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Workplace safety represents a significant challenge for companies and workers worldwide. In 2023, the International Labor Organization reported that every year 3 million people worldwide die from work-related accidents and diseases, and 395 million suffer from non-fatal work injuries. These alarming statistics not only reflect the loss of life and human suffering, but also have a substantial economic impact. For example, it is estimated that Brazil loses about 4% of its annual GDP due to work-related accidents and illnesses, including costs of leave, labor lawsuits, etc., amounting to approximately US$ 82.3 billion in 2024.
Accident prevention is crucial and mandatory. Employers have the legal responsibility to ensure a safe work environment, comply with safety standards, provide adequate protective equipment, and implement risk management programs. However, they face challenges such as the need for constant monitoring, early risk identification, and implementation of effective preventive measures.
It is in this context that computer vision emerges as a powerful ally in workplace safety. This technology offers the ability to analyze images and videos in real-time, identifying potential risks and dangerous behaviors before they result in accidents.
By overcoming the limitations of human supervision, computer vision can provide continuous and accurate surveillance, helping to create safer work environments and significantly reduce accidents and their devastating consequences.
Understanding Computer Vision
Computer vision is a field of artificial intelligence that allows machines to interpret and understand the visual world similarly to humans. Using cameras, sophisticated algorithms, and machine learning techniques, computer vision enables computer systems to capture, process, analyze, and extract meaning from images and videos.
The process typically involves capturing images with a camera, digital processing of these images, and analysis using convolutional neural networks (CNNs), which can extract relevant features such as edges and shapes. As models are trained with extensive datasets, they become increasingly accurate in identifying and classifying objects in new images.
Benefits of Computer Vision
The implementation of computer vision offers several benefits for companies. It allows the automation of repetitive visual tasks, freeing up employees for more strategic functions. Additionally, it facilitates real-time decision-making in critical situations, such as public safety. The reduction of operational costs is another positive point, by replacing the need for human supervision in certain processes.
Safety improvement is also significant, through the prediction of suspicious behaviors and risk identification. This results in increased efficiency and productivity in various industrial sectors, as well as reducing human errors in inspection and quality control processes.
Use Cases: Computer Vision Applied to Workplace Safety
Computer vision can be applied in various ways to improve workplace safety. For example, Edge AI systems with computer vision, like dtLabs’s AIOS, can monitor the correct use of Personal Protective Equipment (PPE) in work environments. Cameras and advanced algorithms running on locally on Edge AI devices analyze in real-time whether workers are using appropriate PPE, such as helmets, safety glasses, and gloves. This allows for immediate interventions in case of non-compliance, reducing accident risks and ensuring compliance with safety standards.
Moreover, computer vision can be used to detect falls in real-time. Models trained to identify abnormal movement patterns associated with falls are particularly useful, allowing for a quick response in emergency cases and helping to save lives.
Another important use case is fire and smoke detection. Cameras equipped with infrared and optical sensors, combined with computer vision algorithms, can detect early signs of fire and smoke, even in low-light conditions or at great distances. This allows for real-time alert generation, such as a WhatsApp notification, triggering a siren, or creating a ticket on a Kanban dashboard, leading to a faster response to incidents, reducing potential damage, and increasing safety in industrial and commercial environments.
some of the many practical uses of a computer vision system.
Computer vision can also be applied to monitor restricted or risk areas. Automated systems can identify and track the presence of people or objects in unauthorized zones, generating immediate alerts for the security team. This is particularly useful in industrial environments, high-security facilities, or dangerous areas, where unauthorized access can pose significant risks.
Access control with facial recognition is another example of practical application. Access control systems based on facial recognition use cameras and advanced algorithms to identify and authenticate individuals. They capture facial images in real-time, compare them with a database of authorized people, and allow or deny access based on authentication results. This offers a more robust and convenient security solution compared to traditional methods such as access cards or passwords.
Finally, computer vision can be employed to monitor and optimize the flow of machines and people in industrial environments. Strategically positioned cameras, combined with motion analysis algorithms, can track the movement of machinery and employees, identify bottlenecks, analyze traffic patterns, and suggest improvements in layout arrangement or work processes. This contributes to increasing operational efficiency and reducing accident risks in production environments.
Conclusion
Computer vision represents a significant advance in the pursuit of safer and more efficient work environments. By integrating this technology with existing security systems, companies can create an additional layer of protection that operates continuously and accurately, overcoming many of the limitations inherent to human supervision.
The implementation of computer vision not only helps prevent accidents and reduce risks but also offers tangible benefits in terms of productivity and savings. With the ability to detect dangerous situations in real-time, from improper use of PPE to the presence of smoke or fire, this technology allows for a faster and more effective response to potential threats.
Furthermore, computer vision can contribute to a cultural change in organizations, promoting greater safety awareness among employees. Knowing they are being monitored, workers tend to adopt safer behaviors and adhere more rigorously to safety protocols.
However, it is important to emphasize that computer vision should not be seen as an isolated solution, but rather as part of a holistic approach to workplace safety. It should be combined with adequate training, well-defined safety policies, and an organizational culture that prioritizes employee well-being.
As technology continues to evolve, we can expect computer vision to become even more sophisticated and accessible, offering increasingly personalized solutions for the specific challenges of each sector. Investing in this technology today is not only a matter of compliance or cost reduction but a crucial step towards building a safer and more productive work future for all.
