Enhancing Workplace Safety and Reducing Accidents with Video Analytics
The United Nations reports that around 2.78 million workers lose their lives every year due to work-related accidents and diseases. Additionally, about 374 million workers face non-fatal work-related accidents. These numbers show that on average, there are 7,500 deaths from workplace accidents each day.
The question remains: as a business owner, what actions can we take to address this situation?
Numerous technologies have been created to make our lives safer. Some examples include airplanes that allow us to travel safely through the air, vaccines and medical innovations that have greatly reduced the number of deaths, and industrial robots that can handle dangerous jobs.
Video analytics is a field of computer vision that involves identifying objects and people in video footage and processing the data based on our commands. It has become an important AI innovation in reducing workplace accidents by playing a crucial role in improving workplace accident statistics.
In this article, we would like to guide you through the capabilities of video analytics in improving workplace safety.
Video analytics, the technology facilitating preventative measures for workplace safety
In truth, most workplace accidents can be avoided by following established rules and guidelines. These include wearing personal protective equipment (PPE), securing seatbelts when operating forklifts, and using fall protection gear. Sadly, workers sometimes neglect these regulations when they think no one is paying attention. Video analytics can help enforce policies more effectively and promote preventive actions.
We can integrate a video analytics system with the workplace's CCTV cameras for ongoing monitoring. There are many ways video analytics can improve safety. For example, we can teach a model to recognize dangerous or restricted areas and immediately notify authorities if someone enters those zones. We can also use CCTV cameras to check if workers are wearing the necessary safety equipment, making sure they follow the rules. Video analytics can monitor manufacturing machines to spot any unusual behavior and prevent potential breakdowns. It can also identify unauthorized vehicles entering restricted areas and locate objects blocking emergency exits.
These capabilities of video analytics can enable proactive measures, thereby reducing accidents and minimizing losses.
Examples of video analytics solutions for workplace safety
Different workplaces have their own safety regulations, such as wearing specific protective gear like safety helmets when entering the site, using masks, glasses, gloves, and boots in chemical-related areas, employing fall protection equipment, and fastening seatbelts while operating forklifts or machinery. Video analytics can learn the specific policies of each area and perform safety gear checks or detect the presence of required protective equipment on workers. This helps ensure that workers comply with the necessary safety measures before accessing restricted areas. Additionally, video analytics can identify any missing equipment that could potentially compromise safety.
Apart from enforcing social distancing measures during the Covid-19 pandemic, it is important to maintain appropriate distancing in manufacturing settings. Workers should keep a safe distance from large machines that can be hazardous and refrain from entering restricted areas without authorization. Video analytics can monitor the movement of workers and identify their location. By using a color compliance solution, authorized personnel can be allowed to access specific zones, while any unauthorized entry or unsafe proximity can be quickly detected, triggering immediate alerts. This proactive approach minimizes the risk of accidents and improves workplace safety.
24-hour safety monitoring
There are times when workers are without supervision, which can be risky as safety policies may be overlooked, increasing the chances of accidents. For example, a worker may try to fix a machine alone, leading to an unnoticed accident. Video analytics can continuously monitor workers and learn to identify falls, injuries, or signs of illness, promptly notifying authorities for timely help. This proactive approach greatly reduces the likelihood of accidents when workers are working alone or without supervision.
Machines that are not working properly can cause unexpected accidents, like loose knots, torn belts, or chemical leaks, which may not be noticeable from the outside. If a worker unknowingly uses a faulty machine, it can lead to unforeseen accidents. Video analytics can be essential in preventing accidents by detecting malfunctions and damages. For example, anomaly detection can identify signs of malfunctions, while leakage detection can promptly detect chemical leaks. This information can then be used to notify engineers and prevent workers from getting close to the affected machines. This proactive approach enhances accident prevention in the workplace.
Safety policy enhancement
By combining video analytics with data analytics solutions, we can analyze the causes of accidents using CCTV footage and statistical data. This analysis enables us to identify patterns such as the most frequent types of accidents, the areas where accidents occur most frequently, and the common instances of policy non-compliance by workers. This valuable information allows us to make informed adjustments to safety policies, ensuring they are more practical and effective in enhancing workplace safety.
Benefits of using video analytics for workplace safety
Reduces chances of accidents: Video analytics enables comprehensive enforcement of safety policies, thereby reducing the likelihood of accidents.
Speeds up response to emergencies: Continuous monitoring and timely alerts provided by video analytics enhance emergency response, leading to quicker intervention and reduced damages.
Lowers personnel costs and workload: By eliminating the need for constant manual monitoring, video analytics reduces personnel costs and workload. This not only saves labor but also minimizes the potential for errors. Consequently, workers' well-being and performance are improved.
Challenges in implementing video analytics for workplace safety
When implementing video analytics for workplace safety, it is important to create practical and accurate models. To build an effective model, sufficient data is needed for the model to learn from. For example, encountering unfamiliar situations may lead to false detections and missed alerts, resulting in potential losses. It is crucial for organizations to address the challenge of obtaining enough data to build practical models. Collaborating with a solution provider that specializes in the relevant domain can help ensure the practicality of the model.
Sertis is a leading data and AI solution provider in Thailand. We are here to collaborate with you and develop customized solutions that meet your unique needs, helping your business grow steadily and sustainably. Our team consists of experts from various domains, including video analytics. We have the expertise and resources to create video analytics solutions that improve safety for your workers and organization. By using advanced models trained on ample data, we ensure reliability and deliver positive outcomes for your business.
Learn more about video analytics solutions for workplace safety from Sertis at: https://www.sertiscorp.com/video-analytics