How Artificial Intelligence Ensures Safety At Workplace

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By Marilyn Royce

Artificial Intelligence is one significant innovation that has truly transformed the strategies to improve workplace safety. 

On-the-job accidents, injuries, and illnesses have been impacting the lives of many families causing mental strains as well as taking a toll on financial standings. For companies, the cost of workplace injuries is devastating and is estimated at $161.5 billion per year (US Department of Labor).

This drives a need to opt for improved technology that can help maintain safety for both employees and employers. 

Although the Occupational Health and Safety Administration has introduced safety inspection standards to ensure better risk management, there is a need to rely on AI and Machine Learning. 

In addition, since its establishment, the Federal OSHA has advocated for employees’ health and safety and stable work culture by ensuring that workers obtain safety training through an authentic provider. Therefore, OSHA 10 Hour training for entry-level workers in both General and Construction industries is highly recommended. Moreover, 30 Hour online construction is advised for construction employees since it covers many aspects of the construction industry, including but not limited to Electrical Safety, site hazards, and the use of Personal Protective Equipment.

OSHA 10 Hour training 30 Hour online construction

Let’s have an in-depth understanding of the role of AI in automating safety inspections. 

How AI Contributes to Ensuring Safety Compliance At Workplace 

Workplace safety is critical for protecting workers from injury or illness, preventing costly accidents, and ensuring regulatory compliance. Safety inspections are an essential part of a comprehensive safety program, providing a systematic way to identify and mitigate potential hazards in the workplace. Just like when you buy 5000 TikTok followers UK and it makes you forget the tension of generating leads.

On average, over 5000 workers lose their lives on the job every year. Moreover, an estimated 30% workplace slip-and-fall incidents were recorded by the US Department of Labor which has caused severe injuries that included broken bones, head injuries and concussions, and even spinal cord injuries. 

By automating safety inspections using AI, businesses can improve the efficiency, accuracy, and cost-effectiveness of their safety programs, while also improving overall safety outcomes for workers and the public. Gartner predicted that AI augmentation will recover 6.2 billion hours of worker productivity by 2021. 

Current Challenges With Safety Inspections

By sticking to traditional safety audits procedures, companies are experiencing a number of challenges. Here are some of those: 

  • Limitations Of Human Inspectors: 

Human inspectors have limitations, including the potential for error, fatigue, and inconsistency. Inspectors may also have varying levels of expertise and knowledge, which can impact the quality of their inspections. Additionally, human inspectors may be limited in their ability to access certain areas or environments, which can limit the scope of their inspections.

  • Costs And Time Associated With Safety Inspections: 

Safety inspections can be time-consuming and costly, especially for large facilities or complex processes. Inspections may require multiple inspectors, specialized equipment, and extensive documentation. This can lead to significant expenses, both in terms of labor costs and lost productivity.

  • The Need For Accuracy And Consistency: 

Safety inspections require a high level of accuracy and consistency to be effective. Inspectors must be able to identify potential hazards and assess risks consistently and accurately across different inspections. This can be challenging, as inspectors may have different interpretations of safety standards or risk factors. Inconsistent inspections can lead to missed hazards or uneven safety outcomes across different facilities or processes. Learn more here.

To overcome these challenges, opting for AI-based solutions can provide more consistency, accuracy and efficiency leading to improved safety outcomes and cost savings for businesses.

AI Technologies Used in Safety Inspections

AI technologies used in safety inspections include computer vision and machine learning. Computer vision involves using cameras and sensors to capture images and data from a facility or process, which can then be analyzed using machine learning algorithms to identify potential hazards. Machine learning involves using algorithms that can learn from data to identify patterns and make predictions. In the context of safety inspections, machine learning algorithms can be trained on historical data to identify potential hazards and assess risks.

Benefits Of AI-Based Safety Inspections 

Artificial Intelligence offers several benefits over traditional human inspections, including improved accuracy, faster inspections, and cost savings. For example, AI-based inspections can identify potential hazards that may be missed by human inspectors, reducing the risk of accidents and injuries. Additionally, it can be conducted more quickly and efficiently than human inspections, allowing businesses to save time and money.Moreover, AI-based inspections can be more consistent and standardized than human inspections, ensuring that inspections are conducted to the same standard across different facilities or processes.

Recent Applications of Artificial Intelligence 

Artificial Intelligence is gradually transforming multiple industries. Here are some common applications:

In the oil and gas industry, drones equipped with sensors and cameras can be used to inspect pipelines and identify potential leaks or other hazards. This can reduce the need for human inspectors to access hazardous areas and improve the accuracy of inspections.

In manufacturing, robots can be programmed to perform routine safety inspections, ensuring that inspections are conducted consistently and accurately. This can save time and money compared to human inspections.

Similarly, for construction technology, AI-based safety inspections can be used to identify potential hazards on job sites, such as unsafe scaffolding or fall hazards. This can improve the safety of workers and reduce the risk of accidents or injuries.

Potential Challenges And Limitations Of AI In Safety Inspections

Despite having innumerous capabilities to add over $15.7 trillion to the economy by 2030

Artificial Intelligence does have some technical complications which create hindrance in achieving maximum productivity. Here are some of the commonly experienced complications. 

Concerns around job displacement and the role of human inspectors: 

One potential challenge of AI-based safety inspections is the potential for job displacement. As AI technology becomes more advanced, it may be able to replace some or all of the tasks currently performed by human inspectors. This raises concerns about the future role of human inspectors and the need for retraining or re-skilling in the workforce.

Potential bias and ethical considerations: 

AI-based safety inspections may also be subject to bias and ethical considerations. For example, if the training data used to develop the AI algorithms is biased or incomplete, the resulting inspections may also be biased or incomplete. Additionally, there may be ethical considerations around the use of AI to make decisions that impact worker safety.

The need for ongoing maintenance and updates to AI-based systems: 

AI-based safety inspection systems require ongoing maintenance and updates to remain effective. This includes updating the algorithms to reflect changes in safety standards or regulatory requirements, as well as maintaining the hardware and software used to capture and analyze data. Failure to maintain and update these systems can lead to inaccurate or incomplete inspections, which can have serious safety consequences.

By recognizing these potential challenges and limitations, businesses can work to address them proactively. For example, businesses can prioritize retraining and reskilling for human inspectors to ensure that they remain relevant in the face of advancing AI technology. Additionally, businesses can invest in diversity and inclusion initiatives to minimize bias in the data used to train AI algorithms. Finally, businesses can prioritize ongoing maintenance and updates to AI-based safety inspection systems to ensure that they remain effective and accurate over time.

Future Directions And Potential For Further Automation Of Safety Inspections

Artificial Intelligence has the capability to be programmed and trained as per your needs. So, if you learn how to handle it wisely feeding the right information and set of instructions it can influence and behave as per your commands and directions. In this way, you will be able to leverage the technology to its full capacity generating the best performance. Here are some insightful strategies for future automation. 

Expansion of AI-based safety inspections to new industries: 

While AI-based safety inspections are already being used in industries like manufacturing and construction, there are many other industries where these technologies could be applied. For example, AI technology could be used in healthcare to carry out predictive analytics by identifying potential safety hazards in hospitals or other healthcare facilities.

Integration with other technologies: 

AI-based safety inspections could be integrated with other emerging technologies to improve safety and efficiency. For example, these systems could be combined with wearable technology to monitor workers’ vital signs and alert them to potential safety hazards.

Advances in machine learning and computer vision: 

Advances in machine learning and computer vision are likely to lead to even more advanced AI-based safety inspection systems in the future for regulatory complaints. For example, machine learning algorithms could be used to identify patterns in safety data, leading to more accurate and effective safety inspections.

Increased use of autonomous inspection technologies: 

Autonomous inspection technologies, such as drones or robots, could be used to perform quality control in hazardous or hard-to-reach areas without putting human inspectors at risk.

Improved data analysis and reporting: 

As AI systems generate more data, there will be an increasing need for efficient data analytics and reporting tools leading to enhanced process improvement These tools will help businesses to make more informed decisions about workplace safety and prioritize the most critical areas for improvement.

In a Nutshell

Overall, the future of AI-based safety inspections looks promising, with the potential to improve workplace safety across a wide range of industries. As AI technology continues to evolve, businesses will need to stay up-to-date with the latest advancements in order to fully leverage the benefits of these systems.