accidents. So it’s no wonder that organizations in construction, transportation, oil and gas, manufacturing, mining, and agriculture are looking for ways to dramatically reduce the number of downturns through Artificial Intelligence.

Machine vision capabilities are being explored to closely monitor scaffolding, handrails, barriers, and mobile platforms that protect workers employed at heights, as well as to track workers’ PPE; such as full body harnesses, and semi-static lanyards. Thanks to real-time analysis, breaches are detected and immediately reported to security officials, allowing them to avoid potential accidents and damage.

The use of technology for safety is vital for organizations in industries as dangerous as construction, manufacturing, oil and gas or mining. By using Artificial Intelligence and machine learning, the number of accidents and injuries of workers in the workplace can be significantly reduced.