We've encountered multiple occasions when smart technologies, such as smartwatches and other smart technologies, have assisted individuals in maintaining outstanding environments and healthy lifestyles. But what about mental wellbeing? Are there any smart gadgets or sensor systems that can assist people in enhancing their mental well-being and leading a cheerful life?

Physical and mental health is closely linked. To achieve a balanced lifestyle, we must care for our minds as well as our bodies. Furthermore, there are specific machine learning technologies and smart gadgets that focus on mental well-being. Let's begin with one of the most underestimated and overlooked problems: FATIGUE.

Fatigue Is Much More Than Simple Drowsiness

We commonly relate fatigue with ordinary sleepiness or tiredness. However, it’s much more than that. Fatigue expresses itself in a variety of ways, both physically and mentally. Furthermore, fatigue could be a sign of a chronic disorder or ailments, including heart problems, diabetes, stress, and several others.

We can’t monitor fatigue easily especially when the individual is on the go (driving). It can, however, be effectively monitored and evaluated by integrating advanced technologies.

Benefits of Fatigue Monitoring That Improves Safety

When your mental health suffers, you might experience physical signs such as dizziness, weight gain/loss, discomfort, and others. As a result, to maintain a healthy lifestyle, you must monitor and strengthen your psychological health. Smart gadgets, such as smartwatches or smart clothes, can be deployed to accomplish this. These technologies assist in monitoring and enhancing your psychological state.

Monitoring Fatigue improves safety at work, boosts productivity, minimizes accidents, and lessens injuries. The fatigue levels can be evaluated and calculated using a variety of factors and sources. It combines multiple user profiles like age, job role, gender, alcohol and drug consumption, productivity, and accuracy measures. In addition, smart fatigue monitoring solutions incorporated responsiveness to generate mental stats.

Machine learning enhances the accuracy of fatigue monitoring solutions using moment assessments, clustering algorithms, and principal component analysis. ML streamlines sensors, accelerometers, gyroscopes, magnetometers, and brain computing interfaces. Moreover, smart fatigue monitoring solution integrates and streamlines data for real-time drowsiness detections.

Fatigue Monitoring for Commercial Drivers

One of the primary causes of traffic accidents and fatalities is careless driving. As a result, monitoring and reporting driver fatigue is important.

Transport, logistics, cab services, haulage, and logistics companies can utilize camera or electroencephalography (EEG) based fatigue monitoring systems to capture data, with detection algorithms applied to monitor driver's alertness levels. Physical processing parameters are computed, and drowsiness is acknowledged based on respective measurements.

Fatigue monitoring may also be handled using driving behavior, which offers real-time notifications to avoid accidents. Machine learning technologies applied to statistics gathered using helmets improve fatigue minimization. The statistics indicate real-time problems and notify the driver with actionable alarms.

Fatigue Monitoring for Professional Miners

Fatigue control and monitoring support mining machinery operators in maintaining the degree of alertness required for long working hours and tedious operations. Fatigue can be accurately evaluated and monitored using advanced detection algorithms paired with scientific body-clock models. Most fatigue indicators, including microsleeps and distraction, can be detected using computational methods and sensing.

A person's movement can be instantly monitored using smart equipment such as smart headbands. Operators inside the mines can be notified via warnings alerts or notifications that inform the site supervisor for immediate intervention. Furthermore, the data acquired by smart wearable technologies can be examined to identify a person's attentiveness and check for indicators of fatigue to avoid future mistakes.

Improved Workforce Safety with SMART Fatigue Monitoring Solutions

There are different machine learning techniques for monitoring operator stress levels. It incorporates safety-related signals from interconnected IoT devices to measure operator stress or fatigue levels. Once the data is evaluated, it immediately notifies professionals and their coworkers with real-time stats, permitting proactive steps to eliminate serious accidents. As a result, it improves workplace safety and reduces corporate liabilities.

The Smart Cap’s fatigue monitoring suite can help you strengthen the psychological health of your employees and create a safe and healthy workplace. Feel free to contact our fatigue monitoring technology experts if you would like to know more about how the combined potential of smart sensors and machine learning for better operational productivity.
 

TAGS - driver fatigue monitoring fatigue monitoring solution mining systems

See Also - Importance of Fatigue Monitoring in Mining