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市場調查報告書

智慧城市:主要平台,市場區隔分析及預測 (2019-2023年)

Smart Cities: Leading Platforms, Segment Analysis & Forecasts 2019-2023

出版商 Juniper Research Ltd 商品編碼 322747
出版日期 內容資訊 英文
商品交期: 最快1-2個工作天內
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智慧城市:主要平台,市場區隔分析及預測 (2019-2023年) Smart Cities: Leading Platforms, Segment Analysis & Forecasts 2019-2023
出版日期: 2019年04月23日內容資訊: 英文
簡介

本報告提供全球智慧城市市場相關調查,各市場區隔的市場規模 (能源/成本/廢氣數量的削減規模、軟體投資額等)的變化與預測,相關組織、經營者分析等資料彙整。

策略 & 競爭

第1章 智慧城市:進化的市場動態

  • 簡介
  • 智慧城市採購
  • 智慧城市平台分析
  • 連接性

第2章 市場區隔分析

  • 簡介
  • 智慧型能源
  • 智慧運輸
  • 智慧健康

第3章 智慧城市平台的供應商分析 & Leaderboard

  • 簡介
  • Juniper Leaderboard
  • 智慧城市的主要企業
  • 相關利益者分析
    • AT&T
    • Bosch
    • Cisco
    • Ericsson
    • GE
    • 日立
    • Huawei
    • IBM
    • Intel
    • Itron
    • Nokia
    • Oracle
    • Schneider Electric
    • Siemens
    • Verizon

資料 & 預測

第1章 智慧城市:進化的市場動態

第2章 智慧城市預測:基本資料 & 摘要

  • 簡介
  • 人口
  • 電力批發價格
  • 廢氣相關要素
  • CO2e的經濟價值
  • 預測的摘要
  • 降低成本的摘要
  • 軟體支出額的摘要

第3章 智慧電網預測

  • 簡介
  • 調查手法、前提條件
  • 城市的能源消費量
  • 智慧電網的能源削減量
  • 智慧電網的能源 & 降低排放成本
  • 智慧電網軟體支出額

第4章 智慧運輸管理 & 停車預測

  • 簡介
  • 調查手法、前提條件
  • 智慧運輸管理的減少排放廢氣量
  • 智慧運輸管理的降低成本額
  • 智慧運輸管理軟體支出額
  • 智慧運輸管理硬體設備支出額
  • 智慧停車的減少排放廢氣量
  • 智慧停車的降低成本額
  • 智慧停車軟體支出額
  • 智慧停車硬體設備支出額
  • 智慧流量 & 智慧停車的摘要

第5章 智慧照明預測

  • 簡介
  • 調查手法、前提條件
  • 智慧路燈的能源削減量
  • 智慧路燈的減少排放廢氣量
  • 智慧路燈的能源 & 降低成本
  • 智慧路燈軟體支出額
  • 智慧路燈硬體設備支出額

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目錄

Overview

Juniper's latest ‘Smart Cities’ research takes a deep dive into the evolving platform landscape across the market; highlighting multiple vendors' and cities' strategies aligned with a series of recommendations and opportunities for stakeholders.

Juniper's must-read research provides unique insights into this market; providing in-depth analysis of key smart city segment market forces and future outlook for the market.

The analysis covers key industry service segments, including:

  • Smart Grid
  • Smart Urban Mobility
  • Smart Traffic Management
  • Smart Parking
  • Smart Street Lighting
  • Smart Health

This research suite includes:

  • Deep Dive Strategy & Competition (PDF)
  • 5-Year Deep Dive Data & Forecasting (PDF & Excel)
  • Executive Summary & Core Findings (PDF)
  • 12 months' access to harvest online data platform

Key Features

  • Sector Dynamics: Multi-segment strategic assessment and breakdown; examining key Smart City platform strategies, business model innovation and future outlook:
    • Smart Grid
    • Smart Street Lighting
    • Smart Urban Mobility
    • Smart Traffic Management
    • Smart Parking
    • Smart Health
  • Procurement Analysis: Evaluation of Smart City business models, in relation to:
    • P3 (Public-Private-Partnership) analysis
    • Investment recovery models
  • Interviews with leading players, including:
    • Dimonoff
    • EnergyHub
    • IoT Living Lab
    • Nokia
    • Passport
    • Ruckus Networks
    • Trafi
  • Juniper Leaderboard: Key player capability and capacity assessment for 15 Smart City platform vendors:
    • AT&T
    • Bosch
    • Cisco
    • Ericsson
    • GE
    • Hitachi
    • Huawei
    • IBM
    • Intel
    • Itron
    • Nokia
    • Oracle
    • Schneider Electric
    • Siemens
    • Verizon
  • Benchmark industry forecasts: market segment forecasts for key Smart City verticals, including:
    • Software Spend
    • Hardware Spend
    • Energy Saving
    • Emissions Saving
    • Cost Saving

Key Questions

  • 1. Who are the leading Smart City platform vendors, and how do they differentiate strategically?
  • 2. Which strategies should cities look to apply when developing Smart City projects?
  • 3. What are the key trends shaping Smart City policy and service markets?
  • 4. What are the prospects for city smart energy, transport services and lighting markets?
  • 5. What is the economic opportunity for smart city projects?

Companies Referenced

  • Interviewed: Dimonoff, EnergyHub, IoT Living Lab, Nokia, Passport, Ridecell, Ruckus Networks, Trafi.
  • Profiled: AT&T, Bosch, Cisco, Ericsson, GE, Hitachi, Huawei, IBM, Intel, Itron, Nokia, Oracle, Schneider Electric, Siemens, Verizon.
  • Case Studied: CityBridge Consortium, Con Edison, Didi Chuxing, Dimonoff, EnergyHub, Huawei, IoT Living Lab, Neusoft, Passport, Ruckus Networks, Surtrac, Trafi.
  • Mentioned: ABB, Accenture, Acuity Brands, Advanced Control Systems, AGT International, Alcatel Lucent, Alibaba, Alphabet, Alstom SA, Amazon, Apple, Argonne National, Arris, AutoGrid, Avrio, Bell Canada, Bharti Infratel, Bidgely, BlaBlaCar, Black & Veatch, Boeing, Bouygues Telecom, Broadcom, Burbank, BVG (Berliner Verkehrsbetriebe), Capgemini, Chicago Innovation Exchange, China Communications Standards Association, Choice! Energy Management, Citi Bike, CITIXL (City Innovation Exchange Lab), Citrix Systems, Citybeacon, CivicSmart, Colorado Smart Cities Alliance, Comark, Connode, Control Group, Cyber Defense Institute, Cyber Security Association of China, Deloitte. Deutsche Telekom, Downer, Dynamic Ratings, EnergyHub, Esri, Estuate, FIDO Alliance, Ford, Freescale Semiconductor, Frost Data Capital, G+D, Genetec, GlobalLogic, Google, Görlitz, Grab, HKSTP (Hong Kong Science and Technology Parks Corporation), Honda, Honeywell, i2O Water, Infosys, INRIX, IRCTC (Indian Railway Catering and Tourism Corporation), JDA, KPMG, Landis+Gyr, Living PlanIT, London Health Commission, Lyft, Masdar Institute of Science and Technology, Master Meter, Meridium, Microsoft, Mizuho Bank, Monaco Telecom, Moniteye, NACTO, National Science Foundation, NEC, Nedaa, NEDO (New Energy and Industrial Technology Development Organisation), NHS (National Health Service), NTT DoCoMo, NXP, Oi Brasil, Ola, OPower, OSIsoft, oXya, Pantascene, Parkeon, Paytm, Philips, Plug and Play, PVT, Qualcomm, Reliance Energy, Renault, Reuters, Rongwen, Samsung, SAP, SAS, SELC, Sensity Systems, Sentient, Shotspotter SST, Silver Spring Networks, SmartGridCIS, SoftBank, Software AG, Songas, Southern Company, Sprint, Streetline, Synchronoss, Tapp, Tata, Tech Mahindra, Telit, Telstra, Tencent, Tendril, TfL (Transport for London), Titan, Trainline, Ubicquia, urbancontrol, Veolia, VMWare, Vodafone, Waymo, Weiqiao Pioneering Group, Wheaton Franciscan, WHO, Wind River, Wipro, World Wide Web Consortium, Zain, Zaphod.

Data & Interactive Forecast

Juniper's ‘Smart Cities’ forecast suite includes:

  • Segment splits for:
    • Smart Grid
    • Smart Traffic Management
    • Smart Parking
    • Smart Street Lighting
  • Regional splits for 8 key regions, as well as country level data splits for:
    • Canada
    • China
    • Denmark
    • Germany
    • Japan
    • Norway
    • Portugal
    • Spain
    • Sweden
    • South Korea
    • UK
    • US
  • Interactive Scenario Tool allowing users to manipulate Juniper's data for 6 different metrics.
  • Access to the full set of forecast data of 77 tables and over 10,300 datapoints.

Juniper Research's highly granular interactive Excels enable clients to manipulate Juniper's forecast data and charts to test their own assumptions using the Interactive Scenario Tool, and compare select markets side by side in customised charts and tables. IFxls greatly increase clients' ability to both understand a particular market and to integrate their own views into the model.

Table of Contents

Deep Dive Strategy & Competition

1. Smart Cities: Evolving Market Dynamics

  • 1.1 Introduction
    • 1.1.1 The Journey to Becoming a Smart City: Key Strategic Considerations for Cities
    • 1.1.2 Talent Acquisition
    • 1.1.3 Governance
    • 1.1.4 Innovation
      • Case Study: Amsterdam IoT Living Lab
  • 1.2 Smart City Procurement
    • 1.2.1 P3 Analysis
    • 1.2.2 Investment Recovery Through Advertising
      • Figure 1.1: LinkNYC Kiosk
      • Case Study: LinkNYC
      • i. Procurement
      • ii. Investment Recovery
      • iii. Juniper's View
  • 1.3 Smart City Platform Analysis
    • 1.3.1 Strategic Approach
      • i. Security Considerations
  • 1.4 Connectivity
    • 1.4.1 Low Power Wide Area Networks
      • Figure 1.2: Total Low Power Smart City Connections in Service (m), Split by Wireless Technology, 2018 & 2022
      • i.Device Roaming
    • 1.4.2 The Emergence of 5G
    • 1.4.3 5G Smart Cities: Strategic Recommendations
    • 1.4.4 Converged Networks
      • Case Study: Ruckus Networks

2. Market Segment Analysis

  • 2.1 Introduction
  • 2.2 Smart Energy
    • 2.2.1 Smart Grid Business Model Innovation
      • Case Study: Brooklyn Microgrid
      • i. Combatting Lost Revenue
    • 2.2.2 Smart Street Lighting
      • Case Study: Dimonoff
    • 2.2.3 Smart Street Lighting City Innovation
      • Case Study: City of Pittsburgh
      • Case Study: Huawei PoleStar 2.0
    • 2.2.4 Smart Street Lighting Challenges
      • i. Energy Savings
      • ii. Interoperability
      • iii. Adjacent Services
    • 2.2.5 Smart Energy Market Investment Trends & Regulatory Environment
      • i. USA
      • ii. EU
      • iii. Far East & China
  • 2.3 Smart Transport
    • 2.3.1 City Strategy
      • Case Study: Didi Chuxing Smart Transportation Brain
      • Case Study: Trafi
    • 2.3.2 Urban Mobility Development Strategies
      • i. Ridesharing
      • ii.Ticketing
        • Figure 2.1: Global Mobile & Online Transport Ticketing Users (m), Transaction Volume (m) 2015-2018
      • iii. Bikesharing
      • iv. Autonomous Vehicles
      • v. Electric Vehicles
        • Case Study: EnergyHub
      • vi. Smart Traffic Management
        • Case Study: Surtrac
      • vii. Smart Parking
        • Case Study: Passport
  • 2.4 Smart Health
    • 2.4.1 Platform Strategies
      • Case Study: Ningbo Cloud Hospital
      • Case Study: Array of Things, Chicago
    • 2.4.2 City Strategy
      • i. Key Considerations
        • Case Study: DigitalHealth.London

3. Smart City Platform Vendor Analysis & Leaderboard

  • 3.1 Introduction
  • 3.2 Juniper Leaderboard
    • Table 3.1: Vendor Capability Assessment Criteria
    • 3.2.1 Leaderboard Scoring Results
      • Table 3.2: Juniper Leaderboard: Smart City Platform Vendors
      • Figure 3.3: Juniper Leaderboard: Smart City Platform Vendors
    • 3.2.2 Vendor Groupings
      • i. Established Leaders
      • ii. Leading Challengers
      • iii. Disruptors & Emulators
    • 3.2.3 Limitations & Interpretations
  • 3.3 Smart City Movers & Shakers
  • 3.4 Stakeholder Analysis
    • 3.4.1 AT&T
      • i. Corporate Profile
        • Table 3.4: AT&T Financial Snapshot ($m) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.4.2 Bosch
      • i. Corporate
        • Table 3.5: Bosh Financial Snapshot (€m/$m) 2015-
      • iii.Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.4.3 Cisco
      • i. Corporate Profile
        • Table 3.6: Cisco Financial Snapshot ($m) FY 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.4.4 Ericsson
      • i. Corporate Profile
        • Table 3.7: Ericsson Financial Snapshot (SEK m) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv.High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.4.5 GE
      • i. Corporate Profile
        • Table 3.8: GE Financial Snapshot ($bn) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Partnerships
      • iv. High Level View of IoT Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.4.6 Hitachi
      • i.Corporate Profile
        • Hitachi Financial Snapshot (¥billion) 2015-
      • ii.Geographic Spread
      • iii.Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.4.7 Huawei
      • i. Corporate
        • Table 3.9: Huawei Financial Performance Snapshot ($m) 2015-2017
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
        • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.4.8 IBM
      • i. Corporate Profile
        • Table 3.10: IBM Financial Snapshot ($m) 2015-2017
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.4.9 Intel
      • i. Corporate Profile
        • Table 3.11: Intel Financial Snapshot ($m) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.4.10 Itron
      • i. Corporate Profile
        • Table 3.12: Itron Financial Snapshot ($m) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.4.11 Nokia
      • i. Corporate Profile
        • Table 3.13: Nokia Financial Snapshot (€m) 2016-
      • v.Geographic Spread
      • iv.Key Clients & Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.4.12 Oracle
      • i. Corporate Profile
        • Table 3.14: Oracle Financial Snapshot ($m) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.4.13 Schneider Electric
      • i. Corporate Profile
        • Table 3.15: Schnieder Electric Financial Snapshot (€m) 2016-
      • ii. Geographic Spread
      • vi.Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.4.14 Siemens
      • i. Corporate Profile
        • Table 3.15: Siemens Financial Snapshot (€m) 2016-
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. Products & Services
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.4.15 Verizon
      • i. Corporate Profile
        • Table 3.17: Verizon Financial Snapshot ($m) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities

Deep Dive Data & Forecasting

1. Smart Cities: Evolving Market Dynamics

  • 1.1 Introduction
    • 1.1.1 The Journey to Becoming a Smart City: Key Strategic Considerations for Cities
    • 1.1.2. Talent Acquisition
    • 1.1.3 Governance
    • 1.1.4 Innovation

2. Smart City Forecasts: Baseline Figures & Summary

  • 2.1 Introduction
  • 2.1 Population
    • Figure & Table 2.1: City Population over 500,000 individuals, Split by 8 Key Regions 2018-2023
  • 2.2 Wholesale Electricity Prices
    • Figure & Table 2.2: Wholesale Electricity Prices ($/MWh) Split by 8 Key Regions 2018-2023
  • 2.3 Emissions Factors
    • 2.3.1 Electricity Generation
      • Table 2.3: CO 2 e Emissions Split by Electricity Generation Fuel
    • 2.3.2 Internal Combustion Engine Vehicles
      • Table 2.4: Emissions Factor for City Vehicles, Split by 8 Key Regions 2018-2023 (t CO 2 e/km)
  • 2.4 Economic Value of CO2e
    • Table 2.5: CO 2 e Emissions Value ($/t) 2017-2022
  • 2.5 Forecast Summary
  • 2.6 Cost Savings Summary
    • Figure & Table 2.6: Combined Energy & CO 2 e Cost Savings ($m) Split by Smart City Market Vertical 2018-2023
  • 2.7 Software Spend Summary
    • Figure & Table 2.7: Combined Annual Smart City Software Spend ($m) Split by Smart City Market Vertical 2018-2023

3. Smart Grid Forecasts

  • 3.1 Introduction
  • 3.2 Methodology & Assumptions
    • Figure 3.1: Smart Grid Forecast Methodology
  • 3.3 City Energy Consumption
    • Figure & Table 3.2: Annual City Energy Electricity Consumption (TWh) Split by 8 Key Regions 2018-2023
  • 3.4 Smart Grid Energy Savings
    • Figure & Table 3.3: Annual Smart Grid Net Energy Savings (TWh) 2018-2023 .. 19 3.5 Smart Grid Emissions Savings
    • Figure & Table 3.4: Smart Grid CO 2 e Emissions Savings (MMT) Split by 8 Key Regions 2018-2023
  • 3.6 Smart Grid Energy & Emissions Cost Savings
    • Figure & Table 3.5: Total Annual Smart Grid Energy & CO2e Cost Savings ($m) 2018-2023
  • 3.7 Smart Grid Software Spend
    • Figure & Table 3.6: Total Annual Smart Grid Software Spend ($m) Split by 8 Key Regions 2018-2023

4. Smart Traffic Management & Parking Forecasts

  • 4.1 Introduction
  • 4.2 Methodology & Assumptions
    • Figure 4.1: Smart Traffic Management & Parking Methodology
  • 4.3 Smart Traffic Management Emissions Savings
    • Figure & Table 4.2: Annual Smart Traffic Management CO 2 e Savings (MMT) Split by 8 Key Regions 2018-2023
  • 4.4 Smart Traffic Management Cost Savings
    • Figure & Table 4.3: Annual Smart City Traffic Management Emissions Cost Savings ($m), Split by 8 Key Regions 2018-2023
  • 4.5 Smart Traffic Management Software Spend
    • Figure & Table 4.4: Total Annual Smart Traffic Management Software Spend ($m) Split by 8 Key Regions 2018-2023
  • 4.6 Smart Traffic Management Hardware Spend
    • Figure & Table 4.5: Total Annual Smart Traffic Management Hardware Unit Spend ($m) Split by 8 Key Regions 2018-2023
  • 4.7 Smart Parking Emissions Savings
    • Figure & Table 4.6: Annual Smart Parking CO 2 e Savings (MMT) Split by 8 Key Regions 2018-2023
  • 4.8 Smart Parking Cost Savings
    • Figure & Table 4.7: Annual Smart City Smart Parking Emissions Cost Savings ($m), Split by 8 Key Regions 2018-2023
  • 4.9 Smart Parking Software Spend
    • Figure & Table 4.8: Annual Software Spend on Smart Parking Systems ($m), Split by 8 Key Regions 2018-2023
  • 4.10 Smart Parking Hardware Spend
    • Figure & Table 4.9: Annual Hardware Unit Spend on Smart Parking Systems ($m), Split by 8 Key Regions 2018-2023
  • 4.11 Smart Traffic & Smart Parking Summary
    • Figure & Table 4.10: Combined Annual Smart City Traffic Management & Smart Parking CO 2 e Emissions Cost Savings ($m), Split by 8 Key Regions 2018-2023
    • Figure & Table 4.11: Combined Annual Smart City Traffic Management & Smart Parking Software Spend ($m), Split by 8 Key Regions 2018-2023
    • Figure & Table 4.12: Combined Annual Smart City Traffic Management & Smart Parking Hardware Unit Spend ($m), Split by 8 Key Regions 2018-2023

5. Smart Street Lighting Forecasts

  • 5.1 Introduction
  • 5.2 Methodology & Assumptions
    • Figure 5.1: Smart Street Lighting Methodology
  • 5.3 Smart Street Lighting Energy Savings
    • Figure & Table 5.2: Annual Smart Street Lighting Energy Savings (TWh), Split by 8 Key Regions 2018-2023
  • 5.4 Smart Street Lighting Emissions Savings
    • Figure & Table 5.3: Annual Smart Street Lighting CO 2 e Savings (MMT), Split by 8 Key Regions 2018-2023
  • 5.5 Smart Street Lighting Energy & Emissions Cost Savings
    • Figure & Table 5.4: Annual Smart Street Lighting Energy & Emissions Cost Savings ($m) Split by 8 Key Regions 2018-2023
  • 5.6 Smart Street Lighting Software Spend
    • Figure & Table 5.5: Annual Smart Street Lighting Software Spend ($m), Split by 8 Key Regions 2018-2023
  • 5.7 Smart Street Lighting Hardware Spend
    • Figure & Table 5.6: Annual Smart Street Lighting Hardware Unit Spend ($m), Split by 8 Key Regions 2018-2023
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