ISSS608 2016-17 T3 Assign Qian Hongjun

From Visual Analytics and Applications
Revision as of 21:46, 7 July 2017 by Hjqian.2016 (talk | contribs)
Jump to navigation Jump to search

Answer to the tasks

Task1. Detect sensor performanc

Sensor detection frequencies

Sensor data frequencies.png

Normally, each monitor will have readings for each of four chemicals every one hour from 0:00 to 23:00. That means each monitor will detect 4*24=96 times each day. However, from the graph above, we can see in some days, the monitor only detects 92 times or 94 times each day. Namely, these days are April 2, April 6, August 2, August 4, August 7, December 2 and December7. These abnormal detection frequencies are questionable and require further investigation.


Sensor readings.png

Take the monitor1 in April 2 as an example, we can find the it starts detection from 1:00 am but normally the monitor starts detection from 0:00. The rest of abnormal detections are the same situation which the sensors start detection from 1:00 instead of 0:00. The reason may be the sensors are not working properly in these years. However, this one hour gap may give the factory some opportunities to discharge the chemicals illegally. Furthermore, we can see a downward trend from 1:00 to 2:00, which means it’s highly possible the factory may discharge more chemicals from 0:00 to 1:00 but the sensor was not working properly at that time period.

Some questionable gaps

Gap.png

The graph above is an example of these gaps showing the readings of monitor1 in August 2. We can see from the graph, there’s a gap between 13:00 and 15:00. It means there’s no reading of the chemical Methylosm at that 14:00. Actually, these gaps very common in other monitors and in other dates. We may infer that these gaps are caused because the monitors are not working properly. However, each time when there’s no reading for Methlosm, the readings of AGOC-3A always increase dramatically.

4.png

Then when we trace back to that period, we can find that actually the recordings are wrong because there are no records of Methlosm at 14:00 August 2 but AGOC-3A was recorded twice. That’s the reason why we see so many gaps. The recording system must be upgraded or fixed to record the readings of corresponding chemicals properly.


Some extreme high readings

5.png

As can be seen in the graph above which is the readings of monitor1 in the 3 months, some readings are extreme high in the range of its corresponding monitors. The following table summarizes some extreme high readings for different monitors. These high readings are also questionable because they are quite outstanding from the normal range. The reason may be the sensors were not working properly or there were some external environmental factors such as wind. The reasons will be further investiged in the later parts.

6.png

Some other high readings

7.png

Except for some extreme high readings, there are also some other high readings in the fluctuation range. For example, the graph above shows the readings of monitor 1 in the middle of April. We can see that for each chemical there’s a reference line showing the median with quartiles and the median value of Chlorodinine is 0.199 but the value in April 16 11:00 is at 5.090. This is a high value compared to the median value and needs further investigation. Especially, we will put more focus on the reading of chemical Chlorodinine because Corrosives are materials that can attack and chemically destroy exposed body tissues. It is a dangerous chemical to our environment and human beings.
Some other high readings are shown in the following table.

8.png



Task2. Chemical exploration

Task3. Define which factories are responsible for which chemical release