using iot devices for sensor based monitoring of employees mental workload investigating managers expectations and concerns14453
Although the objective assessment of mental workload has been a focus of human factors research, few studies have investigated stakeholders' attitudes towards its implementation in real workplaces. The present study addresses this research gap by surveying N = 702 managers in three European
2025-06-28 16:24:57 - Adil Khan
Although the objective assessment of mental workload has been a focus of human factors research, few studies have investigated stakeholders' attitudes towards its implementation in real workplaces. The present study addresses this research gap by surveying N = 702 managers in three European countries (Germany, United Kingdom, Spain) about their expectations and concerns regarding sensor-based monitoring of employee mental workload. The data confirm the relevance of expectations regarding improvements of workplace design and employee well-being, as well as concerns about restrictions of employees' privacy and sovereignty, for the implementation of workload monitoring. Furthermore, Bayesian regression models show that the examined expectations have a substantial positive association with managers’ willingness to support workload monitoring in their company. Privacy concerns are identified as a significant barrier to the acceptance of workload monitoring, both in terms of their prevalence among managers and their strong negative relationship with monitoring support.
Project ObjectivesThe Objectives are as follows:
The assessment of mental workload of human has been a focused.
To confirm the relevance of expectations regarding improvements of workplace design and employee well-being..
To improve health and increase productivity by wearing the “Wearable mental Workload (WML)”.
Detection of occupational safety risks.
To validate the workload monitoring to increase support among corporate decision maker.
Project Implementation MethodThe project will be implemented by following methods:
Sample: Participants were recruited .
Questionnaire:After an introductory section which captured participants’ DE-mographics, their form of employment, and information about their company, participants will be introduced to the concept of sensor-based
monitoring of employees’ mental workload.
Data analysis.
Benefits of the ProjectFor identifying sources of error and to improve performance.
Increased awareness of the negative effects of certain work
practices on the health and well-being of employees, allowing
them to be better addressed.
Earlier detection and prevention of occupational safety risks
caused by employee overload.
Possibility of providing incentives for employees to change
unhealthy work practices through open communication of
individual or group workload indicators.
Technical Details of Final DeliverableEnviron sensors: Environmental sensors that measure environmental conditions such as loudness, humidity, or illumination to determine their effect on the employee’s mental workload .
Wearable: Wearables like fitness trackers that use physiological parameters, such as blood pressure or heart rate, to determine the employee’s mental workload .
Microphone: Microphone-based systems that use voice characteristics, such as pitch or rate of speech, to determine the employee’s mental workload .
Camera: Camera-based systems that use body posture or the occurrence of certain behaviors to determine the employee’s mental workload .
Eye-tracker: Eye-tracker based systems that use eye parameters, such as pupil dilation or eye movement, to determine the employee’s mental workload .
The project WML(Wearable mental Workload ) will be implemented in a factory, industries and in companies to asses the mental workload of employees/ workers.
Final Deliverable of the Project HW/SW integrated systemCore Industry ITOther Industries Others Core Technology Internet of Things (IoT)Other Technologies Augmented & Virtual RealitySustainable Development Goals Zero HungerRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 80000 | |||
| Thesis and stationary | Miscellaneous | 5 | 2000 | 10000 |
| internet connection | Equipment | 6 | 2000 | 12000 |
| tracking sensor | Equipment | 7 | 3000 | 21000 |
| Eye Tracker | Equipment | 1 | 20000 | 20000 |
| Camera | Equipment | 1 | 15000 | 15000 |
| microphones | Equipment | 1 | 2000 | 2000 |