Internet of Things: Providing Services Using Smart Devices, Wearables, and Quantified Self

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    Data Extraction and Forensic Analysis for Smartphone Paired Wearables and IoT Devices
    ( 2020-01-07) Dorai, Gokila ; Houshmand, Shiva ; Aggarwal, Sudhir
    Wearable devices and Internet of Things (IoT) devices have marked the beginning of a new era in forensic science. Data from smart home gadgets and wearable devices can serve as an important "witness" in civil as well as criminal cases. Thus data extracted from these devices has started to impact and transform litigation. Data collected from wearable devices can help determine truths in witness testimony since these devices document several types of activities of an individual at all times. Increased use of smart home devices also opens a new window for investigators. The collective data extracted from wearables and smart home devices can help investigators view the detailed events that have happened in an environment in a larger context, and give them better perspectives in the case under investigation. Our work aims to provide a solution to the challenges faced by the investigators in both extracting and analyzing the sheer volume of extracted data, and illustrates techniques to automatically highlight anomalies and correlations in the time series data collected from these devices.
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    I Spy with my Little Sensor Eye - Effect of Data-Tracking and Convenience on the Intention to Use Smart Technology.
    ( 2020-01-07) Princi, Evgenia ; Krämer, Nicole
    The increasing number of smart objects in private households leads to a profound invasion of privacy. Based on privacy calculus theory, we assume that many users accept tracking in exchange for full functioning and convenience. However, privacy calculus has not yet been tested in an area where privacy protection is a binary decision: to either use a product or not. Therefore, we examined the effect of convenience and tracking on the intention to use a smart device in a 2 x 2 between-subjects online experiment (N = 209). While convenience is a major factor for the willingness to deploy smart technology, users do not seem to care whether these devices track their personal data or not.
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    Toward a User Acceptance Model of Autonomous Driving
    ( 2020-01-07) Garidis, Konstantin ; Ulbricht, Leon ; Rossmann, Alexander ; Schmäh, Marco
    Autonomous driving is becoming the next big digital disruption in the automotive industry. However, the possibility of integrating autonomous driving vehicles into current transportation systems not only involves technological issues but also requires the acceptance and adoption of users. Therefore, this paper develops a conceptual model for user acceptance of autonomous driving vehicles. The corresponding model is tested through a standardized survey of 470 respondents in Germany. Finally, the findings are discussed in relation to the current developments in the automotive industry, and recommendations for further research are given.
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