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市場調查報告書

人機介面及生物識別設備:新興生態系統、機會與預測

Mobile Biometrics: Consumer Markets, Opportunities & Forecasts 2016-2021

出版商 Juniper Research 商品編碼 320770
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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人機介面及生物識別設備:新興生態系統、機會與預測 Mobile Biometrics: Consumer Markets, Opportunities & Forecasts 2016-2021
出版日期: 2016年12月01日 內容資訊: 英文
簡介

本報告提供行動裝置中支持手勢型、非接觸及生物識別功能的各種技術的機會調查、醫療及汽車產業的行動以外的技術用途調查、語音指令、指紋認證及臉部辨識、追蹤等領域的主要趨勢、主要企業簡介等彙整資料,為您概述為以下內容。

目錄

摘要整理

第1章 市場概要

  • 簡介
  • 生物識別技術的終端用戶的優點
  • 感應技術
  • 生物識別領域的地區活動
  • 行動的生物辨識所扮演的角色
  • 行動生物辨識的主要趨勢

第2章 人機介面技術趨勢

  • 簡介
  • 波動&行動
  • 虹膜
  • 語音
  • 指紋
  • 生物識別特定
  • 未來的焦點

第3章 供應商創新、活動

  • 簡介
  • 終端的創新
  • 供應商的關係
  • 地區存在感
  • M&A活動
    • Google
    • Apple
    • Samsung
    • Lenovo
    • 其他主要收購
    • 未來的機會

第4章 市場預測

  • 簡介&預測手法
  • 整體消費者收益
  • 人機介面遊戲預測
  • 多媒體
  • 生活方式
  • 認證

第5章 競爭情形

  • 業者情勢
  • 供應商分析
  • 供應商的定位矩陣結果
  • 供應商簡介
    • Cognitec
    • Emotient
    • Nuance Communications
    • Umoove
    • ValidSoft
    • VoiceTrust
    • Crunchfish
    • Descartes Biometrics
    • Elliptic Labs

本網頁內容可能與最新版本有所差異。詳細情況請與我們聯繫。

目錄

Overview

Juniper Research's new Mobile Biometrics research provides analysis, market sizing and opportunity assessment for both mainstream and emerging biometric technologies.

The research looks at adoption rates across a variety of sectors and geographical markets, identifying key trends, developments and use-cases. The key technologies covered are:

  • Fingerprint biometrics
  • Iris scanning
  • Facial recognition
  • Voice recognition

This research suite includes:

  • Market Trends & Opportunities (PDF)
  • 5 Year Market Sizing & Forecast Spreadsheet (Excel).

Key Features

  • Trend Assessment: Strategic assessment of the key trends and market drivers across the four key biometric markets.
  • Technology Impact Analysis: In-depth assessment of the state of Human Interface technology deployments, showcasing and analysing key deployments.
  • Interviews: Invaluable insights from leading players including:
    • EyeVerify
    • Neurotechnology
    • Acuant.
  • Benchmark industry forecasts: Provided for the size and growth of the consumer biometrics market, including adoption rates, transaction volumes, and transaction values.

Key Questions

  • 1.Which countries will see the biggest uptake in biometric methods, and how do these differ?
  • 2.What devices are best suited to emerging biometric technologies?
  • 3.How will the increasing range of biometric technologies work together to provide increased security?
  • 4.What are the best practices for successful and secure deployment of biometrics?
  • 5.What is the current state of biometric technologies, and how will they evolve in future?

Companies Referenced

Acuant, Amazon, Ant Financial, Apple, Barclays, BioEnable, Biyo, Cheetah Mobile, Cross Match Verifier, CrucialTec, Descartes Biometrics, EyeVerify, Fitbit, Google, Hitachi, Image Vision, ImageWare Systems, Intel, IRIScan, M2SYS, Mastercard, Microsoft, NEC, Neurotechnology, NTT DoCoMo, Nuance, Nymi, Precise Biometrics, Qualcomm, Razer, Samsung, WeChat, Wise Orchard, Xiaomi, Xolo, Yulong, ZKTeco.

Data & Interactive Forecast

Juniper's latest Mobile Biometrics forecast suite includes:

  • Market data splits for 8 key regions, and 11 countries including:
    • Canada
    • China
    • Denmark
    • Germany
    • India
    • Japan
    • Norway
    • Portugal
    • Spain
    • Sweden
    • UK
  • Market hardware and software data splits for 4 biometric technologies:
    • Fingerprint sensors
    • Facial Recognition
    • Iris Recognition
    • Voice Recognition
  • Data splits by device type:
    • Smartphones
    • Tablets
    • PCs
    • Phone banking
  • Data splits by transaction types:
    • Remote payments
    • Contactless payments
    • Ticketing transactions
  • Access to the full set of forecast data of 103 tables and over 11,800 data points.
  • All verticals include forecasts for consumer adoption rates and installed base.

Juniper Research's highly granular Interactive Excels (IFXLs) 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

1. Biometrics Market: Key Takeaways

  • 1.1. Introduction
  • 1.2. Research Scope
    • 1.2.1. Definition
    • 1.2.2. Research Structure
  • 1.3. Key Findings
  • 1.4. Strategic Recommendations & Best Practice Guide

2. Biometrics Market Analysis & Opportunities

  • 2.1. Current Market for Biometrics
    • 2.1.1. Market Status
      • Figure 2.1:Juniper Phased Evolution Model for Biometrics
    • 2.1.2. Circulation-based Biometrics
      • Figure 2.2: Biyo Vein-scanning POS Terminal
      • i. Case Study: Hitachi Camera-based Finger Vein Authentication
      • ii. Case Study: lymi Band
    • 2.1.3. Eye-based Biometrics
      • i. Case Study: CrucialTec Filter Changing
      • ii. Case Study: Eyeprint ID by EyeVerify
    • 2.1.4. Facial Recognition
      • Figure 2.3: Razer Stargazer Webcam Marketing Image
      • i. Case Study: Windows Hello
    • 2.1.5. Fingerprint Scanning
      • Figure 2.4: Google Trends Comparison of 'Touch ID' & Other Biometric Measures as Search Terms
      • i. Case Study: Qualcomm Sense ID
        • Figure 2.5: Xiaomi Mi 5s & Mi 5s Plus
    • 2.1.6. Voiceprint Authentication
      • i. Case Study: Nuance VocalPassword
    • 2.1.7. Other Authentication Methods
  • 2.2. Key Biometrics Stakeholders & Value Chain
    • 2.2.1. Player Analysis & Business Models
      • Figure 2.6: Biometrics Ecosystem
  • 2.3. Biometric Market Dynamics
    • Figure 2.7: Juniper Market Dynamics for Biometrics
    • 2.3.1. Market Drivers
      • Figure 2.8: Proportion of Smartphones Released that have a Fingerprint Sensor Integrated (%)
    • 2.3.2. Market Barriers
    • 2.3.3. Market Trends
      • Figure 2.9: Biometric App Download Distribution

3. Summary Forecasts & Forecast Methodology

  • 3.1. Introduction
  • 3.2. Forecast Methodology
    • 3.2.1. Hardware Forecasts
      • i. Wearable Biometrics
    • 3.2.2. Software & Service Forecasts
      • i. Telephone Banking Voice Authentication
    • 3.2.3. Transaction Forecasts
      • Figure 3.1: Biometric Smart Mobile Devices Hardware Forecast Methodology
      • Figure 3.2: Biometric Smart Mobile Devices Software &Transactions Forecast Methodology
  • 3.3. Summary Forecasts
    • 3.3.1. Hardware Forecasts
      • Figure & Table 3.3: Biometrics Hardware Installed Base (m) by Category, 2016-2021
    • 3.3.2. App Forecasts
      • Figure & Table 3.4: Biometric-enabled Apps, Installed Base by Category (m), 2016-2021
    • 3.3.3. Transaction Forecasts
      • i. Transaction Volume
        • Figure & Table 3.5: Biometrically-Authenticated Transactions (m) per annum, 2016-2021
      • ii. Transaction Value
        • Figure & Table 3.6: Biometric Transaction Value per annum ($m) by Catagory

4. Biometric Hardware Forecasts

  • 4.1. Installed Base Forecasts
    • 4.1.1. Fingerprint Scanners
      • Figure & Table 4.1: Number of Smart Mobile Devices writh Fingerprint Scanners, Installed Base per annum (m), 2016-2021
    • 4.1.2. Iris Scanners
      • Figure & Table 4.2: Number of Smartphones writh Iris Scanners, Installed Base per annum (m), 2016-2021
    • 4.1.3. Integrated PC Facial Recognition Cameras
      • Figure & Table 4.3: Number of PCs with Integrated Facial Recognition Cameras, Installed Base per annum (m), 2016-2021
    • 4.1.4. Biometric Authentication Wearables
      • Figure & Table 4.4: Number of Biometric Authentication Wearables, Installed Base per annum (m), 2016-2021

5. Biometric Software & Transaction Forecasts

  • 5.1. Software Forecasts
    • 5.1.1. App Forecasts
      • i. Apps Using Pictorial ID Biometrics
        • Figure & Table 5.1: Pictorial ID Biometric Software Apps, Installed Base per annum (m), 2016-2021
      • ii. Apps Using Fingerprint Biometrics
        • Figure & Table 5.2: Number of Apps that Use Fingerprint Biometrics, Installed Base per annum (m), 2016-2021
      • iii. Apps Using Iris Biometrics
        • Figure & Table 5.3: Number of Apps that Use Iris Biometrics, Installed Base per annum (m), 2016-2021
      • iv. Apps Using Voice Biometrics
        • Figure & Table 5.4: Number of Apps that Use Iris Biometrics, Installed Base per annum (m), 2016-2021
      • v. Voiceprint Phone Banking Software Users
        • Figure & Table 5.5: Number of Banked Individuals using Biometric-Verified Phone Banking per annum (m)
  • 5.2. Trcansaction Forecasts
    • 5.2.1. Transaction Volume Forecasts
      • i. Biometric Payment Transactions
        • Figure & Table 5.6: Number of Smartphone Payments Per Annum that are Biometrically Verified (m), Split by 8 Key Regions 2016-2021
      • ii. Biometric Ticketing Transactions
        • Figure & Table 5.7: Number of Biometrically-Authenticated Tickets per annum (m ), 2016-2021
    • 5.2.2. Transaction Value Forecasts
      • i. Biometric Payment Transaction Value
        • Figure & Table 5.8: Value of Biometrically-Verified Smartphone Payment Transactions per annum (m), 2016-2021
      • ii. Biometric Ticketing Transaction Revenue
        • Figure & Table 5.9: Value of Biometrically-Verified Smartphone Ticketing Transactions per annum ($m) 2016-2021
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