A Study on Best Location Selection Experiments, Using AHP ...iieng.org/images/proceedings_pdf/9172E1213628.pdfresource utilization, 'Outsourcing' is a portmanteau of the company's

Abstract— Public to make online content while many showing of

the traditional boundaries, production and consumption are

unraveling. The evolution of online access to information technology

facilitates comparable to professional and amateur engineers are born,

focusing on common interests among people formed community is

growing together.

Recently, based on these wide range of public companies can take

advantage of collective intelligence to effectively 'Crowdsourcing' has

attracted attention.

This study, the best location for AHP techniques and subsequent

analysis based on Crowdsourcing, So spatial information for crowd

mapping in the field of development of the concept proposed.

Keywords—Spatial Information, GIS, AHP technique,

Crowdsourcing, user participation.

I. INTRODUCTION

ROWDSORUCING is since 2006 contributing editor Jeff

Howe of 'Wired Magazine' presents a concept for the first

time [2]. That means of public, 'Crowd' and the external

resource utilization, 'Outsourcing' is a portmanteau of the

company's manufacturing, service and problem-solving process

an unspecified number of specific community or the public to

participate in raise efficiency of the approach.

In fact, companies that participate in the activities of the

general public that had been long. Is not a new concept.

Competition from the old form of advertising firms to get

ideas or the general public, such as product development with

the participation of potential customers have been derived

through the development [1].

Why this old concept revisited again recently received?

Yong-won Cho is with the Advanced technology Fusion, Konkuk

University, South Korea (corresponding author‟s phone: 82-10-9470-1010 ;

e-mail: [email protected]).

Mu-wook Pyeon is with the Civil Engineering, Konkuk University, South

Korea, (e-mail: [email protected]).

Il-woong Jang is with the Civil Engineering, Konkuk University, South

Korea (e-mail: [email protected]).

Tak Heo is with the Materials Chemistry & Engineering, Konkuk

University, South Korea (e-mail: [email protected]).

Fig 1. Jeff Howe says 'Crowdsourcing'(Google Image)

Already on-line is not on the lookout for the production and

consumption.

Also, thorough history of the community area centered

around the development of the online form, but they are not

necessarily in the same area around the private interests was to

form a community. People with common interests to share with

each other by exchanging information about online users are

getting smarter over time, as good as a professional engineer

and amateur engineers to be born. Only then could the old

company are now a variety of activities that the general public

[1].

In this study, taking advantage of user participation

Crowdsourcing the best commercial location analysis

techniques for utilizing AHP 'Google Earth' via mash-up

program on the experiment.

II. MAIN TECHNIQUES ARE DESCRIBED

A. Crowdsourcing

As mentioned earlier, many of Crowdsourcing development

and through user participation can be consumed. Today, based

on the evolution of online communication technologies with the

A Study on Best Location Selection Experiments,

Using AHP Technique

Yong-won Cho, Mu-wook Pyeon, Il-woong Jang, and Tak Hur

C

International Conference on Innovations in Engineering and Technology (ICIET'2013) Dec. 25-26, 2013 Bangkok (Thailand)

http://dx.doi.org/10.15242/IIE.E1213628 281

public to show the infinite possibilities[3].

Crowdsourcing is therefore beneficial to both businesses and

the public to be used, a systematic procedure based on a clear

sense of purpose can be satisfied through the participants should

be provided with appropriate incentives[1].

In this study, the 'Google Earth' on their GPS location will be

used to collect the floating population.

Fig. 2 The advantage of Crowdsourcing(SpinAct)

B. Google Earth

Google Earth is world of 3D digital maps, that Google's map

service[4]. Through this program, you can view its location, air

satellite imagery or road view can be provided through the

service.

In this study, to show the best position for the exact location

of their 'Google Earth' on the show.

Fig. 3 Google Earth

C. AHP technique

AHP technique is 'Analytic Hierarchy Process'. 'Analytic

Hierarchy Process and methods' is called[8].

That is the whole process of decision after it is divided by the

number of solving, step by step analysis method to reach a final

decision[8].

In this study, the experimental conditions are set for some

suggestion that these conditions was tested by applying the AHP

technique.

Fig. 4 AHP Hierarchies

D. Big Data

Big Data and efficient processing of such data, analysis, and

in order to take advantage of was the emergence, Big Data is

usually data volume, variety, velocity as a combination of three

factors is characterized by changes[5][7]. Big Data and analysis

techniques for processing such data, the text mining, opinion

mining, social network analysis, cluster analysis has dual

images similar to nested characteristics of the object together

with the cluster analysis technique was used for outgoing[6].

Fig. 5 Big Data(Fotolia)

III. EXPERIMENT FOR AHP TECHNIQUE & GOOGLE EARTH

In this study, to establish the following our topic were

experiment: 'What would be found in which place?'. For

calculating the AHP technique, we summary multiple properties

establishments, subway accessibility, land acquisition costs and

disgust facilities have or not. We selected test-bed and construct

database, finally visualization. We would like to find the best

location to build a franchises shop using GIS with the assistance

of AHP technique. 3 locations were selected to make

experiment. The best location was selected among three

candidates and shown in GIS and Google Earth.



A. Solution

First, we constructed data in GIS and selected criteria for

AHP: State, accessibility, economy and environment. Second,

we survey the score of respective criterion of each candidate

using GIS. Third, we use AHP to compute total score of each

candidate and suggest where is the best location. The data and

results are visualize in GIS and Google Earth.

B. Data Collection

Using an open data source with the increase if data quality,

accessibility and availability is more and more popular. 'Seoul

open data square' can provide the detail data about social and

economic. It contributes to the creation of a variety of private

business.

Fig. 6 Evaluate the items score

C. Experimental Area

We chose Konkuk university complex in Seoul, South Korea.

Because the most recent floating population in Korea showed

areas and excellent proximity to the laboratory were selected.

Below figure is Korea internet news script and choose

experiment area image.

Fig. 7 Experiment area and news script

Where we have about 3 locations, some conditions gave the

score.

Fig. 8 Comprehensive evaluation criteria scores

Fig. 9 Comparison matrix and relative elements

Fig 9. will be described. Example economy is more important

than accessibility. So its score comparing to accessibility is 3.

Fig 10 Calculated the relative proportion of assessment items

We will calculate the consistency ratio. Related to the

expression below.



3*332*321*31

3*232*221*21

3*132*121*11

3

2

1

333231

232221

131211

wawawa

wawawa

wawawa

w

w

w

aaa

aaa

aaa

tbytheweighMultiplied

(1)

weight

ytheweightMultipiedbyratioConsistenc )( (2)

Fig. 11 Consistent evaluation

Now, we make CI. CI is Consistency Index. Seeing the

indicator how much have consistency about result. Do not have

consistency : Someone „A‟ is more important than „B‟ and „B‟ is

more important „C‟, but evaluate „A‟ is less important „C‟.

When someone respond „A‟ is twice better than „B‟ and „B‟ is

three times better than „c‟, „A‟ is six times better than „C‟. C.I is

to verify the logical contradiction for response. If C.I is less than

0.1, that means comparison have a consistent.

Fig. 12 Consistency Index

Value of C is biggest, it mean C is the best location to build

the shop. We use to perform AHP: Excel, GIS, or some

programming language. We use to Excel.

Fig 13. Derived final relative importance

IV. RESULTS

Blue one is Structured data. The properties population

density, resident population, and red one is unstructured data.

When we visual the data we 'Google Earth' icons are the big

data they updated real time and so on.

Fig. 14 GIS platform layers to address Big Data & data construction

What did we use GIS to do? Structure data, Inquiry data, and

represent data? We use the GIS to allocate the flower store and

input the inquiry data. Population density, current population

and calculate these data within GIS.

Fig. 15 Using ArcGIS & Google Earth



If possible, please show the area of location C with its

attributes in this slide. You can see the location C from this

animation(the last part).

Fig. 16 The best location(Yellow round point)

V. CONCLUSION

We have selected the best location through a simple

experiment made the results. Simply not only one program is

used, appropriately using multiple programs results showed

efficient(Google Earth, Arc GIS and AHP technique).

And materials, as well as our existing data, you turned on the

GPS to determine the flow of people around, more accurate data

is available, were confirmed. This mean is through user

participation, as we want accurate data can be obtained.

User participation on the basis of Crowdsourcing, Crowd

game and Crowd map will be able to develop.

ACKNOWLEDGMENT

This work is financially supported by Korea Minister of

Ministry of Land, Infrastructure, and Transport as 『U-City

Master and Doctor Course Grant Program』 & This research was

supported by a grant(11 High-Tech Urban G10) from

Architecture & Urban Development Research Program funded

by Ministry of Land, Infrastructure and Transport of Korean

government.

REFERENCES

[1] J.H. Yoo, The wisdom of the masses to be successful crowdsourcing is

Mine, LG Business Insight, pp.46-53, 2010

[2] H. Jeff, Crowdsourcing, Google Image search, 2010

[3] Crowdsourcing Through Knowledge Marketplace, SpinAct, 2010

[4] S. J. Moon, M. W. Pyeon, C. J. Kim, S. W. Lee, N. G. Kang, “Element

Analysis for Constructing a Multidimensional Real-Time Map Service”,

ICONI, 2012

[5] O'Reilly Radar Team, Planning for Big Data, O'Reilly, 2012.

[6] M.M. Kang, S.R. Kim, S.M. Park, Analysis and utilization of Big Data,

Journal of Information Science, vol. 30, pp. 25-32, 2013

[7] C. Ben, Big Data Image, Fotolia(Google Image)

[8] Bishu, R. R. and Rajurkar, K. P. (1999), Analytical Hierarchy Process: A

Tool for Assessing Service Quality, Proceedings of the International

Conference on Delivering Service Quality edited by M. Raghavachari and

K.V. Ramani, India, December 28-29, 1999, 581-587.



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A Study on Best Location Selection Experiments, Using AHP ...iieng.org/images/proceedings_pdf/9172E1213628.pdfresource utilization, 'Outsourcing' is a portmanteau of the company's