Self-Driving Cars

Daily, M.; Medasani, S.; Behringer, Reinhold; Trivedi, Mohan M.

doi:10.1109/mc.2017.4451204

Cited by 173 publications

(68 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This lack of granular and continuous monitoring can prevent timely intervention strategies 8–13 . With recent advancements in artificial intelligence (AI) and sensing, many researchers are exploring complex autonomous systems in real-world settings 14 . In ICU settings, doctors are required to make life-saving decisions while dealing with high level of uncertainty under strict time constraints to synthesize high-volume of complex physiologic and clinical data.…”

Section: Introductionmentioning

confidence: 99%

Intelligent ICU for Autonomous Patient Monitoring Using Pervasive Sensing and Deep Learning

Davoudi

Malhotra

Shickel

et al. 2019

Sci Rep

115

107

View full text Add to dashboard Cite

Currently, many critical care indices are not captured automatically at a granular level, rather are repetitively assessed by overburdened nurses. In this pilot study, we examined the feasibility of using pervasive sensing technology and artificial intelligence for autonomous and granular monitoring in the Intensive Care Unit (ICU). As an exemplary prevalent condition, we characterized delirious patients and their environment. We used wearable sensors, light and sound sensors, and a camera to collect data on patients and their environment. We analyzed collected data to detect and recognize patient’s face, their postures, facial action units and expressions, head pose variation, extremity movements, sound pressure levels, light intensity level, and visitation frequency. We found that facial expressions, functional status entailing extremity movement and postures, and environmental factors including the visitation frequency, light and sound pressure levels at night were significantly different between the delirious and non-delirious patients. Our results showed that granular and autonomous monitoring of critically ill patients and their environment is feasible using a noninvasive system, and we demonstrated its potential for characterizing critical care patients and environmental factors.

show abstract

Section: Introductionmentioning

confidence: 99%

Intelligent ICU for Autonomous Patient Monitoring Using Pervasive Sensing and Deep Learning

Davoudi

Malhotra

Shickel

et al. 2019

Sci Rep

115

107

View full text Add to dashboard Cite

show abstract

“…Nor does the defense of human capacities involved in driving greatly capture the attention of an information-jaded public. It seems, therefore, that the autonomous vehicle juggernaut will roll on despite any such observations (Daily et al, 2017). However, faced with this almost inevitable line of autonomy's progress, the next consideration has to be one of the transition periods between human and computer control, and what challenges we are facing in the immediate, near-term.…”

Section: The Most Practiced Skill In the Worldmentioning

confidence: 99%

Driving Into the Future

Hancock

2020

Front. Psychol.

View full text Add to dashboard Cite

This work considers the future of driving in terms of both its short-and long-term horizons. It conjectures that human-controlled driving will follow in the footsteps of a wide swath of other, now either residual or abandoned human occupations. Pursuits that have preceded it into oblivion. In this way, driving will dwindle down into only a few niche locales wherein enthusiasts will still persist, much in the way that steam train hobbyists now continue their own aspirational inclinations. Of course, the value of any such prognostication is in direct proportion to the degree that information is conveyed, and prospective uncertainty reduced. In more colloquial terms: the devil is in the details of these coming transitions. It is anticipated that we will see a progressive transformation of the composition of on-road traffic that will be registered most immediately in the realm of professional transportation in which the imperative for optimization exceeds that in virtually all other user segments. The transition from manual control to full automation will be more punctate than gradualist in its evolutionary development. As performance optimization slowly exhausts the commercial sector, it will progressively transition more into the discretionary realm by dint of simple technology transfer alone. The hedonic dimension of everyday driving will be dispersed and pursued by progressively fewer individuals. The traveling window of generational expectation will soon mean that human driving will be largely "forgotten," as each sequential generation matures without this, still presently common experience. Indications of this stage of progress are beginning to be witnessed in the demographic profile of vehicle usage and ownership rates. The purpose of the exposition which follows is to consider and support each of these stated propositions.

show abstract

“…So the customers are more interested in buying autonomous cars for their comfort. The autonomous car is a motor vehicle that guides itself without any human intervention . It is also called a driver‐less car, robotic car, and self‐driving vehicle.…”

Section: Case Studiesmentioning

confidence: 99%

Tactile internet and its applications in 5G era: A comprehensive review

Gupta

Tanwar

Tyagi

et al. 2019

Int J Communication

127

View full text Add to dashboard Cite

Over the last few years, communication latency has been a major hurdle for most of the applications deployed in different network domains. During this era, a number of communication protocols and standards were developed and used by the community. However, still, the problem of latency persists keeping in view of the quality of service (QoS) and quality of experience (QoE) for different applications. To mitigate the aforementioned issues, in this paper, we present an in-depth survey of state-of-the art proposals having tactile internet as a backbone for delay mitigation using 5G networks for future ultra-reliable low-latency applications such as Healthcare 4.0, Industry 4.0, virtual reality and augmented reality, and smart education. From the existing proposals, it has been observed that tactile internet can provide interactions between virtual objects to give a feel of real environment with maximum latency of 1 millisecond. Also, this paper highlights the key differences between the tactile internet and Internet of Things in context with 5G revolution. Then open issues and challenges of tactile internet for smart applications are analyzed. Finally, a comparison of existing proposals with respect to various parameters is presented, which allows the end users to select one of the proposals in comparison with its merits over the others. KEYWORDSHealthcare 4.0, Industry 4.0, IoT, latency, reliability, tactile internet, 5G INTRODUCTIONMobile communication allows users to exchange data using smart devices ubiquitously using the mobile internet (MI). MI has millions of connected smart devices irrespective of their locations. It has revolutionized the different segments of industries such as health care, logistics, education, gaming, and transportation for maintaining quality of service (QoS) and quality of experience (QoE) for different applications. Moreover, it provides a device-to-device (D2D) communication, ie, ubiquitous communication for data sharing and communication between devices. This D2D communication coined the new term, the Internet of Things (IoT), 1 which provides the low power devices or equipments to perform specific tasks in the environment where they are deployed. IoT is being used in various smart city applications such as smart lightening, smart parking, waste management, traffic congestion, and forest fire detection. In D2D communication, the mobile devices can share prime or critical information in which a delay of even millisecond can harm the persons life (for example, the information sharing during robotic telesurgery). Existing cellular systems infrastructure is not suitable for such sensitive data sharing because of low data rates and long delay (greater than 20 ms). However, for D2D communications, Int J Commun Syst. 2019;32:e3981.wileyonlinelibrary.com/journal/dac

show abstract

Self-Driving Cars

Cited by 173 publications

References 1 publication

Intelligent ICU for Autonomous Patient Monitoring Using Pervasive Sensing and Deep Learning

Intelligent ICU for Autonomous Patient Monitoring Using Pervasive Sensing and Deep Learning

Driving Into the Future

Tactile internet and its applications in 5G era: A comprehensive review

Contact Info

Product

Resources

About