Stress-oriented driver assistance system for electric vehicles

Athanasiou, George S.; Tsotoulidis, Savvas; Mitronikas, Epaminondas D.; Lymberopoulos, Dimitrios

doi:10.1109/embc.2014.6944980

Cited by 2 publications

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A comprehensive Reputation mechanism for ubiquitous healthcare environment exploiting cloud model

Athanasiou

Lymberopoulos

2016

2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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Absence of trust foundations may outweigh benefits of ubiquitous and personalized mental healthcare supervision provided within a Ubiquitous Healthcare environment (UH). Trust is composed by patient's Personal Interaction Experience (PIE) and social entourage accumulated PIE, i.e. Reputation (R). In this paper, a cloud-based Reputation mechanism is proposed. Since PIE is the elementary trust information source, also an Updating mechanism of PIE, is introduced, in this paper. Cloud materialization of combined mechanisms provides adaptability to UH Providers' dynamic behavior, facilitates detection of milking behaviors and complex malicious attacks while meets the challenge of limited accuracy in case of data sparseness. The effectiveness of the proposed mechanisms is verified via simulation in MATLAB.

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A comprehensive Reputation mechanism for ubiquitous healthcare environment exploiting cloud model

Athanasiou

Lymberopoulos

2016

2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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IoT-Based Assessment of a Driver’s Stress Level

Mattioli,

Davoli,

Belli

et al. 2024

Sensors

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Driver Monitoring Systems (DMSs) play a key role in preventing hazardous events (e.g., road accidents) by providing prompt assistance when anomalies are detected while driving. Different factors, such as traffic and road conditions, might alter the psycho-physiological status of a driver by increasing stress and workload levels. This motivates the development of advanced monitoring architectures taking into account psycho-physiological aspects. In this work, we propose a novel in-vehicle Internet of Things (IoT)-oriented monitoring system to assess the stress status of the driver. In detail, the system leverages heterogeneous components and techniques to collect driver (and, possibly, vehicle) data, aiming at estimating the driver’s arousal level, i.e., their psycho-physiological response to driving tasks. In particular, a wearable sensorized bodice and a thermal camera are employed to extract physiological parameters of interest (namely, the heart rate and skin temperature of the subject), which are processed and analyzed with innovative algorithms. Finally, experimental results are obtained both in simulated and real driving scenarios, demonstrating the adaptability and efficacy of the proposed system.

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Stress-oriented driver assistance system for electric vehicles

Cited by 2 publications

References 13 publications

A comprehensive Reputation mechanism for ubiquitous healthcare environment exploiting cloud model

A comprehensive Reputation mechanism for ubiquitous healthcare environment exploiting cloud model

IoT-Based Assessment of a Driver’s Stress Level

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