AutonomousOnlinePredictiveMonitoringSystem
forhazardousairpollutionprediction:ACaseStudy
AYEDA.SALMAN&FAWAZ SAL-ANZI
ayed.salman@ku.edu.kw &alenzi.f@ku.edu.kw
COLLEGEOFCOMPUTINGSCIENCESANDENGINEERING
KUWAITUNIVERSITY
GET 2016 - Kuwait - 26th - 28th Jan, 2016.
Environment – Human Relationship
economic
development
illness
GET 2016 - Kuwait - 26th - 28th Jan, 2016.
Air pollution
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An average of 2 million people are
killed worldwide every year due to air
pollution
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Air pollution in China alone is related
to around 656,000 deaths every year
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In a survey of more than 100 cities,
the World Bank has found that the air
in many urban areas remains
unhealthy
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Air pollution increasingly affects
climate changes directly by
preventing sun heat from escaping
from atmospheric back to the space
(Source: National Geographic News)
GET 2016 - Kuwait - 26th - 28th Jan, 2016.
Source: European environmental Agency: http://www.eea.europa.eu/data-andmaps/figures/rise-of-greenhouse-gases-concentration-compared-with-the-year-1750
Kuwait Air Quality
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Current population of Over 4 million
Industrial areas are of closed proximity to residential areas.
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A recent study showed that concentrations of the following air pollutants CH4,
CO, O3, SO2, NOx and total sulfur (TS), had increased over the period (19982004)
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The same study shows that NOx and SO2 exceed the permitted standard levels.
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Alwadhi (2014) stated that factories like the one in oil industry are a major
contributor to pollution in Kuwait.
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Sources:
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Al-Mutairi, N. and Koushki, P, Potential Contribution of Traffic to Air Pollution in the State of Kuwait. American, Journal of Environmental Sciences, 5,
218-222, . (2009).
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Jasem M. Al-Awadhi, Measurement of Air Pollution in Kuwait City Using Passive Samplers, Atmospheric and Climate Sciences, 4, 253-271, , 2014.
GET 2016 - Kuwait - 26th - 28th Jan, 2016.
Data mining
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Data mining is a computer science field
in which a computational process is
used for discovering patterns in large
data sets using methods from artificial
intelligence.
Data
Acquisition
Classification
Prediction
Clustering
Regression
Data
Mining
Association
Autonomous
Predictive
system
GET 2016 - Kuwait - 26th - 28th Jan, 2016.
building an autonomous system for
Hazardous rates prediction
GET 2016 - Kuwait - 26th - 28th Jan, 2016.
System Details (1):
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Phase 1: Data acquisition & preparation:
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every 15 minutes: Raw data readings of gases such as CH4, CO, CO2,
NO, NO2, SO2, and H2S is acquired using mobile sensors around the
industrial area for a period of time ( ~ 2 months time).
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Data is transferred to a central server
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average readings for 1, 12 and 24 hours is calculated & stored as well.
GET 2016 - Kuwait - 26th - 28th Jan, 2016.
Phase 2: Data Mining
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Data is divided into training and testing
sets
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Data Mining algorithm is used to learn the
pattern using training set
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The same algorithm is tested using the
testing set, once satisfactory results à
System goes online.
GET 2016 - Kuwait - 26th - 28th Jan, 2016.
Testing set
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Training set
System Details (2)
1.2 0.3 0.5 3.2 01.2 30.2
2.3 4.3 0.57 3.2 11.2 21.4
2.22 3.4 4.6 0.8 2.1 7.1
1.2 0.3 0.5 3.2 01.2 30.2
1.2 3.4 4.6 0.8 2.1 7.1
2.2 0.3 0.5 3.2 01.2 30.2
2.3 4.3 0.57 3.2 11.2 21.4
2 3.4 4.6 0.8 2.1 7.1
1.2 0.3 0.5 3.2 01.2 30.2
2.22 3.4 4.6 0.8 2.1 7.1
1.2 0.3 0.5 3.2 01.2 30.2
3.4 4.6 0.8 2.1 7.1 01.2 30.2
2.3 4.3 0.57 3.2 11.2 21.4
2.22 3.4 4.6 0.8 2.1 7.1
System Details (3)
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Online Phase:
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Continuous Data acquisition
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Continuous prediction for 1, 12, 24 hours period.
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Alert is sent to managers in case rates goes beyond standards
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Reports are generated continuously
GET 2016 - Kuwait - 26th - 28th Jan, 2016.
BIG Picture
GET 2016 - Kuwait - 26th - 28th Jan, 2016.
Screen Shot of Prediction Report
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Prediction
Reaches as
high as 99.8%
for some
gasses
especially for
larger
periods (12
hours or 24
hours)
GET 2016 - Kuwait - 26th - 28th Jan, 2016.
Screen Shot of Monitoring Interface
GET 2016 - Kuwait - 26th - 28th Jan, 2016.
System Reliability
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Data transfer temporally disruption
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Mobile station Shutdown (intentional or unintentional)
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Concurrency problem.
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Dealing with Multi-norms
GET 2016 - Kuwait - 26th - 28th Jan, 2016.
70
Conclusion
60
50
40
30
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System was able to achieve
error percentage below 10%
within a 15 days of
operation only when
reading does not contained
abnormalities.
System is being able to
adjust itself once spikes in
data reading fade away.
20
10
predicted_value
0
0
5000
average_value
10000
15000
20000
70.00%
60.00%
50.00%
40.00%
30.00%
20.00%
10.00%
0.00%
-10.00%
0
200
400
600
error_value
GET 2016 - Kuwait - 26th - 28th Jan, 2016.
800
1000
GET 2016 - Kuwait - 26th - 28th Jan, 2016.