Since Artificial Intelligence was invented, how people work and live has changed significantly. While AI effortlessly learns and processes a huge amount of data, it has become an undeniable favorite tool for corporations across the globe. From personal to business uses, the options are endless. In a bid to automate multiple business procedures, identifying safety hazards has become a new addition.
An Environmental, Health, and Safety (EHS) Manager must be present for these processes to occur. As described by ProtexAI in a guide, an EHS manager develops and implements effective safety programs to enhance the well-being of employees in a workplace. From training initiatives to recycling programs, the applications are numerous. They usually work with facility managers, but AI is fast becoming a new application.
To be an aide to the EHS (Environmental, Health, and Safety) Manager, AI has to identify, improvise, and mitigate safety risks in the workplace. Apart from the traditional approaches of audits, which can be time-consuming and inaccurate, AI can automate the process better. It works by analyzing data sources effectively to pinpoint patterns and improvement opportunities. This allows the EHS manager to focus on problem areas to establish efficacy-driven measures.
Here are some ways how AI can help EHS managers improve workplace safety:
Identify Patterns in Data
For AI to pick up patterns of equipment behavior, analyzing large data sets from machine sensors is vital. AI can easily highlight a potential safety hazard by using a data-driven approach to identify discrepancies, abnormalities, and disparate patterns. From overheated machines to unusual sounds from internal machinery, nothing is undetectable. In addition, employee feedback on production floors can also be incorporated. Not just limited to machines, slippery floors, poor lighting, and ventilation can also be noted. As long as data can be coordinated and consolidated, AI can use it for EHS managers to take preventive or corrective actions.
Potential Hazard Prediction
Through historical data, AI can swiftly detect consistent or probable recurring patterns. With this additional information, identifying the root causes of accidents is simple. By knowing the reasons behind different incidents, EHS managers can establish preventative measures to stop history from repeating itself. One of the best aspects is predictive modeling. It is a methodology that analyzes data using statistical algorithms to predict future outcomes. AI can instantly predict potential safety risks as long as a wide range of data sources is included, such as weather and machine data.
Empower Safety Training
Employees must be adequately trained and informed of the latest safety procedures to cultivate a safe workplace. AI can help analyze data from employee training programs. Struggling employees can be pulled aside and given a personalized approach to help improve. By addressing their pain points, employee safety awareness can be maximized to reduce the probability of accidents.
Drive Regulatory Compliance
With data, AI can be a potent ally for workplace safety. AI can instantly pinpoint areas lacking regulatory compliance through employee feedback, machine and environmental data. By being aware of areas that lack compliance, EHS managers can develop and implement measures for damage control. In some cases, corrective measures can be executed to ensure each area complies with the state’s regulations.
In Summary
AI is a powerful aid for EHS managers to identify potential safety hazards in the workplace by analyzing a vast range of data sources. Not just to prevent accidents, it is a helpful ally in ensuring the corporation is compliant with the state’s regulations to avoid legal implications. Despite AI’s many uses, it is not a direct replacement for human judgments but a tool for providing actionable insights to help EHS managers make informed decisions.
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