Developing Future Wearable Interfaces for Human-Drone Teams through a Virtual Drone Search Game

Fraune, Marlena R.; Khalaf, Ahmed S.; Zemedie, Mahlet; Pianpak, Poom; NaminiMianji, Zahra; Alharthi, Sultan A.; Dolgov, Igor; Hamilton, Bill; Son, Tran Cao; Toups, Zachary O.

doi:10.1016/j.ijhcs.2020.102573

Cited by 18 publications

(10 citation statements)

References 46 publications

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“…Numerous methods have been developed to assess a user's SA at a given moment. More common methods like the SAGAT rely on pausing a simulation and querying the user based on their memory of the systems state directly preceding the question (Endsley, 2019;Durso et al, 2006;Fraune et al, 2021;Nguyen et al, 2019;Fabris et al, 2021). In contrast, SPAM focuses on one's ability to locate the requisite information, as opposed to using memory to measure their SA, and is assessed based on reaction time and performance (Durso et al, 1999;Durso and Dattel, 2004;Cunningham et al, 2015).…”

Section: Situational Awarenessmentioning

confidence: 99%

“…Human Trust in robots is made more complicated by the fact that humans tend to anthropomorphize robotic vehicles and systems (Fraune et al, 2021;Hancock et al, 2020). That is to say people tend to erroneously attribute human emotions and features to robots, so understanding how self-assessed Trust develops across immersion levels, and over time, might give insight into this relationship.…”

Section: Trustmentioning

confidence: 99%

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Exploring the Impact of Immersion on Situational Awareness and Trust in Remotely Monitored Maritime Autonomous Surface Ships

Gregor,

Allison,

Heffner

2023

OCEANS 2023 - Limerick

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This thesis examines how Situational Awareness (SA) and Trust, along with some exploratory variables, were affected by different immersion levels in maritime remote monitoring. To examine this a simulated Shore Control Centre (SCC) interface for Maritime Autonomous Surface Ships (MASS) was constructed, which had an autonomous container ship traversing the arctic with robotic aids. Three query sets were asked per simulation run, which facilitated tracking how SA, Trust, and Motion Sickness (MS) evolved over time. Three different virtual reality (VR) interfaces were used; Non-Immersive VR (NVR), Semi-immersive VR (SVR), and Immersive VR (IVR). The simulation and query sets were performed on a counterbalanced within-subjects user study with 39 participants. The results illustrated various trade-offs -with NVR showing higher user preference, SVR showing signs of higher SA, and IVR showing moderate Trust but increased MS. Understanding these trade-offs between immersion levels is a requisite step for designing future SCCs.

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Section: Situational Awarenessmentioning

confidence: 99%

Section: Trustmentioning

confidence: 99%

Exploring the Impact of Immersion on Situational Awareness and Trust in Remotely Monitored Maritime Autonomous Surface Ships

Gregor,

Allison,

Heffner

2023

OCEANS 2023 - Limerick

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“…Figure 13 shows different wearable devices used for COVID-19. Recently, some studies have discussed the emerging wearable interface for human–drone integration to perform various tasks such as search and rescue [ 121 ], personal identification [ 122 ], and combatting pandemics [ 9 ]. The work presented in [ 122 ] can be used to trace people for monitoring, surveillance, and security purposes through drone technology.…”

Section: Emerging Technologies To Fight Against Covid-19mentioning

confidence: 99%

Role of Drone Technology Helping in Alleviating the COVID-19 Pandemic

et al. 2022

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The COVID-19 pandemic, caused by a new coronavirus, has affected economic and social standards as governments and healthcare regulatory agencies throughout the world expressed worry and explored harsh preventative measures to counteract the disease’s spread and intensity. Several academics and experts are primarily concerned with halting the continuous spread of the unique virus. Social separation, the closing of borders, the avoidance of big gatherings, contactless transit, and quarantine are important methods. Multiple nations employ autonomous, digital, wireless, and other promising technologies to tackle this coronary pneumonia. This research examines a number of potential technologies, including unmanned aerial vehicles (UAVs), artificial intelligence (AI), blockchain, deep learning (DL), the Internet of Things (IoT), edge computing, and virtual reality (VR), in an effort to mitigate the danger of COVID-19. Due to their ability to transport food and medical supplies to a specific location, UAVs are currently being utilized as an innovative method to combat this illness. This research intends to examine the possibilities of UAVs in the context of the COVID-19 pandemic from several angles. UAVs offer intriguing options for delivering medical supplies, spraying disinfectants, broadcasting communications, conducting surveillance, inspecting, and screening patients for infection. This article examines the use of drones in healthcare as well as the advantages and disadvantages of strict adoption. Finally, challenges, opportunities, and future work are discussed to assist in adopting drone technology to tackle COVID-19-like diseases.

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“…Therefore, drone edge intelligence can collaborate autonomously and with SAR heterogeneously. Drone edge is widely used to serve wearable IoT devices in many applications [38,39]. To perform tasks effectively and locally in the disaster, drone edge requires understanding the surrounding environment.…”

Section: Drone Edge Intelligence Over Disaster Areamentioning

confidence: 99%

Multi‐Drone Edge Intelligence and SAR Smart Wearable Devices for Emergency Communication

Alsamhi

Almalki

Al-Dois

et al. 2021

Wireless Communications and Mobile Computing

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Disasters, either manmade or natural, call for rapid and timely actions. Due to disaster, all of the communication infrastructures are destroyed, and there is no way for connection between people in disaster and others outside the disaster range. Drone technology is the critical technology for delivering communication services and guiding people and monitoring the unwanted effects of a disaster. The collaboration of advanced technologies can reduce life losses, save people’s lives, and manage the disaster crisis. The network performance of collaboration between the Internet of Things (IoT) and drone edge intelligence can help gather and process data, extend the wireless coverage area, deliver medical emergencies, provide real-time information about the emergency, and gather data from areas that are impossible for humans to reach. In this paper, we focus on the network performance for efficient collaboration of drone edge intelligence and smart wearable devices for disaster management. We focus mainly on network connectivity parameters for improving real-time data sharing between the drone edge intelligence and smart wearable devices. The relevant parameters that are considered in this study include delay, throughput, and the load from drone edge intelligence. It is further shown that network performance can have significant improvement when the abovementioned parameters are correctly optimised, and the improved performance can significantly improve the guiding/coordinating of search and rescue (SAR) teams effectively and efficiently.

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Developing Future Wearable Interfaces for Human-Drone Teams through a Virtual Drone Search Game

Cited by 18 publications

References 46 publications

Exploring the Impact of Immersion on Situational Awareness and Trust in Remotely Monitored Maritime Autonomous Surface Ships

Exploring the Impact of Immersion on Situational Awareness and Trust in Remotely Monitored Maritime Autonomous Surface Ships

Role of Drone Technology Helping in Alleviating the COVID-19 Pandemic

Multi‐Drone Edge Intelligence and SAR Smart Wearable Devices for Emergency Communication

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