Enhanced Vehicle Safety Design Proposal: Personalized Driver Behavior Monitoring System; Google Glass Trajectory Investigation through Actor Network Theory

My STS research paper explains why Google Glass failed as an attempt to prevent car crashes and thus with such insight, in my technical project, I propose a more effective driver monitoring system to prevent car crashes. My STS research paper analyzes how Google failed to consider all human and non-human actors in the Glass network whereas my technician proposal discusses both types of actors as part of the success of the monitoring system. Nonetheless, the theme of using technology to try and prevent car crashes is common to both papers. My technical proposal for an effective driver monitoring system involves a combination of a camera in the driver’s vehicle and a mobile application installed on the driver’s phone. The camera will analyze and collect data about the driver’s behavior during driving. It then feeds this information to the application which will then use machine learning algorithms to detect what distractions are more of an issue than others for this driver, when the distractions occur, and how the driver responds to the system-produced alerts. This way, the system can adapt to each unique driver and produce more effective real-time alerts, helping to prevent car accidents. My STS research paper examines why the Google Glass technology was discontinued through the lens of the Actor-Network-Theory (ANT). Glass was a technology released by Google that could be worn like sunglasses and the idea was to provide a hands-free tool for instances like driving. In the paper I argue that the downfall of Glass can be attributed to the combination of poor technical design, privacy concerns from non-users, and general public judgement. I use various pieces of evidence to illustrate how Google, as the network builder, did not consider all human and non-human actors together, ultimately leading to its downfall. It was valuable to have worked on both projects simultaneously because the STS aspect really made me realize how truly all aspects of a technology need to be considered in order for it to be successful. Learning about all the different technical and social actors in Glass inspired me to also think about them when writing my technical proposal for a monitoring system. I realize now that it is going to take more than just the technology working for such a system to work. For example, I discuss that the system would also rely on the drivers, their approval, and their trust through robust security. Furthermore, I hope to apply this insight to my professional career in the future in the Computer Science field, keeping in mind that there is a lot more than just the piece of technology itself.

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Publication Details

Journal
Libra
Published
2025-05-07
DOI
https://doi.org/10.18130/abpc-f674
Primary Topic
Information Systems Theories and Implementation
Type
article
Field-Weighted Citation Impact
0.00
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article

Enhanced Vehicle Safety Design Proposal: Personalized Driver Behavior Monitoring System; Google Glass Trajectory Investigation through Actor Network Theory

Libra
Information Systems Theories and Implementation
article

Enhanced Vehicle Safety Design Proposal: Personalized Driver Behavior Monitoring System; Google Glass Trajectory Investigation through Actor Network Theory

article en

Abstract

My STS research paper explains why Google Glass failed as an attempt to prevent car crashes and thus with such insight, in my technical project, I propose a more effective driver monitoring system to prevent car crashes. My STS research paper analyzes how Google failed to consider all human and non-human actors in the Glass network whereas my technician proposal discusses both types of actors as part of the success of the monitoring system. Nonetheless, the theme of using technology to try and prevent car crashes is common to both papers. My technical proposal for an effective driver monitoring system involves a combination of a camera in the driver’s vehicle and a mobile application installed on the driver’s phone. The camera will analyze and collect data about the driver’s behavior during driving. It then feeds this information to the application which will then use machine learning algorithms to detect what distractions are more of an issue than others for this driver, when the distractions occur, and how the driver responds to the system-produced alerts. This way, the system can adapt to each unique driver and produce more effective real-time alerts, helping to prevent car accidents. My STS research paper examines why the Google Glass technology was discontinued through the lens of the Actor-Network-Theory (ANT). Glass was a technology released by Google that could be worn like sunglasses and the idea was to provide a hands-free tool for instances like driving. In the paper I argue that the downfall of Glass can be attributed to the combination of poor technical design, privacy concerns from non-users, and general public judgement. I use various pieces of evidence to illustrate how Google, as the network builder, did not consider all human and non-human actors together, ultimately leading to its downfall. It was valuable to have worked on both projects simultaneously because the STS aspect really made me realize how truly all aspects of a technology need to be considered in order for it to be successful. Learning about all the different technical and social actors in Glass inspired me to also think about them when writing my technical proposal for a monitoring system. I realize now that it is going to take more than just the technology working for such a system to work. For example, I discuss that the system would also rely on the drivers, their approval, and their trust through robust security. Furthermore, I hope to apply this insight to my professional career in the future in the Computer Science field, keeping in mind that there is a lot more than just the piece of technology itself.

Libra
University of Virginia (US)
Openalex Percentile: Top 47%
Information Systems Theories and Implementation
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