Special Report

Special Report (Vol. 44)

  • 2019-01-15
  • You Chanyong

Special Report Vol. 44 (2018)

DEVELOPMENT STRATEGIES OF SMART CITY INFRASTRUCTURE FOR URBAN REGENERATION


Chapter I. Introduction

1. Backgrounds and Objectives of Study

2. Scope and Methodology of the Study


Chapter II. Theoretical and Literature Research

1. Definition of Smart City Infrastructure

2. Definition on Concept of Smart City Infrastructure

3. Effect of Smart City Infrastructure Policy in Urban Regeneration

4. Differentiation of the Study


Chapter III. Target District Status and Citizens Demand Survey

1. Selection of the Target District and Framework of Analysis

2. Results of Field Investigation

3. Results of Citizens Survey

4. Target District Analysis Overview and Direction Setting

Chapter IV. Smart City Infrastructure Improvement Plan

1. Open Space Network Building

2. Hub Space Building

3. Citizens Project Plan

4. Smart City Improvement Initiatives to Align with Urban Regeneration

Chapter V. Conclusions

1. Establishment of Institutional Basis of Smart City Infrastructure Building for Urban Regeneration

2. Establishment of Institutional Basis for Modularized Smart City Infrastructure

3. Assuming as the Same in Applying Regulations

References



Summary

The operational definition of a smart cell and the process of producing information

about smart cells can be understood as follows for the purposes of this study. A smart

cell is the minimum unit of territory in which individual spatial information (e.g., personal

characteristics and location) is identifiable in real time.


Smart cells can track the behavior of individuals through space by means of lines

(representing movement) and dots (representing individuals), which can be seen moving

in and out of smart cells. Data for this purpose are collected by mobile phone base

stations and processed by wireless service carriers.


Smart cells have a number of applications in transportation and spatial planning policy,

as data from smart cells are scalable and can thus be extrapolated to different spatial

hierarchy levels such as towns and regions.


This research sought to analyze activity in the Seoul metropolitan area along gender and

age lines at different times of the day. The central focus of activity in the city was found

to shift over the course of a day, from Seoul’s south side at 7 a.m. to north side by noon,

and back south again by 6 p.m.


On the demographic distribution for age groups, the analysis showed greater activity in

southern Seoul among men, whereas women were more active in the city center.

This study tracked human activity in real time in Gangnam-gu (ward), an upscale and

busy area in southern Seoul, using mobile big data generated by smart cells. Human

activity, the survey found, was highly concentrated near subway stations, especially

Gangnam and Yeoksam. Weekend activity was also monitored in and around Seoul

Land, one of the capital region’s most popular amusement parks, and parking lots saw

peak levels of congestion Saturdays between noon and 3 p.m.


Smart cells are likely to prove extremely helpful in the event of a natural disaster or

other emergency thanks to its ability to provide real-time information on human activity

in a specific location, including the number of people and their precise coordinates.

This study evaluated the utility of smart cells in a hypothetical disaster scenario in which

an extreme heat wave hits Jongno-gu, an administrative ward in central Seoul. In the

event of a predictable, slow-occurring disaster such as extreme heat wave, smart cells

have applications in three stages: the advance warning stage, in which authorities issue

an excessive heat advisory and urge appropriate precautions; the emergency stage, in

which they prepare to evacuate people in high-risk areas; and the evacuation stage.

The scenario analysis demonstrates that smart cells can be used in developing countries

in the following four ways:


First, smart cells can help build statistical databases for the purpose of better

understanding population trends and the habits of the economically active population.

Developing countries tend to lack basic statistical data on such matters because of

budget constraints and underdeveloped social institutions. As this study shows, wireless

carriers’ databases and mobile big data can possess significant information about human

activity in any country with a high rate of mobile phone penetration. By using smart cells

to gather basic social statistics that could otherwise be obtained only through surveys,

developing countries stand to save significant time and costs.


Smart cells also enable spatial planners to implement policies at different levels within

the spatial hierarchy (e.g., nation, region or city). National territorial policy transcends

boundaries such as those between new and old city centers. Smart cells can help achieve

policy objectives at different levels in the spatial hierarchy; it commands high value for

macro spaces such as countries and regions, as well as micro spaces such as towns and

districts.


Smart cells also have business applications. Merchants who wish to start small

businesses can preemptively use the data to reduce their risk of failure. Equipped with

a clearer understanding of trends in human activity in a given area, entrepreneurs can

be better prepared to serve their potential markets. In developing countries, many

new entrepreneurs have recently moved to large cities and lack knowledge about their

respective markets. Information obtained through smart cells can prove indispensable

for such a purpose.


Furthermore, smart cells can be incorporated into disaster prevention and response

systems. Mobile big data is a mobile phone-based system of automatic data collection

that enables constant monitoring of the number of people in a given area who are

especially vulnerable to a natural or social disaster. Continuous monitoring is an

effective tool for disaster prevention in regions at high risk of natural or social disaster.

Developing countries with insufficient databases for basic statistics can use smart cells

in the event of a disaster to forecast the number of casualties and devise effective

responses. In the event of a disaster, this technology can send to emergency response

teams highly reliable information in a timely fashion to expedite the decision-making

process and minimize casualties.

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