The fast-moving world today is exposed to many challenges which can occur in unexpected ways. For industries such as construction, manufacturing, oil & gas, or mining, the nature of tasks involved at the workplace makes the situation even more prone to danger. The visual vigilance in sites such critical needs to be stronger and tech-smart to miss any blind spots around. While traditional monitoring systems might overlook certain instances, technology vigilance is always on point.
Computer vision is a field of artificial intelligence (AI) that involves training machines to interpret and understand visual information from the world. By leveraging deep learning algorithms and neural networks, computer vision systems can process and analyze images and videos to detect specific objects. The propagation of this technology has opened many opportunities for making dynamic labour-intensive sites safer.
Here we explore how computer vision is elevating safety standards on critical sites, providing real-time vigilance, and safeguarding workers like never before.
The Importance of Helmet Recognition
Helmets are the frontline defense against head injuries in critical working zones. Despite their importance, it is often observed that ensuring compliance with helmet-wearing protocols can be challenging.
Manual monitoring methods in this regard, such as on-site inspections and video surveillance reviews, are labour-intensive and not always effective in real-time enforcement. The need for a more efficient and reliable system to ensure helmet compliance is clear.
Let’s take real-life examples showing the importance of helmets -
The word “struck-by” is used to define a set of injuries occurring at workplaces due to the violent contact taking place between equipment and a person. In the year 2020, there were about 150 fatalities and 14,000 non-fatal injuries taking place in the construction sector after a struck-by incident. Falling objects in the sites is one of the prime reasons for such incidents.
Helmets form a basic and important part of PPE compliance in a risky working environment. This mode of incident can be brought under control to a reasonable level with the application of computer vision technology through helmet recognition. Its enhancement with AI can substantially make the environment smarter and safer.
Enhancing Helmet Recognition Through Computer Vision
viAct's computer vision technology utilizes advanced AI algorithms to automated incident analysis and reporting by recognizing helmets in real time. From ensuring that every worker consistently wears a helmet to maintain safety standards to anomaly detection through it, the recognition system is capable of utilising the technology to its best use.
Here are four ways in which viAct’s Helmet Recognition System works –
Adapting to the Needs
The design of this solution is curated in a way that it can adapt to the different roles of helmets across different industries. For example, in construction safety monitoring, the helmet can detect falling objects, collisions, and accidental falls which are common in these sites.
In manufacturing units operating with heavy machinery and hazardous materials, helmets are crucial for preventing head injuries. Similarly, Helmets provide essential protection against explosions, falling debris, and harsh environmental conditions seen in the drilling rigs of the Oil & Gas industry. Further, workers in confined spaces for mining operations rely on their helmets for falling rocks, cave-ins, and equipment-related accidents.
viAct’s helmet recognition system uses advanced computer vision algorithms to monitor live video feeds under any of the above circumstances. It automatically detects the presence or absence of helmets on workers in real time. This ensures immediate compliance and enhances overall safety by providing instant alerts when a worker is not wearing a helmet.
Color-Based Recognition for Job Profile Segregation
In many industries, different helmet colors signify various job profiles or roles. For example, in construction:
White helmets might indicate managers or engineers.
Yellow helmets could represent general laborers.
Red helmets might denote safety officers or emergency responders.
While this is just an instance, the recognition can be set up based on the following patterns of the industry.
This functionality allows for the segregation of job profiles and ensures that workers comply with safety standards specific to their roles. Based on the color of the helmet, the system can recognise the set safety guidelines and scan the workers for compliance. Immediate alerts are generated if any worker is not following the set safety rules as per their helmet colors.
Moreover, the system can recognize if a worker is not wearing the correct helmet color for their job profile, this can trigger an alert for non-compliance, ensuring that everyone is correctly identified and properly protected. This prevents unauthorized entry of workers into danger zones or intrusion in areas where tasks beyond their abilities are being carried on.
Real-Time Monitoring and Alerts
The continuous, real-time monitoring provided by viAct's AI-powered helmet recognition system means that compliance is checked constantly without human intervention. When a worker is detected without a helmet or wearing the wrong color, the system sends immediate alerts to supervisors or safety officers. This prompt action can prevent potential injuries and maintain a high level of safety compliance across the site.
Data Analytics and Reporting
viAct's AI-powered system collects and analyzes data on helmet compliance, providing valuable insights into safety practices on-site. Managers can access detailed reports on helmet usage, non-compliance incidents, and trends over time using the centralized management platform. This data helps in identifying areas for improvement, optimizing safety protocols, and training programs to enhance worker safety continually.
The helmet recognition system is highly scalable and can be integrated into various existing safety management systems. Whether it's a small construction site or a large industrial complex, viAct's technology can be tailored to fit the specific needs of the environment. This flexibility ensures that all industries can benefit from enhanced helmet recognition, improving safety standards across the board.
Computer vision is transforming the way various sites enforce safety protocols. By providing real-time, accurate, and efficient helmet recognition, this technology ensures that workers are protected, and safety standards are upheld. As computer vision continues to evolve, its applications in workplace safety will expand, paving the way for even safer and more efficient work environments.
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