ISSS608 2016-17 T3 Assign DEBASISH BEHERA conclusion

VAST Challenge: Mini Challenge 2

Introduction

Data Preparation

Insight & Conclusion

Tableau Public: https://public.tableau.com/profile/debasish.behera#!/vizhome/Book4_3059/Story1?publish=yes

Question 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?

Month: April

Figure 1

Using of box-plot shows some of the outlier readings which are consistently very high.

From the figure, monitor 3 and monitor 6 are consistently showing very high readings every day.

Month: August

Figure 2

We notice that the readings are very high for the monitor 3,4 and 6. Monitor 3 is the one with the highest readings.

Month: December

Figure 3

• We notice that very high readings are showing for monitor 3,4 and 6.

• Monitor 4 is showing the highest reading.

Figure 4

• From the above figure, it is evident that the readings from monitor 3,4, 5 and 6 are consistently showing more than average readings throughout the 3 months’ period whereas monitor 1, 2 and 9 are showing consistent readings.

• Also, if we consider the readings of 7 and 8 there is some spike in the month of April but no spikes in the month of August and December.

After we have looked into the raw readings of the sensors we now have a look at the no of readings picked up by each of the sensors around the factory vicinity.

Ideally the no of readings that are captured by each of the sensors should be equal!

Figure 5

Figure 6

Figure 7

From the readings obtained for the month of April, August and December it seems that whenever there is an increase in readings of chemical AGOC-3A there is a decrease in the readings of the chemical Methylosmolene.

Also we can see that the readings captured by each of the sensors are not the same throughout the every month.

Conclusion:

• From the raw readings and number of readings recorded it seems that Sensor 7 and 8 were showing different readings for the month of april for AGOC and Methylosmolene but in the month of August and December the readings were constant.

• For the sensors 3,4,5,6,9 the no of readings recorded seems to change a lot especially for the month of August whereas the no of readings from sensor 1 and 2 varies very little throughout the 3 months time.

Question 2

Which chemicals are being detected by the sensor group? What patterns of chemical releases do you see, as being reported in the data?

From the calendar plot we get some interesting insights from it. We notice that the number of records for the month of April is low for every chemical reading on the 2nd and 6th of the month. For august it is getting repeated for the 2nd,4th and 8th of the month For December, there is no peculiar pattern that we can find. In December, the chemical readings are changing for the 2nd and 7th of the month. Now let us see the readings of the chemicals throughout the different monitor readings.

April:

AGOC-3A- monitor/sensor 4,5,6,8,9 are the group of monitors that are showing very high spikes in terms of readings mainly between 05:00 AM to 02:00 PM. Sensors 1 and 2 captures most of the readings throughout the day. Appluimonia- Monitor/sensor 6,7 and 9 are the groups of sensors that are showing very high spikes in readings. Chlorodinine-1,4,5,6,8 are the sensors group that captures most of the reading during 12:00 AM to 03:00 AM. Sensors 1,2,8 are able to capture the readings throughout the day. Methylosmolene-1,2,3,8 are the sensors that capture most of the readings throughout the day with sensors 4,6,7,8 showing high spikes only in the morning hours. Here we have to see whether this pattern exists throughout rest of the months as well.

August:

AGOC-3A- sensors 3,4,5,6 captured very high readings for this chemical between 5:00 AM to 4:00 PM Appluimonia -2,3 and 9 are the sensors that captured this chemical reading. Chlorodinine-sensors 3,4,8 and 9 captured most of the readings of this chemical Methylosmolene-1,8,9 are the sensors that captured most of the readings here. Whereas some spikes were observed by the sensors 2,5 and 6 during the time 12:00 AM to 6:00 AM

December:

AGOC-3A- Here the sensors 1,2,3 shows spikes in the readings at 6:00 AM where as the sensors 4,5,6 are picking up very high spike in the readings. Appluimonia – sensor 6 and 7 show high readings . Chlorodinine- sensor 5 and 6 here are showing some high readings. Methylosmolene-1,3,5,6,8,9 observed very high spikes in the readings during the night hours which seems to suggest that this chemical which is banned and most dangerous of all the chemicals are being released by the factory during the night hours. In our case, we observe the spike in the readings from 10:00 PM to 6:00 AM This trend is similar to the high spikes that was observed in the month of April. Also, it seems that this particular chemical shows spike in the morning hours but no spike between 6:00 AM to 10:00 PM which may suggest that the factories may have been neutralizing the chemical after 6:00 AM but at night they may not be doing so.

Question 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.

We will be looking into this chemical wise:

Chemical AGOC-3A:

sensor 5:

For the chemical AGOC-3A it seems that the sensor 5 is picking up the readings which is from the Factory Road runner.

Radiance is one of the factory that is responsible for the high reading. Also at this point the wind is fresh breeze.

sensor 6:

From the above figure it shows that sensor 6 picks up the chemical AGOC-3A from the factory Kasio

Sensor 7:

Kasio seems to be the factory which is emitting the chemical.

Chemical: Appluimonia

From the above figure it can be concluded that Road runner and Kasio are the factories responsible for the chemical release of Appluimonia.

Chemical: Chlorodine

sensor 5:

This chemical is being detected by sensor 5 which is emitted from the factory Radiance. This can be concluded because even though the wind is showing a light breeze the sensor is picking up the values.

Here Roadrunner is detecting the high readings for the chemical chlorodyne.

Chemical: Methylosmolene

Sensor 9:

Here it seems that indigo is the one that is responsible for the release of the gas Methylosmolene which can be picked up by sensor 9.

Here as per the figure the factory radiance and roadrunner are responsible for the release of the chemicals Methylosmolene.

Comments

Hi Debasish,

It is a great piece of work but I have following concerns:

- For question 1, did you combined four chemicals? I think maybe you should analyze the readings for each chemical.

- For question 1, maybe you can take multiple records into consideration.(high reading may due to multiple records)

- For question 2, would it be better if you include the color legend for horizon chart?

- For question 3, does fan-shape stand for influence area due to wind? Is it more clearer if they start by factories?

P.S. Interestingly we happen to have very similar content on our wiki pages. Such coincidence is surprising!

Thanks,

Jean