How Can Visual AI Help to Ensure Workplace Safety?
4 Minutes Read
Time has come when the world is slowly, yet steadily reviving and reaching the new normal. Businesses need to mull over how to ensure business continuity and flexibility. For those who wish to quickly adapt to this new normal must prioritize workplace safety and put in efforts to ensure that their employees work without any perils to their health. Leveraging artificial intelligence (AI) and machine learning (ML) has been on the top of the mind for CIOs looking to build and strengthen their workplace safety mechanism. Visual AI or computer vision (CV) serves as the complete solution to monitor, analyze, and respond to safety and health-related risks.In fact, AI enables you to drive digital transformation and growth faster.
What is Visual AI?
Visual AI enables new and expert users to easily build and deploy more accurate and explicable machine learning models with images through community hardware. Computer vision enables you to work with images in a way like any other kind of data. There are enterprise AI platforms that automate the preparation, selection, and training of a large variety of cutting-edge deep learning models to recommend the best model for deployment.
Computer vision extends immediate support to classification and regression use cases with images and then allows users to use images as several other feature types in the dataset, including numeric, date, categorical, and text. Visual AI or computer vision sparks innovation by using these different data types that offer broader perspectives to AI/ML models.
The unique combination of AI technology and computer vision enables you to see the unseen, as it bridges the gap between humans and the insights that enterprises need today, especially during this pandemic scenario. What’s most important here is to ensure the safety of people and spaces.
How Does Computer Vision Ensure Workplace Safety Across Industries?
As social distancing becomes the new normal, it becomes crucial to track and monitor the gathering and movement of people. Businesses need to put in place their Standard Operating Procedures (SOPs) and track them in real-time. But guaranteeing safety and restoring business efficiency will only be possible with computer vision.
CV algorithms help to analyze footage from on-site video cameras so that employees can maintain safe, mandated distances from one another during shifts while following the standard protocols. AI and machine learning software enable retailers to supervise the distances maintained between their warehouse staff. These tools signal warnings in real-time when there is a deviation from normal behavior.
Besides, businesses need to score high on the social distancing index to show that their workspaces are safe for their employees. The social distancing index measures the distance between groups, people, and assets, such as machinery and vehicles. Tracking is done in real-time to send alerts to those concerned, in case of any safety violation.
Advancements in machine vision imply that now AI algorithms can detect objects, edges, and speed. In addition to that, improvement of processing power, sensors, and drones as well as robots, we can create fully automatized state-of-the-art routines that are better than their human counterparts. Computer vision replicates the human eyes effectively and like the human brain, can tell the difference between varied objects or situations. When used in an industrial setting, this means fewer accidents and prevention.
Monitoring workers for wearing personal protective equipment (PPE) comes handy with computer vision. With an automated AI system at work, even little violations, such as taking off a facemask or helmet, are reported and corrected. As you calculate your safety precautions index, you can measure how safe people are in a given area, regarding safety compliances and PPE.
When your workers don’t wear PPE, there are higher chances of injuries and subsequent financial losses, owing to fines for injuries and deaths. Automation of PPE detection enables manufacturers to mitigate the risk of accidents to the worker and minimize their liability while improving operational efficiency and providing analytics on workplace safety. Besides, AI automation helps to gather and analyze data for those responsible to ensure the safety of their workers. You can run factories with limited capacity through visual inspection and remote machine monitoring.
Bedside computer vision has gained much prominence to improve patient safety. To protect patient and staff privacy, depth, and thermal sensors are used to create images of human shapes in motion. Sensors are mounted in the doorways of patient rooms, next to hand hygiene alcohol gel dispensers. A doctor or nurse is thus reminded to take care of hand hygiene, as soon as they enter a patient’s room.
As neural network layers are exposed to labeled images, the surgeon also receives an alert if a crucial step is missed during a complex surgical procedure, and a nurse gets notified whether an agitated patient is dangerously attempting to pull out an endotracheal tube. As AI in the form of computer vision applications finds room in the healthcare industry; constantly monitoring bedside behavior, low-value work can be offloaded to machines, augmenting instead of replacing clinicians.
Computer vision intelligent systems have been deployed in several public places to safeguard the public. Not only can you analyze real-time video feeds, but also combine these images with infrared imaging to detect body temperatures. Recognizing infected people and monitoring physical distancing is the key. Computer vision has helped answer questions like:
Are people maintaining safe social distances?
How many people adhere to wearing masks?
What surfaces are people touching that may require cleaning?
They measure what, when, how, and where things move in open spaces and streets. Multi-object tracking in video enables the monitoring of objects and their pathways, as they move through space. In vision-based detection and analysis, the mechanism utilizes vision as the main sensor, so that the machine works in real-time.
Due to the development of robust machine learning algorithms, it has become possible to guarantee proper cluster density all the time. You can score high on the cluster density index that measures the crowd in an area. Besides, without automation, it becomes almost impossible to determine if proper sanitary measures are taken and prescribed guidelines are followed at large.
Is your workplace safe?
Visual AI is going to be at the forefront as the world embraces radical measures to guarantee workplace safety. It’s high time that you leverage technology to restore business efficiency, assuring your workers’ well-being at the same time. Safeguarding your workplace has now become crucial, not only to ensure the good health of your employees but also maintaining your brand reputation. Remember 75%1 of big organizations will hire artificial intelligence behavior privacy, forensic, and customer trust specialists to reduce brand and reputation risk by 2023.