IS428 2017-18 T1 Assign Lee Ting Kon Jeremy
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Problem & Motivation
Mistford is a mid-size city is located to the southwest of a large nature preserve. The city has a small industrial area with four light-manufacturing endeavors. Mitch Vogel is a post-doc student studying ornithology at Mistford College and has been discovering signs that the number of nesting pairs of the Rose-Crested Blue Pipit, a popular local bird due to its attractive plumage and pleasant songs, is decreasing! The decrease is sufficiently significant that the Pangera Ornithology Conservation Society is sponsoring Mitch to undertake additional studies to identify the possible reasons. Mitch is gaining access to several datasets that may help him in his work, and he has asked you (and your colleagues) as experts in visual analytics to help him analyze these datasets.
Mitch Vogel was immediately suspicious of the noxious gases just pouring out of the smokestacks from the four manufacturing factories south of the nature preserve. He was almost certain that all of these companies are contributing to the downfall of the poor Rose-crested Blue Pipit bird. But when he talked to company representatives and workers, they all seem to be nice people and actually pretty respectful of the environment.
In fact, Mitch was surprised to learn that the factories had recently taken steps to make their processes more environmentally friendly, even though it raised their cost of production. Mitch discovered that the state government has been monitoring the gaseous effluents from the factories through a set of sensors, distributed around the factories, and set between the smokestacks, the city of Mistford and the nature preserve. The state has given Mitch access to their air sampler data, meteorological data, and locations map. Mitch is very good in Excel, but he knows that there are better tools for data discovery, and he knows that you are very clever at visual analytics and would be able to help perform an analysis.
Background Information
| Companies | Description | Location |
|---|---|---|
| Roadrunner Fitness Electronics | Produces personal fitness trackers, heart rate monitors, headlamps, GPS watches, and other sport-related consumer electronics. | 89,27 |
| Kasios Office Furtniture | Manufactures metal and composite-wood office furniture including desks, tables, and chairs. | 90,21 |
| Radiance ColourTek | Produces solvent based optically variable metallic flake paints with the lowest volatile organic compounds in industry. | 109,26 |
| Indigo Sol Boards | Produces skateboards and snowboards and has seen modest growth in recent years. | 120,22 |
| Chemicals | Description |
|---|---|
| Appluimonia | It is an airborne odor is caused by a substance in the air that you can smell. While it does not cause serious injury, long-term health effect, or death to humans or animals, it may affect the quality of life and sense of well-being. |
| Chlorodinine | It is a corrosive that can attack and chemically destroy exposed body tissues as soon as it touches the skin, eyes, respiratory tract or digestive tract. It is thus harmful if inhaled or swallowed. Chlorodinine is used as a disinfectant and sterilizing agent as well as other uses. |
| Methylosmolene | It is a trade name for a family of volatile organic solvents. Several studies have documented the toxic side effects of Methylosmolene in vertebrates, and the use of it in manufacturing is strictly regulated. Liquid forms of Methylosmolene are required by law to be chemically neutralized before disposal. |
| AGOC-3A | It has been developed under new environmental regulations and consumer demand for low-VOC and zero-VOC solvents. It is less harmful to human and environmental health. |
The Data
The factories and sensors locations are provided in terms of x,y coordinates on a 200x200 grid, with (0,0) at the lower left hand corner (southwest).
Sensor Location
Sensor Data
Chemical: Which one of the four chemicals detected by the sensors
Monitor: Which one of the nine sensors picking up the reading
Reading: The air sensor detected amount in parts per million
Date Time: The date and time of day of the reading, local time with no change for Daylight Savings.
Meteorological Data
Each of these reading is taken at the date and time provided.
Date: The date and time of the readings, local time with no change for Daylight Savings.
Wind Direction: The compass directions where the wind is originating from, using a north-referenced azimuth bearing where 360/000 is true north.
Wind Speed: The speed of the wind in meters per second.
The Task
General task
The four factories in the industrial area are subjected to higher-than-usual environmental assessment, due to their proximity to both the city and the preserve. Gaseous effluent data from several sampling stations has been collected over several months, along with meteorological data (wind speed and direction), that could help Mitch understand what impact these factories may be having on the Rose-Crested Blue Pipit. These factories are supposed to be quite compliant with recent years’ environmental regulations, but Mitch has his doubts that the actual data has been closely reviewed. Could visual analytics help him understand the real situation?
The primary job for Mitch is to determine which (if any) of the factories may be contributing to the problems of the Rose-crested Blue Pipit. Often, air sampling analysis deals with a single chemical being emitted by a single factory. In this case, though, there are four factories, potentially each emitting four chemicals, being monitored by nine different sensors. Further, some chemicals being emitted are more hazardous than others. Your task, as supported by visual analytics that you apply, is to detangle the data to help Mitch determine where problems may be. Use visual analytics to analyze the available data and develop responses to the questions below.
The specific tasks
Task 1
Characterize the sensors’ performance and operation. Are they all working properly at all times? Can you detect any unexpected behaviors of the sensors through analyzing the readings they capture?Limit your response to no more than 9 images and 1000 words.
| Chart | Visualisation | Analysis |
|---|---|---|
| Calendar Heatmap |    |
After plotting a calendar heatmap of sum of readings based on a hourly breakdown across 3 months, we will be able to detect the operational stability of the sensors hourly. As seen from the heatmap, there is no reading on the 2nd April, 6th April, 4th August, 7th August and 2nd December at 00:00 hrs. However, a reading is detected at 01:00hrs on the same days. This indicates a 1 hour breakdown in sensor during the above mentioned dates. From the similar pattern and timing in breakdown dates and time it suggest that a regular monthly maintenance/ data collection of sensor is scheduled at the start of the month causing a disruption in data collection from 0:00hrs - 01:00hrs.
Tableau Field Configuration: |
Task 2
Now turn your attention to the chemicals themselves. Which chemicals are being detected by the sensor group? What patterns of chemical releases do you see, as being reported in the data? Limit your response to no more than 6 images and 500 words.
Task 3
Which factories are responsible for which chemical releases? Carefully describe how you determined this using all the data you have available. For the factories you identified, describe any observed patterns of operation revealed in the data. Limit your response to no more than 8 images and 1000 words.
Dataset Cleaning & Transformation Process
| S/N | Dataset | Changes | Description |
|---|---|---|---|
| 1 | Meteorological Data.xlsx |  |
Remove redundant column |
| 2 | Sensor Location.xlsx |  |
Rename column name to "Location" so we can append the factory names to the column |
| 3 | Sensor Location.xlsx |  |
Append factory location coordinates to date file |
