![]() Finally, we have also devised a web service able to provide graphical visualization and historical evolution of sensed data. Furthermore, our navigation app is able to provide users with personalized pedestrian routes that take into account environmental parameters and not only the route length. To improve the quality of collected data we have also created an application for pedestrian navigation that works both on smartphones (also using Augmented Reality) and on smartwatches, thus ensuring an appropriate exposition of the mobile device (and its sensors) when collecting data. As a proof-of-concept, we have developed a mobile sensing platform able to pervasively collect environmental data. ![]() Mobile sensing and wireless communications can hence be employed to gather data and generate new information and services, benefiting our society. Through this new paradigm, physical phenomena can be observed in a distributed way, crowd-sourcing the data measurement tasks to smartphones and/or other popular smart wearables. The ubiquity of mobile technology has opened the door to the new era of mobile sensing. The two public artworks generated in this work can been seen at. This work is a typical practice of creating public installations with data visualization technology, giving a glimpse into the many ways science and art intersect. Two public artworks have been created with the above visualization and auralization methods and displayed on an exhibition held at China Resources Tower, Shenzhen, China. Furthermore, we also use the sunlight data to generate music as another form of data representation. Due to the variation of the sunlight data over time, the generated visual pattern presents a periodic variation that corresponds to the changing “mood” of the sunlight. ![]() Specifically, we create visual patterns with a rotating planet gear, which has an intuitively consistent geometric meaning with HSV colour model and the planetary motion. The proposed method makes use of the saturation and value information of collected sunlight image data in Hue Saturation Value (HSV) colour model to show the variation of the “mood” of the sunlight. In this paper, we present the design and implementation of a visualization method for sunlight data collected over a long period of time with an industrial camera. The application of data visualization in public art attracts increasing attention.
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