Design of a real-time autonomous in-cabin sensory system to detect passenger anomaly

Nandi, Pratyush; Mishra, Anubhav; Kedia, Pranav; Rao, Madhav

doi:10.1109/iv47402.2020.9304666

Cited by 6 publications

(2 citation statements)

References 10 publications

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“…Authors have surveyed multiple articles and AI methods for in-vehicle emotion detection to develop violence detection in carpooling services. In-cabin passenger anomaly detection was suggested in [13]. An evaluation of the in-vehicle monitoring system (IVMS) has been carried out in [14] to reduce risky driving behaviors.…”

Section: In-cabin Monitoringmentioning

confidence: 99%

“…To enhance the safety and security inside the vehicle's cabin, multiple works have been reported [5][6][7][8][9][10][11][12][13][14][15][16][17]. Recently various companies have also reported their in-cabin monitoring systems for improving the safety and security of the occupants inside the vehicle [18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33].…”

Section: Related Workmentioning

confidence: 99%

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In-Cabin Monitoring System for Autonomous Vehicles

Mishra

Lee

Kim

et al. 2022

Sensors

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In this paper, we have demonstrated a robust in-cabin monitoring system (IMS) for safety, security, surveillance, and monitoring, including privacy concerns for personal and shared autonomous vehicles (AVs). It consists of a set of monitoring cameras and an onboard device (OBD) equipped with artificial intelligence (AI). Hereafter, this combination of a camera and an OBD is referred to as the AI camera. We have investigated the issues for mobility services in higher levels of autonomous driving, what needs to be monitored, how to monitor, etc. Our proposed IMS is an on-device AI system that indigenously has improved the privacy of the users. Furthermore, we have enlisted the essential actions to be considered in an IMS and developed an appropriate database (DB). Our DB consists of multifaced scenarios important for monitoring the in-cabin of the higher-level AVs. Moreover, we have compared popular AI models applied for object and occupant recognition. In addition, our DB is available on request to support the research on the development of seamless monitoring of the in-cabin higher levels of autonomous driving for the assurance of safety and security.

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Section: In-cabin Monitoringmentioning

confidence: 99%