Integrating Technology in Workplace Safety: The Role of AI and IoT
Integrating AI and IoT into workplace safety enhances predictive analytics, real-time monitoring and proactive risk management to significantly reduce accidents and improve overall safety.
- By Juliet Pavelko
- Jul 17, 2024
The workplace has not always been a safe place. In fact, it is only really in the last half-century that serious efforts have gone into protecting people as they fulfill their professional roles from day to day.
While improvements have been made in a piecemeal fashion over the course of several decades, we’re now seeing a one-two technical transformation in this arena being brought about by artificial intelligence (AI) and the Internet of Things (IoT). Here’s a look at how this is shaping up and what’s already possible thanks to this tech.
Utilizing Predictive Analytics for Incident Prevention
Predictive analytics is revamping workplace safety by forecasting incidents before they happen. This is important given that there were 2.8 million nonfatal injuries and illnesses recorded in workplaces nationally in the most recently available annual data from the U.S. Bureau of Labor Statistics (BLS). The only way to bring this down is with better tech.
Understanding Predictive Analytics
At its core, predictive analytics involves:
- Data collection. Gathering historical data on past incidents, equipment performance and environmental conditions.
- Pattern recognition. Using machine learning to identify trends or anomalies that precede accidents.
- Risk assessment: Evaluating potential risks based on current data and predicted future events.
Take the example of HelloFresh, a provider of stress-free meal delivery that serves customers across the planet. The company’s Associate Director of Food Safety and Quality Assurance Reshma Malick said, “The way I see it, the most important aspect of achieving success is not just doing what you ‘have to do’, but also learning what you ‘have not to do’."
This is crucial in a context where it’s not just employee safety that’s at stake based on choices made and patterns overseen in-house but also customer safety.
Practical Applications in Safety
Here’s how businesses can leverage predictive analytics effectively.
1. Equipment Maintenance
- Schedule maintenance before failures occur.
- Reduce unexpected downtimes which lead to risky emergency repairs. This can avoid costs of up to $22,000 per minute.
2. Employee Behavior Monitoring:
- Identify patterns of unsafe behavior early.
- Tailor training programs to address specific issues detected by the system.
3. Environmental Hazard Detection
- Use IoT sensors to monitor changes in environmental conditions like temperature or air quality.
- Predict hazardous situations such as gas leaks or extreme weather events.
4. Incident Trend Analysis
- Analyze past incident reports to find common factors.
- Implement targeted interventions where the risk is highest.
Case Study: Newmetrix and JE Dunn
As highlighted by the National Safety Council, Newmetrix—an AI-focused workplace risk prediction software firm from Massachusetts—teamed up with JE Dunn, a Missouri-based building contractor employing 3,500 workers across the U.S.
Initial issues revolved around storing project documentation, images, and videos on individual smartphones and devices.
Implementing workflows to ensure all data was accessible to Newmetrix’s predictive AI software.
- Solution Implemented:
- Utilizing diverse data, including project location, weather conditions, staffing levels as well as images and videos from 2016 to 2021.
- Prompting site superintendents for additional safety conversations with workers based on insights derived.
- Outcomes Achieved:
- Predicted 75 percent of recordable incidents on the top seven ranked projects for risk each week.
- Initiated approximately 350 additional safety conversations between supervisors and employees.
Overall, Newmetrix’s advanced risk prediction software provided JE Dunn with a practical safety analytics solution that significantly enhanced workplace safety through actionable insights. This collaboration showcases how leveraging historical data can lead to proactive incident prevention in dynamic environments like construction sites.
The Role of Technology Leaders
We’re at a point where businesses are able to work with third parties to produce their own AI-enhanced, IoT-enabled predictive analytics tools that suit their specific needs. It just takes leaders to grab this opportunity.
And as Christopher Heer, IP Lawyer at Heer Law, said, "If you’ve created new and innovative workplace safety technology, consider protecting your ingenuity with a patent. Great innovations that make money in the commercial marketplace will be copied by others unless you protect them."
AI-Driven Safety Protocols and Real-Time Monitoring
AI isn't just for chatbots, autonomous cars and education. It's transforming workplace safety by offering dynamic, real-time solutions. Let's look into how AI can actively protect workers.
Implementing AI for Safety
Integrating AI-driven protocols means automating responses to potential hazards, streamlining safety checks and providing continuous monitoring. Here's how it works:
- Automation. Automate repetitive safety tasks like equipment checks.
- Surveillance. Use computer vision to monitor workplaces 24/7.
- Analysis. Leverage natural language processing (NLP) to review incident reports.
Key Applications of AI in Workplace Safety
It’s useful to think about AI’s arrival holistically, before drilling down into the safety specifics. For instance, its impact on cybersecurity has links to workplace safety.
As stated in this guide to secure AI by the experts at Wiz, “AI is going to be central to the next chapter of tech advancements. That’s why AI security is critical and can’t be treated as an afterthought. Working with reputable and highly qualified cloud security experts is the best way to strengthen your AI and cybersecurity posture.”
This type of rigor must be used when applying AI to protect flesh-and-blood workers on-site and in the field. Applications here include:
1. Computer Vision
- Cameras equipped with machine learning algorithms identify unsafe behaviors or conditions.
- Alert supervisors immediately when anomalies are detected.
2. Predictive Maintenance
- Analyze data from IoT sensors on machinery to predict failures before they happen.
- Schedule repairs at optimal times to prevent accidents due to malfunctioning equipment.
3. Smart PPE (Personal Protective Equipment)
- Use wearable technology that can detect environmental hazards like toxic gasses or high temperatures.
- Send alerts directly to the worker's wearable device for immediate action.
4. Incident Analysis
- NLP tools analyze written reports quickly.
- Highlight patterns in reported incidents for further investigation.
Real-Time Monitoring Systems
Real-time monitoring using IoT devices paired with AI creates a responsive environment that reacts instantly.
Advantages Include:
- Immediate Alerts
- Workers get instant notifications about dangers via smart devices.
- Supervisors receive comprehensive reports for swift decision-making.
- Continuous Data Collection
- Non-stop gathering of data points leads to a deeper understanding of potential risks.
- Algorithms constantly update their models based on new information.
Case Study: Amazon
Amazon has been at the forefront here, implementing real-time tracking systems in their warehouses utilizing computer vision technology coupled with robust machine learning models.
These systems help mitigate injury risks significantly by alerting both workers and managers about potentially dangerous situations instantly, while also having major advantages in terms of efficiency as well. This explains in part how it achieved a 12 percent boost to net sales in spite of its incumbent position as market leader, with what might be assumed was a high level of saturation.
Adopting such technologies means companies can react faster and also create safer work environments proactively. And it’s not just Amazon that can consider taking this route, as affordability is improving by the month.
Final Thoughts
For businesses and organizations across all sectors, the responsibility to protect workers is strong and fundamental. AI and IoT technology make this more attainable, efficient and cost-effective. These tools are there for the using, and the firms that want to flourish tomorrow will embrace them today.