Difference between revisions of "Trenchcoat Detectives"
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| − | [[ | + | <font size = 5; color="#001a66"><span style="font-family:Century Gothic;">''' ISSS608: Visual Analytics and Applications'''</span></font> |
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| + | <font size = 4; color="#001a66"><span style="font-family:Century Gothic;"> - Anuthama Murugesan </span></font> | ||
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| + | <font size = 4; color="#001a66"><span style="font-family:Century Gothic;"> - Krutika Balveer Choudhary </span></font> | ||
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| + | <font size = 4; color="#001a66"><span style="font-family:Century Gothic;"> - Sumalika Kodumuru </span></font> | ||
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| + | [[Trenchcoat Detectives | <font color="#FFFFFF">''' Proposal'''</font>]] | ||
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| + | [[Data Overview| <font color="#FFFFFF"> Data Overview </font>]] | ||
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| + | [[Question1_SUMALIKA KODUMURU| <font color="#FFFFFF"> Sensor Performance </font>]] | ||
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| + | [[Question 2_SUMALIKA KODUMURU| <font color="#FFFFFF"> Patterns of Chemical Release </font>]] | ||
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| + | [[Question 3_SUMALIKA KODUMURU| <font color="#FFFFFF"> Factories Responsible </font>]] | ||
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| + | [[References & Feedback | <font color="#FFFFFF"> ''' Report''' </font>]] | ||
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| + | <font size = 5; color="#001a66"><span style="font-family:Century Gothic;"> '''Geo-spatial analysis of vehicle movement data to uncover patterns and detect anomalies'''</span></font> | ||
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Revision as of 14:49, 6 August 2017
ISSS608: Visual Analytics and Applications
- Anuthama Murugesan
- Krutika Balveer Choudhary
- Sumalika Kodumuru
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Geo-spatial analysis of vehicle movement data to uncover patterns and detect anomalies
Motivation
We found plot of ‘VAST Challenge 2017’ to be intriguing, to the likes of a detective story. The plot unfolds with a clear purpose of identifying the most plausible factors that lead to the decline of the endangered bird species Rose-crested Blue Pipit at the Boonsong Lekagul Nature Preserve. We aim to propose a hypothesis backed by the deductions from our analysis. The dataset covers a broad range of data types, from timestamp of vehicles that move through the preserve, to gaseous effluents data from nearby factories and imagery data of the flora and fauna in the Preserve.
This will challenge us to deal with different types of data set and strive to find correlations between such varied data.
Dataset Overview
We have 4 kinds of data available for this challenge:
- Timestamp data from the movement of vehicles through the Preserve
- Gaseous effluents data from the 4 surrounding factories
- Imagery data of the flora and fauna/ maps, etc
- Newsletters of the Preserve which may provide additional information on the Preserve.
Proposed Timeline
