This is a study about the features found in vehicles. With the advancement in technology, vehicles are recently depending on sensors and recording. Features such as radar and cameras capture the areas around the car. Other features include traffic detection, automatic lane correction, location tracking and object detection among others. Little is known about the public attitude towards the already emerging vehicle-based recording. However, as such features become more common, it is important to understand how people feel about them.
The study revealed that vehicle based recording will add dynamics to recording and sensing. It makes it possible for recording to be done in spaces previously thought to be of comfort and semiprivate. However, the recording varies based on the specific benefits of the car. The advanced technology also makes it uncertain to collect access and identify. However, as vehicle-based recording technologies have been developed, opportunities to develop features and user education that are sensitive to public perception have been developed.
Another research by Mednis (2013) aimed at developing and verifying specific processing and recording methodologies based on participatory sensing. The study revealed that it is possible for the “possibility of mobile vehicle based sensor networks built as implementation of participatory sensing approach”. The study showed that there are individual methodologies with specific individual attributes. In addition, the implementation of these methodologies has individual aspects.
Both of these studies have been done thoroughly. Data was collected from credible participants and well analysed to test the hypothesis. In addition, the results are well presented using tables and graphs.
Mednis, A. (2013). Implementation of participatory sensing approach in mobile vehicle based sensor networks.
Sleeper, M., Schnorf, S., Kemler, B., & Consolvo, S. (2015, September). Attitudes toward vehicle-based sensing and recording. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 1017-1028). ACM.
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