A workspace without any injuries and other accidents increases employee motivation and performance. Whether it is health, agriculture, clothing or electronics; today hundreds of thousands of workers are working in different branches of the manufacturing and services sectors all around the world. We all wish that the whole process keeps going on with maximum productivity without any accident, but sometimes things do not work that well.
Workplace safety and health is an important topic for the companies. Although most of the managers don’t think providing a safe and healthy work environment for the workers is the service that carries the utmost importance, ignoring even the basic precautions against the accidents may cause undesired consequences. According to the US Bureau of Labor Statistics, 5333 workers died on the job in 2019. To decrease the possibility of fatal accidents, companies must pay attention to occupational safety regulations.
On paper, companies follow various strategies to act upon occupational safety and health(OSH) regulations for preventing the accidents that may happen in a workplace. But unfortunately, giving a OSH seminar once in a year or hanging posters to warn the workers does not really help to create awareness among the workers and maintain a safe environment. It is not easy for the health and safety teams to inspect the whole facility and take action for risky behaviors and also be sure that every worker is obeying the basic rules such as wearing a work vest or a safety helmet. At this point, cutting edge technologies, for instance artificial intelligence, may create lifesaver solutions to improve workplace safety.
It is definitely important for workers to wear personal protective equipment in a working environment to protect themselves from accidents. However, workers don’t always mind the importance of these equipment and tend to work without them. Another example is the line markings that are warning the employees for dangerous areas or showing the walking zones can be crossed by the workers. It is a hard and exhausting job to avert all of these problems because they can drop beneath the radar easily. Thanks to artificial intelligence, today it is possible to conduct all of this process by using AI driven real time video processing.
An artificial intelligence model can be developed to detect whether a worker is wearing equipment such as a safety helmet and a work vest or staying in the working zones that the worker should be in. A well developed AI model can conduct this process with minimum mistakes 24/7. Detecting a behavior that may cause an accident immediately is an important step to prevent the health and safety problems in a workplace, so the abilities of AI such as rapid decision making and autonomous operation make it much more easier for health and safety teams to maintain a better workplace. A camera system powered with an AI model as mentioned can scan the whole facility and inform the OHS teams about the undesired situations immediately. Thus physical injuries and other accidents can be prevented with maximum performance.
The development phase of the AI model has a critical role to come up with a foolproof AI driven OHS monitoring device, since the AI model is responsible for detecting the individuals and the objects in the workplace. Training the AI model with a comprehensive dataset makes the model able to identify the objects in the video frames. As a better example, the AI model recognizes the safety helmet and distinguishes it from the other elements by virtue of this step. Moreover, data annotation is vital to build the dataset that is used to train the model because through the annotation process, the objects in the image data are classified as desired. An AI model that is trained by a well-annotated dataset can detect the objects without any mistake, so it is important to get support from an experienced and successful annotation team.
At Co-one, our data annotators annotate occupational datasets to satisfy the needs of the teams that are developing AI products to create better workplaces. With the help of the datasets annotated at Co-one, it is possible to train AI models for preventing accidents by detecting workers and getting the insights about them. We built our data annotation process on perfect data labeling, cross validation and agile tracking to provide the high quality dataset needed by AI developers.
We are sharing our open-source annotated datasets to make a contribution in AI by giving a chance for developers to reach high quality datasets. We believe in the power of AI to solve problems and create new solutions, so we are working to participate with our rapid data annotation service.
Want to take a look at our open-source annotated datasets or learn more about Co-one? Contact us!