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dc.contributor Wang, Xuyu en_US
dc.contributor.advisor Baynes, Anna en_US
dc.contributor.author Mopathi, Uthej
dc.date.accessioned 2020-12-17T21:16:50Z
dc.date.issued 2020-12-17
dc.date.submitted 2020
dc.identifier.uri http://hdl.handle.net/10211.3/218176
dc.description Project (M.S., Computer Science)--California State University, Sacramento, 2020. en_US
dc.description.abstract As John W. Turkey once said that “The greatest value of a picture is when it forces us to notice what we never expected to see.” It is a known fact that the evolution of computer science not only made completing tasks easier and improved our way of living, but the recent developments in the field of data analytics helps humans to implement it in their daily tasks, keep check on multiple tasks, understand the data in a more clear and efficient way. In the present world where every need is driven by technological solutions, it is very important to refine these huge loads of data and analyze it in a more efficient and quick way as it helps make rapid and accurate decisions. One important factor in the field of data visualization is to extract only knowledge from the data rather than complete data. Visual analytics is the science of providing analytical reasoning with support from interactive visuals and synthesize the data’s knowledge [1].. Visual analytics contains various tools and techniques that help a user to infer knowledge and develop solutions for the arising problems and it is also a diverse area ranging from household needs to economic enhancements. In this work, we present a novel approach towards monitoring the radiation levels recorded on various static and mobile sensors throughout a city. To develop our visual analytics to visualize the data from static and mobile sensors, we collect and aggregate the data we process [2]. We then input this cleaned data to the tool (Tableau) or write program (D3.js) to generate visualizations which answers the four questions which are the basis of sensor data and their uncertainties. The generated static and interactive visualizations help us understand and determine the uncertainties in these measurements, identify the areas of major concern and to identify the threat early as it can be a major concern if unattended due to the harmful effects of radiations on human beings, animals and ecosystem. We developed a webpage and deployed it on the local server where the visualizations can be interpreted and analyzed to derive the information required to evaluate the plans to overcome the effects of radiation. en_US
dc.description.sponsorship Computer Science en_US
dc.language.iso en_US en_US
dc.subject Data analysis en_US
dc.subject IEEE vast challenge en_US
dc.subject Tableau en_US
dc.subject D3.js en_US
dc.subject Data en_US
dc.subject Visualizations en_US
dc.title Citizen science to the rescue en_US
dc.type Project en_US
dc.description.embargoterms forever en_US
dc.date.embargountil 10000-01-01

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