Difference between revisions of "IS428 AY2019-20T1 Assign Ngoh Yi Long Tasks"
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− | ''' 2. Use visual analytics to represent and analyze uncertainty in the measurement of radiation across the city. ''' | + | ''' 2. Use visual analytics to represent and analyze uncertainty in the measurement of radiation across the city. ''' <br> |
− | a. Compare uncertainty of the static sensors to the mobile sensors. What anomalies can you see? Are there sensors that are too uncertain to trust? | + | a. Compare uncertainty of the static sensors to the mobile sensors. What anomalies can you see? Are there sensors that are too uncertain to trust? <br> |
− | b. Which regions of the city have greater uncertainty of radiation measurement? Use visual analytics to explain your rationale. | + | b. Which regions of the city have greater uncertainty of radiation measurement? Use visual analytics to explain your rationale. <br> |
− | c. What effects do you see in the sensor readings after the earthquake and other major events? What effect do these events have on uncertainty? | + | c. What effects do you see in the sensor readings after the earthquake and other major events? What effect do these events have on uncertainty? <br> |
{| class="wikitable" | {| class="wikitable" | ||
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Although the static sensors only have one sensor which is uncertain, mobile sensors itself can be seen above might be proving uncertainty over the north and south-east area where majority of the large radiation level readings were being recorded. | Although the static sensors only have one sensor which is uncertain, mobile sensors itself can be seen above might be proving uncertainty over the north and south-east area where majority of the large radiation level readings were being recorded. | ||
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− | |[[File:Task 2.4 (YL).png|400px|frameless]] <br> | + | |[[File:Task 2.4 (YL).png|400px|frameless]] <br> [[File:Task 2.5 (YL).png|400px|frameless]] || |
− | [[File:Task 2.5 (YL).png|400px|frameless]] || | ||
Comparing the 2 graphs, the highlight table depicts the maximum value recorded for each minute over the time frame for all mobile sensors. As we can see there is 2 regions of high readings which could show the earthquake and other major events. The event happening right before April 9 has caused many mobile sensors to not be able to properly have their readings recorded at the later part of the day on April 9. Similar for the event happening around April 10, which caused the mobile sensors to not have their readings recorded at the later part in the day. This might show a relationship over major events occurring and the uncertainty on the sensors, where some of the sensors would not be working or unable to retrieve data after the event has happened. | Comparing the 2 graphs, the highlight table depicts the maximum value recorded for each minute over the time frame for all mobile sensors. As we can see there is 2 regions of high readings which could show the earthquake and other major events. The event happening right before April 9 has caused many mobile sensors to not be able to properly have their readings recorded at the later part of the day on April 9. Similar for the event happening around April 10, which caused the mobile sensors to not have their readings recorded at the later part in the day. This might show a relationship over major events occurring and the uncertainty on the sensors, where some of the sensors would not be working or unable to retrieve data after the event has happened. | ||
|- | |- | ||
+ | |} | ||
+ | |||
+ | ''' 3. Given the uncertainty you observed in question 2, are the radiation measurements reliable enough to locate areas of concern? ''' <br> | ||
+ | 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? <br> | ||
+ | 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.<br> | ||
+ | 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. <br> | ||
+ | |||
+ | {| class="wikitable" | ||
+ | |- | ||
+ | |[[File:Task 3.1 (YL).png|400px|frameless]] || | ||
+ | This diagram is a filtered to show only those mobile sensors reading below 100 (safe radiation level). The readings over the time frame is mostly showing the roads where the car is on the move, moving from cities to cities too. | ||
+ | |- | ||
+ | |[[File:Task 3.2 (YL).png|400px|frameless]] || | ||
+ | On the other hand, these are the mobile sensor readings which are above 100 (unsafe radiation level). The points on this graph are mostly on its own and no relationship except for higher radiation level in the central, north, and south-east part of the city. This would show that despite the places which might be contaminated, the cars are still safe to roam around and not affecting the locations’ radiation level. | ||
+ | |- | ||
+ | |[[File:Task 3.3 (YL).png|400px|frameless]] <br> [[File:Task 3.4 (YL).png|400px|frameless]] || | ||
+ | According to the cumulative radiation by the static sensor, at around April 8, 4pm, is when the recorded readings started to split which means more radiation recorded due to the earthquake happening. While the highlight table showed increasing radiation level pickup on the sensors around April 8, 2pm. So that would mean that the earthquake occurred around April 8, 2-4pm. | ||
+ | |- | ||
+ | |[[File:Task 3.5 (YL).png|400px|frameless]] || | ||
+ | Using that time frame, I filtered out the mobile sensor to show all the points of the mobile sensors recording during that period. There is only one vehicle with sensor-id 9 that is inside the nuclear power plant in that period. Around the vicinity of the nuclear powerplant there was the vehicle with sensor-id 13. If the coolant leakage might contaminate the vehicles, these 2 vehicles with sensor-id 9 and 13 might have been exposed. | ||
+ | |- | ||
+ | |[[File:Task 3.6 (YL).png|400px|frameless]] || | ||
+ | After the earthquake period, both vehicles did leave the area and roamed around the north part of the city which includes Old Town, Easton, Weston and Downtown areas. | ||
+ | Seeing how the earthquake can affect the mobile sensors recordings, in my opinion I would recommend to put more static sensors as it seems to be more trusted as compared to the mobile sensors. | ||
+ | |- | ||
+ | |[[File:Task 3.7 (YL).png|400px|frameless]] || | ||
+ | With the current static sensor locations placed already, I would put at least one static sensor in every other neighbourhood that currently do not have one. This would help the uncertainties in mobile sensors for each neighbourhood. It would also help the relevant authority to have a better grasp of each neighbourhood on the ground and can respond to the respective neighbourhood when an emergency has occurred. <br> | ||
+ | However, we should not put down the effort of the mobile sensors. Mobile sensors although if the car is moving usually would not be able to detect much radiation, however at park locations like over the night or stationary in the morning at work would allow the radiation level at that spot to be picked up which the static sensors are not there to pick up. At the same time, the mobile sensors are able to track the vehicles moving in and out of the city by the highway which could show signs of possible contaminated cars going out of the city as well. | ||
+ | |- | ||
|} | |} |
Revision as of 23:26, 13 October 2019
MC2: St. HiMark Radiation Monitor System
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1. Visualize radiation measurements over time from both static and mobile sensors to identify areas where radiation over background is detected. Characterize changes over time.
2. Use visual analytics to represent and analyze uncertainty in the measurement of radiation across the city.
a. Compare uncertainty of the static sensors to the mobile sensors. What anomalies can you see? Are there sensors that are too uncertain to trust?
b. Which regions of the city have greater uncertainty of radiation measurement? Use visual analytics to explain your rationale.
c. What effects do you see in the sensor readings after the earthquake and other major events? What effect do these events have on uncertainty?
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?
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.
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.