학술논문

Skadi: Heterogeneous Human-sensing System for Automotive IoT
Document Type
Conference
Source
2022 IEEE International Conference on Smart Computing (SMARTCOMP) SMARTCOMP Smart Computing (SMARTCOMP), 2022 IEEE International Conference on. :165-167 Jun, 2022
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Cloud computing
Wearable computers
Prototypes
Sensors
Internet of Things
Biomedical monitoring
Monitoring
Vehicular Systems
Automotive Computing
Language
ISSN
2693-8340
Abstract
Over the past years, cars' computing, sensing, and networking capabilities have rapidly increased, and the automotive development aims for autonomous driving. However, the driver is still the focal point for decision making. It has to be alert at all times to avoid traffic accidents due to human factors like tiredness, inattentiveness, and intoxication. Therefore, there is a need for a system that monitors the driver and intervenes before human failure can have a negative impact on traffic. A variety of commercially available wearable IoT devices, such as smartwatches, bracelets, and rings, are capable of monitoring human health conditions. However, those devices come with technological differences and manufacturer-specific implementations. This paper proposes a prototype for a human-sensing and health monitoring system based on wearable sensor devices. The aim is to find a solution that ignores the technological heterogeneity of IoT devices and generalises their implementation into the automotive system. Consequently, the data should be available to be analysed together with the data collected from the vehicular sensors. Our solution is compatible with open-source platforms Eclipse Hono and Kuksa.