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スマートシティ:都市データ - デジタルコミュニティにおけるピボットエレメント
Smart City Urban data: a pivotal element in digital communities
■商品番号 idatedec27 ■出版日 2014-12-27
■出版社 イダテ社 ■ページ数 70
■図表数 お問い合わせください ■価格 EUR 3,000
■商品形態 電子媒体    
注:外貨表示の価格は購入申込日のTTSレートで換算し、消費税を加えたものが商品の購入価格になります。
レポート概要
This report explores the topic of smart cities from the perspective of the urban data generated by the city's various stakeholders: public and private sector players and citizens. It inventories the different sources of urban data, and examines the issues surrounding their collection, storage and processing.

The report then looks at the different ways these data can be utilised and monetised, and presents the main problems that have been identified by smart city initiatives: business models, governance, citizen involvement.

These different topics are described by drawing on multiple examples that have been tested or deployed in different cities around the globe.


目次

Report contents

1. Executive Summary

1.1. Mass production of urban data
1.2. Is it smart to pool urban data, and their collection?
1.3. The challenge of making urban data, open data
1.4. Do we need national governance for urban data?

2. Methodology & definitions

2.1. IDATE's general methodology
2.2. Methodology specific to this report
2.3. Definitions

3. The what and why of urban data

4. The prospect of a huge surge in the production of urban data

4.1. Government and citizen data
4.2. Sensors and tags
4.2.1. Infrastructure sensors
4.2.2. Tags: RFID, NFC, QR code
4.3. Citizen-generated data
4.3.1. Personal sensors
4.3.2. Examples of citizen-generated data
4.4. External data
4.4.1. The Internet
4.4.2. Other possible sources of data

5. Collection urban data: from juxtaposed to shared networks

5.1. Available networks
5.1.1. WPAN technologies
5.1.2. Ultra Wide-band (UWB)
5.1.3. Proprietary technologies
5.1.4. Cellular networks
5.2. The challenge of streamlining backhaul networks

6. Storage and processing: the heart of any urban data utilisation project

6.1. The challenge of making urban data, open data
6.1.1. Open Data: first small forays
6.1.2. Open data specialists
6.2. Storing urban data
6.3. Processing urban data
6.3.1. Quality of the data and prior processing
6.3.2. APIs: automating data transfers
6.3.3. The emergence of big data
6.3.4. Visualisation

7. Putting urban data to work: complementary approaches in search of a winning model

7.1. Private sector approach to utilising urban data
7.1.1. Developing businesses and creating new professions
7.1.2. New specialised players
7.1.3. How telcos and IT service companies are positioned in the market
7.2. Public approach
7.2.1. The city as decision-maker
7.2.2. The city as data manager
7.3. Public-private approach
7.4. Managing the ecosystem
7.4.1. Incubators
7.4.2. Living labs
7.4.3. Challenges, contests and other incentive measures

8. Urban data: still a number of unknown

8.1. Legal and regulatory framework governing data
8.1.1. Personal data
8.1.2. Data from public actors
8.1.3. Data from private actors
8.2. Standardising urban data
8.3. Business models
8.3.1. Expected benefits
8.3.2. Potential sources of financing

9. Conclusion: stepping stones to urban data governance

Report figures

Figure 1: Processing urban data
Figure 2: The five main sources of data for smart city applications
Figure 3: The different types of data collected by smart city sensors
Figure 4: Main types of network deployed in a city
Figure 5: String of networks used to collect sensor data
Figure 6: Open data portals around the globe
Figure 7: Urban data: revenue sources and externalities
Figure 8: Technical layers enabling the use of urban data
Figure 9: The main vertical services targeted by smart city initiatives
Figure 10: Some recent smart city market estimates
Figure 11: The main living labs around the globe
Figure 12: Estimated number of connected objects in use around the globe
Figure 13: Processing urban data
Figure 14: The five main sources of data for smart city applications
Figure 15: Open data portals around the globe
Figure 16: Examples of free parking space and full rubbish bin sensors
Figure 17: The different types of data collected by smart city sensors
Figure 18: The connected boulevard in Nice
Figure 19: QR code/NFC tags for accessing different services
Figure 20: QR code/NFC tags for accessing different services
Figure 21: The "Fix my Street" service in Brussels
Figure 22: How the Green Watch works
Figure 23: Map of connected Netatmo personal weather stations
Figure 24: How data is captured for the Urban Emotions project
Figure 25: "Rate my area" home screen
Figure 26: Map of the number of photos taken by location in New York
Figure 27: Live Singapore! taxis and rain screen
Figure 28: Example of the Waze  Berlin application interface
Figure 29: Main types of network deployed in cities
Figure 30: PAN ecosystem
Figure 31: Main wireless technology networks
Figure 32: Mobile technology specifications
Figure 33: String of networks used to collect sensor data
Figure 34: Storing and processing urban data
Figure 35: The datacentre ecosystem
Figure 36: The open data ecosystem
Figure 37: Dashboard for France's data.gouv.fr open data site
Figure 38: Functionalities offered on the OpenDataSoft site
Figure 39: A selection of datacentres that are part of PIN in France (non exhaustive list)
Figure 40: Using API for the different sources of urban data
Figure 41: Using tweets to indicate flooded areas in Jakarta
Figure 42: Priority targets for smart city projects
Figure 43: IBM Smart Water: the operator's view  selecting events, asset types and logical zones to display on a geospatial map
Figure 44: Schneider Electric: applying existing expertise to the smart city
Figure 45: INEO  GDF Suez: utilising data for the national benefit
Figure 46: Ondeo Systems: overview of the water data processing chain
Figure 47: M2ocity: overview of the water data processing chain
Figure 48: Deutsche Telekom: an integrated and centralised approach to the smart city
Figure 49: Traffic management system in Berlin
Figure 50: New York City: the DataBridge Store
Figure 51: The main mobility-related data made available by Metropolitan Lyon
Figure 52: Main public and private sector players involved in the latest edition of Datact
Figure 53: The Datalyse approach to processing big data
Figure 54: Approaches to smart cities
Figure 55: Tel Aviv  a map of start-ups
Figure 56: The "Tuba" living Lab in the Part-Dieu neighbourhood of Lyon
Figure 57: Data discovery challenge  Singapore December 2014
Figure 58: Public concern over how their personal information is used on the Internet (on the left Europe; on the right, the United States)
Figure 59: Percentage of people willing to share personal information depending on the reward they receive in exchange
Figure 60: Urban data: revenue sources and externalities
Figure 61: Home page for the Spacehive crowdfunding platform
Figure 62: Examples of crowdfunding platforms

Slideshow contents

1. The smart city and urban data
" The smart city
" Urban data
" Sources of urban data
" Collecting urban data
" Processing and storing urban data

2. Utilising and monetising data
" Utilising and monetising urban data

3. The central issues surrounding urban data
" Issues surrounding urban data

http://www.dri.co.jp/auto/report/idate/idatescity.html


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