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市場調查報告書

IoT的機器學習

Machine Learning in IoT

出版商 ABI Research 商品編碼 363950
出版日期 內容資訊 英文 25 Pages, 7 Tables
商品交期: 最快1-2個工作天內
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IoT的機器學習 Machine Learning in IoT
出版日期: 2016年07月20日 內容資訊: 英文 25 Pages, 7 Tables
簡介

本報告提供IoT系統和應用所使用的機器學習 (ML) 調查分析,主要的產業領域和應用概要,IoT分析的年度收益預測,主要供應商簡介等系統性資訊。

第1章 IoT的機器學習 (ML)

  • ML定義
  • ML演算法的分類
  • IoT的ML的利用:應用,趨勢,見解
  • 優點與課題

第2章 各產業領域市場引進與預測

  • 主要的各產業領域市場與應用
  • 預測

第3章 業者情勢

  • Google
  • PTC (ColdLight)
  • Amazon
  • Infobright
  • Mtell
  • Predikto
  • Predixion Software
  • IBM
  • Microsoft
  • Cisco
  • Sight Machine

刊載企業

  • 3 Group
  • 946
  • Accenture Ltd
  • Amazon
  • Analysis Group
  • Apache Corporation
  • Asia Technologies Ltd
  • Ayasdi
  • Azure
  • Bloomberg
  • Chrysler LLC
  • CSX Corporation
  • Even Technologies
  • Go
  • Google
  • IBM Corp
  • Intel Corporation
  • International Technologies
  • Jabil Circuit
  • Liebherr
  • Microsoft Corporation
  • ML
  • Mtell
  • Netflix
  • Open Technologies
  • Predikto
  • Processing Technologies
  • PTC
  • Qualcomm Inc
  • Reply
  • Revolution Analytics
  • Sight Machine
  • Source Technologies
  • South Technologies
  • Stream Technologies
  • ThingWorx
  • Two Technologies Inc
  • United Technologies Corporation
  • USA Technologies
  • Venture
  • YouTube
目錄
Product Code: AN-2016

With the number of IoT-connected devices estimated to grow to tens of billions by the end of the decade, the volume of the data generated by these devices is poised to reach unprecedented proportions. According to ABI Research's research analysis Edge Analytics in IoT (AN-1914), the total volume of data produced annually by IoT-connected devices is estimated to reach almost 130 million yottabytes (YB) in 2020, where 1 YB equals 1024 bytes or 1018 megabytes (MB). With such huge numbers in play, managing the large volume, variety, and velocity of big data becomes one of the major challenges the IoT industry has to face today.

Table of Contents

1. MACHINE LEARNING IN IOT1.1. Defining Machine Learning

  • 1.2. Categorization of Machine Learning Algorithms
  • 1.3. Use of Machine Learning in IoT: Applications, Trends, Observations
  • 1.4. Benefits and Challenges

2. VERTICAL MARKET ADOPTION AND FORECASTS2.1. Key Vertical Markets and Applications

  • 2.2. Forecasts

3. VENDORS LANDSCAPE3.1. Google

  • 3.2. PTC (ColdLight)
  • 3.3. Amazon
  • 3.4. Infobright
  • 3.5. Mtell
  • 3.6. Predikto
  • 3.7. Predixion Software
  • 3.8. IBM
  • 3.9. Microsoft
  • 3.10. Cisco
  • 3.11. Sight Machine

Companies Mentioned

  • 3 Group
  • 946
  • Accenture Ltd
  • Amazon
  • Analysis Group
  • Apache Corporation
  • Asia Technologies Ltd
  • Ayasdi
  • Azure
  • Bloomberg
  • Chrysler LLC
  • CSX Corporation
  • Even Technologies
  • Go
  • Google
  • IBM Corp
  • Intel Corporation
  • International Technologies
  • Jabil Circuit
  • Liebherr
  • Microsoft Corporation
  • ML
  • Mtell
  • Netflix
  • Open Technologies
  • Predikto
  • Processing Technologies
  • PTC
  • Qualcomm Inc
  • Reply
  • Revolution Analytics
  • Sight Machine
  • Source Technologies
  • South Technologies
  • Stream Technologies
  • ThingWorx
  • Two Technologies Inc
  • United Technologies Corporation
  • USA Technologies
  • Venture
  • YouTube
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