Smart Cities in Taiwan: A Perspective on Big Data Applications
1.1. The Smart City
1.2. Big Data
- to foster decision-making and accountability;
- to determine where funds are sent;
- to determine whether funding is being sent to the right place;
- for monitoring and evaluation;
- to identify changes over time;
- to determine whether such changes were caused by a specific intervention;
- to identify other factors that may have caused the outcome .
1.4. Planning of Smart Cities in Taiwan
2. Development of a Smart City
2.1. Development Indicators and Rating Mechanisms of International Smart Cities
- The European Smart City Index  employs the dimensions smart economy, smart people, smart governance, smart mobility, smart environment, and smart living and refines them into different indicators, assigning weights to assist ratings.
- After an overall assessment and formation of indicators, the Intelligent Community Forum (ICF)  promotes city or community management philosophies and operating models to city leaders. Additionally, they commend the achievements of cities in using ICT to develop a smart city through the ICF Awards, promoting exchange and learning between cities.
- SMART , the theoretical model of China’s smart city evaluation indicator system, comprises five key elements: service, management and maintenance, application platform, resources, and technology.
- The Foreseeing Innovative New Digiservices (FIND) model  was designed by the Institute for Information Industry in hopes of employing rational research data and physical examination analysis to enhance the quality of life of urban residents and firm competitiveness.
2.2. Smart City Commercial Application Structure
- The underlying sensing equipment (e.g., Internet of Vehicles (IoV), QR codes, IP Cam, radio-frequency identification (RFID), eTag, and geographic information systems (GIS)) generate data, which are collected and converted using the interface.
- The IoT technology is used to collect information. Information is gathered through mobile networks or social networks into a database or data warehouse (e.g., Oracle, DB2, and Teradata) for information-related storage cloud operations.
- Subsequently, after extraction of various types of databases, transaction data and behavior log data are separately imported into the big database (such as Hadoop) of the converged data platform. This is the core of Big Data.
- After processing of the data, customers can use the Mobile Network to search for information.
- Various types of smart business applications are thus generated.
2.3. Mobile Network
2.4. Cloud Computing
2.5. The IoT
2.6. Range of Application of Smart Cities in Taiwan
3. Big Data
3.1. Big Data Management
3.2. Big Data Activation and Application
- Input: Different types of data are input through the system and network interface to the data access module.
- Data Access: For the access interface, which is responsible for connecting to external heterogeneous platforms and applications, the commonly used kits and functions are Kafka distributed messaging, Sqoop for relational database connectivity, flume data clustering, and HttpFS (Hadoop Distributed File System, HDFS) supported HTTP (Hypertext Transfer Protocol) links and operations.
- The data store is the primary data storage system for a Big Data platform. HBASE is the database system used by Hadoop. The file system is the primary file storage system for the Big Data platform, and HDFS is the DFS (Distributed File System) used by Hadoop.
- RUN TIME is primarily responsible for parallel operations and program execution. MapReduce processes large volumes of data for Hadoop and complies with system architecture with a high fault tolerance. Spark is a cluster computing framework that uses in-memory computing technology. YARN (Hadoop MapReduceV2) processes large volumes of data for Hadoop 2.0, complies with system architecture with a high fault tolerance, and is also called MapReduce 2.0.
- The advanced analysis engine is used for kits related to statistical analysis and machine learning. R language is employed for statistical analysis and machine learning. Mahout and SAS Viya are approximately similar; it is most convenient to use the MapReduce function library for distributed analysis and machine learning operations.
- The application and development platform uses related development tools for various developments and applications of Big Data. Text Analytics is employed for text mining and analysis, and Apps is used for mobile application development. Storms is a fault-tolerant distributed open-source computing system and Hive uses SQL syntax to access Hadoop data; Pig is employed for data manipulation and processing, and Impala is used for high-performance SQL-like access of Hadoop data.
- Management: The collaborations between each component and resource management include the monitoring and setting of files, databases, and system resources. ZooKeeper collaborates with the internal servers of Hadoop, and Oozie is a workflow manager on Hadoop. The purpose of Sentry for Apache Sentry is to handle privilege management; it is a policy engine used by data processing tools to verify access rights. Ambari is a tool for establishing, managing, and monitoring Hadoop clusters.
- Security: The system security is responsible for authorization, verification, and encryption tools. Kerberos is a network authentication protocol used for secure identity authentication of personal communication on insecure networks. LDAP is an open, neutral, and industry-standard application protocol that uses IP protocol to control access and maintain the directory information of distributed messages. Guardium automates all compliance workflows in a heterogeneous environment to ensure the privacy and integrity of reliable information in the data center.
- The output module renders outputs using visualization, statistical graphs, and reports.
4. Current Developments in the Smart Cities of Taiwan
- Broadband connectivity: Including subscribers of various telecom services and penetration rates of various telecom services (total 4G subscribers for mobile subscribers in 2014; mobile broadband subscribers including data transmission services for 3G, 4G subscribers and Wireless Broadband Alliance (WBA) subscribers; fixed networks including ADSL (Asymmetric Digital Subscriber Loop), FTTx (Fiber To The x), Cable Modem, leased lines and Public WLAN (PWLAN) subscribers; other broadband subscribers include PWLANs and leased lines) [29,30,33].
- Marketing and advocacy: Calculated by the ratio of the following Items—Internet Services, the Principal Indicators of Family Income and Expenditures, Result of Promotion for Community Development/Revenue and Expense for Operations Funds, Tourist Businesses and Inbound Visitors, Number of Visitors to the Principal Scenic Spots, Number and Capital of Companies Registered—by Organization and Industrial Classifications, Actual Number of Personnel in the Organic Structure with Subsidiaries [27,28,34,35,36,37,38,39].
- Sum: The sum of above.
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|Rating Name||First Use||Place of Origin||Originating Institution||Indicator Orientation||Object of Evaluation|
|European Smart City Index||2007||Austria/Slovenia/the Netherlands||Vienna University of Technology, University of Ljubljana, Delft University of Technology||Smart economy,|
|Medium-sized cities in Europe|
|Intelligent Community Awards||1985||United States||World Teleport Association, WTA (Intelligent Community Forum, ICF)||Broadband connectivity,|
marketing and publicity
|Cities worldwide (communities)|
|SMART||2013||China||China Software Testing Center||Intellectualized city infrastructure,|
intellectualized city management,
intellectualized city services,
open information resource integration,
intellectualized city industry
|Cities in China|
|FIND||2010||Taiwan||Foreseeing Innovative New Digiservices||Intellectualized city ability,|
benefits of intellectualized city construction
|Cities in Taiwan|
|Number of Motor Vehicles||Number of Factories|
|New Taipei city||2053||3,970,644||1934.48||3,193,363||18,251|
|City||Developmental Characteristics||Implementation Characteristics||Current Status|
|New Taipei city||Mobile applications||Perform public service mobilization and informatization, reduce the urban–rural information gap, and increase public service efficiency and the degree of public participation||Implementation stage|
|Taipei city||Network convenience|
|Promote the Taipei free (TPE-Free) wireless Internet in the city and use the open data platform to create an innovative industry development environment||Implementation stage|
|Taoyuan city||Regional development||Use the Taoyuan Aerotropolis as a center, promote various smart applications, and diffuse and copy successful models to corners of the city||Planning stage|
|Taichung city||Industry investment||Use vigorous local commercial power; the introduction of crucial large-scale construction and investment in key economic parks will create innovative industrial development environments and create a new look for the city||Planning and implementation stages|
|Tainan city||Low-carbon sustainability||Low-carbon city development as a primary idea; promote the value-added application of smart electric cars, a smart grid, a mobile sightseeing service. and smart agricultural marketing-related business||Planning and implementation stages|
|Kaohsiung city||Humanistic transportation||Promote green transportation information services, enhance public service efficiency, create a new mobile objective for the city, and establish a favorable environment that is low-carbon and sustainable||Implementation stage|
|Broadband Connectivity||Knowledge Workforce||Innovation||Digital Inclusion||Marketing & Advocacy||Sum|
|New Taipei city||9.12||5.8||6.8||0.2||7.0||28.92|
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Wu, S.M.; Chen, T.-c.; Wu, Y.J.; Lytras, M. Smart Cities in Taiwan: A Perspective on Big Data Applications. Sustainability 2018, 10, 106. https://doi.org/10.3390/su10010106
Wu SM, Chen T-c, Wu YJ, Lytras M. Smart Cities in Taiwan: A Perspective on Big Data Applications. Sustainability. 2018; 10(1):106. https://doi.org/10.3390/su10010106Chicago/Turabian Style
Wu, Shiann Ming, Tsung-chun Chen, Yenchun Jim Wu, and Miltiadis Lytras. 2018. "Smart Cities in Taiwan: A Perspective on Big Data Applications" Sustainability 10, no. 1: 106. https://doi.org/10.3390/su10010106