Difference between revisions of "IS428 2016-17 Term1 Assign3 Tan Yong Kiong Alson"
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== Problem and Motivation == | == Problem and Motivation == | ||
+ | Due to the kidnapping that happened in GAStech’s old office, the officials decided to shift its operations to a new three-story building. The data given consist of the results from sensors across the building, which can be used to analyse any patterns and anomalies. GAStech’s CEO is also concerned about the side effects that Hazium has on its employees, which may exist within the building. Therefore, four zones are fitted with the Hazium Concentration Sensors to monitor the level and take precautionary measures in the future. | ||
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+ | This report aims to find out the patterns and anomalies that exists within the 2 million data points embedded in the dataset. With the fixed and mobile prox card data from employees, we can see how the employees interact in the building during their working hours daily, with Rosie the robot. By realizing the patterns in the building data, it will aid in identifying and explaining the reasons behind them. We also want to find out the anomalies or ususual events that can be gathered from the data, which would help the higher management to be alerted or safety or fraud issues. | ||
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+ | Below are list of questions that will be explored: | ||
+ | # What are the typical patterns in the prox card data? What does a typical day look like for GAStech employees? | ||
+ | # Describe up to ten of the most interesting patterns that appear in the building data. Describe what is notable about the pattern and explain its possible significance. | ||
+ | # Describe up to ten notable anomalies or unusual events you see in the data. Prioritize those issues that are most likely to represent a danger or a serious issue for building operations. | ||
+ | # Describe up to five observed relationships between the proximity card data and building data elements. If you find a causal relationship (for example, a building event or condition leading to personnel behavior changes or personnel activity leading to building operations changes), describe your discovered cause and effect, the evidence you found to support it, and your level of confidence in your assessment of the relationship. | ||
== Approaches == | == Approaches == |
Revision as of 14:55, 25 October 2016
Contents
Data Visualization
The full dashboard on the data visualization can be found here.
Abstract
Problem and Motivation
Due to the kidnapping that happened in GAStech’s old office, the officials decided to shift its operations to a new three-story building. The data given consist of the results from sensors across the building, which can be used to analyse any patterns and anomalies. GAStech’s CEO is also concerned about the side effects that Hazium has on its employees, which may exist within the building. Therefore, four zones are fitted with the Hazium Concentration Sensors to monitor the level and take precautionary measures in the future.
This report aims to find out the patterns and anomalies that exists within the 2 million data points embedded in the dataset. With the fixed and mobile prox card data from employees, we can see how the employees interact in the building during their working hours daily, with Rosie the robot. By realizing the patterns in the building data, it will aid in identifying and explaining the reasons behind them. We also want to find out the anomalies or ususual events that can be gathered from the data, which would help the higher management to be alerted or safety or fraud issues.
Below are list of questions that will be explored:
- What are the typical patterns in the prox card data? What does a typical day look like for GAStech employees?
- Describe up to ten of the most interesting patterns that appear in the building data. Describe what is notable about the pattern and explain its possible significance.
- Describe up to ten notable anomalies or unusual events you see in the data. Prioritize those issues that are most likely to represent a danger or a serious issue for building operations.
- Describe up to five observed relationships between the proximity card data and building data elements. If you find a causal relationship (for example, a building event or condition leading to personnel behavior changes or personnel activity leading to building operations changes), describe your discovered cause and effect, the evidence you found to support it, and your level of confidence in your assessment of the relationship.