Kexin Zhang, Brianna R Cochran, Ruijia Chen, Lance Hartung, Bryce Sprecher, Ross Tredinnick, Kevin Ponto, Suman Banerjee, Yuhang Zhao
Proceedings of the CHI Conference on Human Factors in Computing Systems
This research paper investigates the design space of optical see-through AR head-mounted displays (HMDs) specifically tailored for first responders in the field.
Key Focus in Edge Computing Context:
Enhanced Situational Awareness:
The research aims to leverage edge computing capabilities to provide real-time, on-device processing and analysis of sensor data. This enables the AR HMD to deliver critical information to first responders instantly, such as:
- Real-time threat detection: Identifying and highlighting potential hazards (e.g., hazardous materials, structural weaknesses) in the environment.
- Location-based information: Providing accurate maps, building floor plans, and the locations of victims or other first responders.
- Communication enhancements: Facilitating seamless communication and collaboration among first responders on the scene.
Reduced Latency:
Edge computing minimizes the latency associated with cloud-based processing, ensuring that critical information is delivered to first responders with minimal delay. This is crucial in time-sensitive situations where rapid decision-making is essential.
Improved Reliability:
By processing data locally, the AR HMD can operate more reliably in environments with limited or intermittent connectivity, such as disaster zones or remote locations.
In essence, this research explores how edge computing can be integrated with AR HMDs to create powerful tools that enhance the safety and effectiveness of first responders in the field. By leveraging real-time data processing and analysis, these systems can provide critical support in a wide range of emergency scenarios.
Read the paper here.
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