Connected Car: Quantified Self becomes Quantified Car

Journal of Sensor and Actuator Networks

Melanie Swan¹ 

[1] Kingston University London, Penrhyn Rd, Kingston upon Thames, Surrey KT1 2EE, UK; E-Mail

关键词: automotive;    quantified self;    sensors;    connected devices;    big data;    automation;    cognitive relief;    biometrics;    self-driving cars;    connected car;   

DOI  :  10.3390/jsan4010002

来源: mdpi

【 摘 要 】

The automotive industry could be facing a situation of profound change and opportunity in the coming decades. There are a number of influencing factors such as increasing urban and aging populations, self-driving cars, 3D parts printing, energy innovation, and new models of transportation service delivery (Zipcar, Uber). The connected car means that vehicles are now part of the connected world, continuously Internet-connected, generating and transmitting data, which on the one hand can be helpfully integrated into applications, like real-time traffic alerts broadcast to smartwatches, but also raises security and privacy concerns. This paper explores the automotive connected world, and describes five killer QS (Quantified Self)-auto sensor applications that link quantified-self sensors (sensors that measure the personal biometrics of individuals like heart rate) and automotive sensors (sensors that measure driver and passenger biometrics or quantitative automotive performance metrics like speed and braking activity). The applications are fatigue detection, real-time assistance for parking and accidents, anger management and stress reduction, keyless authentication and digital identity verification, and DIY diagnostics. These kinds of applications help to demonstrate the benefit of connected world data streams in the automotive industry and beyond where, more fundamentally for human progress, the automation of both physical and now cognitive tasks is underway.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.