IS428 AY2019-20T1 Assign Sin Myeong Eun Task3

VAST Challenge'19 MC2:Citizen Science to the Rescue

Overview & Data preparation

Tasks

Interactive Visualisation

References

Task 1

Task 2

Task 3

Task 4

Task 5

Task 3: Given the uncertainty you observed in question 2, are the radiation measurements reliable enough to locate areas of concern?

a) Highlight potential locations of contamination, including the locations of contaminated cars. Should St. Himark officials be worried about contaminated cars moving around the city?

Figure 3a-1

1. In order to locate the areas that were highly contaminated, we need to study the distribution of each static sensor. A new field had to be created to contain only the readings that were above 75cpm, meaning we just want to study the readings that do not only consist of the background radiation. The new field was computed using the following equation: "if(avg([Value])>75) THEN avg([Value]) END".
2. Moving on, boxplot was chosen as a visualisation method to show the distribution of each static sensor's readings. From figure 3a-1, we can compare the average value of each sensor's readings to the average value of the all the sensors' readings.
3. By manual comparison, we can see that sensors with sensor ID 1,4,6,9,11 are the sensors that detected higher average reading than the overall average reading. Sensor 15 was not chosen because its average reading was too sensitive to the outliers when most of its data points lie below the overall average reading.
4. By comparing with the shake map that shows the region where each static sensor is located at, we can deduce that the following list of regions are the potential locations of contamination.
   • Sensor ID 1: Palace Hills
   • Sensor ID 4: DownTown
   • Sensor ID 6: SouthWest
   • Sensor ID 9: Old Town
   • Sensor ID 11: Broadview

Figure 3a-2

1. In order to locate the locations of contaminated cars,we have to visualise the movement of the cars whose mobile sensors detected readings higher than 75cpm. Firstly, refer to figure 3a-2 which shows the average readings of all the mobile sensors across the time span, sorted by their sensor-id. We will have to focus on the "spikes" shown on 3a-2, which are the readings that were higher than 75cpm (highest background radiation) as those sensors are the ones that detected high radiation records. The following list is the mobile sensors that were identified to have detected high radiation readings.
   Sensor IDs:
   • 10
   • 20
   • 21
   • 22
   • 24
   • 25
   • 27
   • 28
   • 29
   • 45
2. Next, with the identified sensors, we analyse their movements across the city. Figure 3a-3 below is an example of how the movement of highly contaminated car can be visualised using the sensor-id filter. This step will be repeated for all sensors listed as highly contaminated from previous step.


Figure 3a-3

Sensor ID	Regions traveled	Sensor ID	Regions traveled	Overall Regions frequency
10	DownTown Weston Easton Old Town	25	Southwest Southton West Parton Oak Willow Broadview Chapparal Scenic Vista	Palace Hills: 0 Northwest: 0 Old Town: 1 Safe Town: 2 Southwest: DownTown Wilson Forest: 0 Scenic Vista: 2 Broadview: 6 Chapparal: 5 Terrapin Springs: 3 Pepper Mill: 0 Cheddarford: 3 Easton: 2 Weston: Southton Oak Willow East Parton West Parton DownTown Cheddarford Chapparal
20	DownTown Southton West Parton East Parton Oak Willow Broadview DownTown Cheddarford Chapparal	27	DownTown Weston Southton Southwest West Parton Oak Willow Broadview Scenic Vista
21	Easton Safe Town East Parton Cheddarford Terrapin Springs	28	Broadview Scenic Vista Chapparal
22	East Parton Safe Town Cheddarford Chapparal Scenic Vista	29	Terrapin Springs Scenic Vista
24	West Parton Oak Willow Broadview Scenic Vista	45	Safe Town East Parton West Parton Oak Willow Broadview Chapparal Terrapin Springs
















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b) Estimate how many cars may have been contaminated when coolant leaked from the Always Safe plant. Use visual analysis of radiation measurements to determine if any have left the area.




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c) Indicated where you would deploy more sensors to improve radiation monitoring in the city. Would you recommend more static sensors or more mobile sensors or both? Use your visualization of radiation measurement uncertainty to justify your recommendation.