Automated Alert to Dangerous Workplace Conditions

Many industries require that employees work in high risk environments. For this reason, employees are certified in advance of performing tasks and follow very strict protocols. When sensors on a device or during a work flow detect that a high risk or dangerous setting or task is imminent, there needs to be an automatically-displayed alert. Research that increases the reliability of automatic risk assessment based on situational awareness from employee-worn sensors, regardless of the technology provider, and produces a consistent and clear response regardless of the AR device model, mode or connection state would provide value to those working in high risk industries.

This research topic will extend the user experiences that are currently provided on smartphones in the workplace. It will also need to clarify when and how existing alert systems prioritize the messaging to users and test usability and benefit of having the alerts appear in AR view.

Stakeholders

Standards bodies, Safety officers, employees working in high risk jobs

Possible Methodologies

This topic requires consensus building by working with safety officers, and new approaches to create and codify use of AI (and train the AI) to detect high risk context and circumstances, and to immediately alert the AR user. The research could also study different types of alerts for different industries, their effectiveness and recommend protocols that all devices and AR-based systems could adopt.

Research Program

This topic or theme of research overlaps with the topic of visualizing alerts in a timely, intuitive and meaningful way. The outcomes of this research could also be applied in many industries. It could be combined with topics pertaining to safety and human factors.

Miscellaneous Notes

Standards for automatic alerts could also be applied in many industries where danger is minimal. It could be combined with topics pertaining to safety and human factors. Could be an offshoot of UL8400 or BSI IST/31.

Keywords

Safety, risk, automated alert, standards, situational awareness, sensors for risk detection, artificial intelligence, health risks, occupational risks, risk assessment, risk perception, accidents, safety-critical software, occupational health, occupational safety, safety, accident prevention, disaster prevention, electrical safety, health and safety, health hazards, safety devices, safety factor, safety systems, fault detection, monitoring, system monitoring

Research Agenda Categories

Standards, Technology

Expected Impact Timeframe

Near

Related Publications

Using the words in this topic description and Natural Language Processing analysis of publications in the AREA FindAR database, the references below have the highest number of matches with this topic:

• Lutz, R. R. (2018). Safe-AR: Reducing Risk While Augmenting Reality. 2018 IEEE 29th International Symposium on Software Reliability Engineering (ISSRE).
• Aromaa, S., Väätänen, A., Aaltonen, I., Goriachev, V., Helin, K., & Karjalainen, J. (2020). Awareness of the real-world environment when using augmented reality head-mounted display. Applied Ergonomics, 88, 103145.
• Ko, H., Oksana, B., Na, I. S., & Pan, S. B. (2018). Analysis an identification with ECG base in augmented-reality. Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems.
• Aromaa, S., Väätänen, A., Kaasinen, E., Uimonen, M., & Siltanen, S. (2018). Human Factors and Ergonomics Evaluation of a Tablet Based Augmented Reality System in Maintenance Work. Proceedings of the 22nd International Academic Mindtrek Conference.
• MITSUHASHI, K. (2018). Suggestion of the Booting System for Necessary Safety Check by Augmented Reality and Computer Graphics. 2018 9th International Conference on Awareness Science and Technology (iCAST).

More publications can be explored using the AREA FindAR research tool.

Author

Christine Perey

Last Published (yyyy-mm-dd)

2021-08-31

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