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農業におけるM2M/IoTアプリケーション

M2M/IoT Applications in the Agricultural Industry

発行 BERG Insight 商品コード 586078
出版日 ページ情報 英文 160 Pages
納期: 即日から翌営業日
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農業におけるM2M/IoTアプリケーション M2M/IoT Applications in the Agricultural Industry
出版日: 2017年11月30日 ページ情報: 英文 160 Pages
概要

農業生産用途の設置済みワイヤレスデバイス数は、2016年末の1,700万から2021年までに2,740万台へと10%のCAGR (年間複合成長率) で成長すると予測されています。セルラー接続数は2016年末の80万から30.2%のCAGRで増加し、2021年には310万へ達すると予測されています。

当レポートでは、農業向けM2MおよびIoTアプリケーション市場について調査し、市場動向と予測、新興のスマート農業市場における技術とソリューション、OEM製品と戦略、およびアフターマーケットソリューションプロバイダーなどについてまとめています。

エグゼクティブサマリー

第1章 農業部門

  • 農業生産
  • 農産物
  • 農産物の需要
  • 農業活動
  • 農業装置

第2章 スマート農業技術・ソリューション

  • スマート農業インフラ
  • 機械管理
  • 精密農業
  • リモートセンシング
  • リモートモニタリング・コントロール
  • 精密畜産農業
  • データ管理・予測分析
  • ビジネスモデル・戦略

第3章 市場予測・動向

  • 市場分析
  • 市場成長促進因子・抑制因子
  • バリューチェーン分析
  • 市場動向

第4章 OEM製品・戦略

  • AGCO
  • CLAAS Group
  • CNH Industrial
  • Deere & Company
  • Krone
  • クボタ
  • Mahindra & Mahindra
  • SDF

第5章 アフターマーケットソリューションプロバイダー

  • 精密農業
  • リモートモニタリング・コントロール
  • 乳牛群管理
  • データ管理

用語集

目次

How will the market for agricultural M2M and IoT applications evolve in 2018 and beyond? Berg Insight covers the latest trends and developments in the emerging smart farming market. Berg Insight forecasts that the number of installed wireless devices for applications in agricultural production is forecasted to grow at a CAGR of 10.0 percent from 17.0 million connections at the end of 2016 to 27.4 million connected devices by 2021. Cellular connections amounted to 0.8 million at the end of 2016 and is expected to grow at a CAGR of 30.2 percent to reach 3.1 million in 2021. Get up to date with the latest information about vendors, products and markets.

Table of Contents

Table of Contents

List of Figures

Executive summary

1 The agricultural sector

  • 1.1 Agricultural production
    • 1.1.1 Agricultural land use
    • 1.1.2 Irrigated area and irrigation methods
    • 1.1.3 Employment in agriculture
    • 1.1.4 Forestry
    • 1.1.5 The food and agribusiness value chain
  • 1.2 Agricultural commodities
  • 1.3 Demand for agricultural commodities
    • 1.3.1 Population growth and economic development
    • 1.3.2 Consumption of agricultural products
  • 1.4 Agricultural operations
    • 1.4.1 Farm income and capital expenditures
    • 1.4.2 Mixed crop-livestock farming
    • 1.4.3 Crop farming
    • 1.4.4 Livestock farming
  • 1.5 Agricultural equipment

2 Smart farming technologies and solutions

  • 2.1 Smart farming infrastructure
    • 2.1.1 Farm equipment segment
    • 2.1.2 Field segment
    • 2.1.3 Livestock segment
    • 2.1.4 GNSS segment
    • 2.1.5 Network segment
    • 2.1.6 Backoffice segment
  • 2.2 Machinery management
    • 2.2.1 Vehicle diagnostics and maintenance planning
  • 2.3 Precision agriculture
    • 2.3.1 Guidance and automated steering
    • 2.3.2 Yield monitoring and mapping
    • 2.3.3 Precision seeding
    • 2.3.4 Precision fertilising
    • 2.3.5 Precision spraying
  • 2.4 Remote sensing
    • 2.4.1 Satellite and drone imagery
  • 2.5 Remote monitoring and control
    • 2.5.1 Weather monitoring
    • 2.5.2 Pest monitoring and control
    • 2.5.3 Irrigation management
  • 2.6 Precision livestock farming
    • 2.6.1 Pig management
    • 2.6.2 Poultry management
    • 2.6.3 Beef cattle management
    • 2.6.4 Dairy herd management.
  • 2.7 Data management and predictive analytics
  • 2.8 Business models and strategies

3 Market forecasts and trends

  • 3.1 Market analysis
    • 3.1.1 Installed base and unit shipments
    • 3.1.2 Regional markets
    • 3.1.3 Wireless technologies
    • 3.1.4 Precision agriculture
    • 3.1.5 Dairy herd management.
  • 3.2 Market drivers and barriers
    • 3.2.1 Macroeconomic environment
    • 3.2.2 Regulatory environment
    • 3.2.3 Competitive environment
    • 3.2.4 Technology environment
  • 3.3 Value chain analysis
    • 3.3.1 Precision farming industry players
    • 3.3.2 Farm equipment players
    • 3.3.3 Input industry players
    • 3.3.4 Dairy equipment industry players
    • 3.3.5 Telecom industry players
  • 3.4 Market trends
    • 3.4.1 The emerging digital ecosystem requires a shift towards collaboration
    • 3.4.2 Larger herds drive the adoption of precision livestock farming technologies
    • 3.4.3 IoT start-ups are attractive to investors
    • 3.4.4 Dealerships remain as gateways to customers
    • 3.4.5 Freemium strategies will intensify competition between software vendors

4 OEM products and strategies

  • 4.1 AGCO
  • 4.2 CLAAS Group
  • 4.3 CNH Industrial
  • 4.4 Deere & Company
  • 4.5 Krone
  • 4.6 Kubota
  • 4.7 Mahindra & Mahindra
  • 4.8 SDF

5 Aftermarket solution providers

  • 5.1 Precision farming
    • 5.1.1 Ag Leader Technology
    • 5.1.2 Agjunction
    • 5.1.3 DICKEY-john
    • 5.1.4 The Climate Corporation (Monsanto)
    • 5.1.5 Farmers Edge
    • 5.1.6 Hexagon Agriculture
    • 5.1.7 Raven Industries
    • 5.1.8 Topcon Positioning Systems
    • 5.1.9 Trimble
    • 5.1.10 Yara
  • 5.2 Remote monitoring and control
    • 5.2.1 Arable Labs
    • 5.2.2 Aquaspy
    • 5.2.3 Campbell Scientific
    • 5.2.4 CropX
    • 5.2.5 Davis Instruments
    • 5.2.6 Hortau
    • 5.2.7 Jain Irrigation Systems
    • 5.2.8 Libelium
    • 5.2.9 Lindsay Corporation
    • 5.2.10 Netafim
    • 5.2.11 Net Irrigate
    • 5.2.12 Pessl Instruments
    • 5.2.13 Semios
    • 5.2.14 Spensa Technologies
    • 5.2.15 Valmont Industries
  • 5.3 Dairy herd management
    • 5.3.1 Afimilk
    • 5.3.2 DeLaval
    • 5.3.3 Farmnote
    • 5.3.4 Fullwood
    • 5.3.5 GEA Group
    • 5.3.6 Smartbow
    • 5.3.7 Lely
    • 5.3.8 Moocall
    • 5.3.9 Nedap
    • 5.3.10 SCR (The Allflex Group)
  • 5.4 Data management
    • 5.4.1 365FarmNet
    • 5.4.2 Agrian
    • 5.4.3 Conservis
    • 5.4.4 DKE-Data
    • 5.4.5 DowDuPont Agriculture
    • 5.4.6 Farmers Business Network
    • 5.4.7 FarmLogs
    • 5.4.8 Farmobile
    • 5.4.9 Isagri
    • 5.4.10 SST Software

Glossary

List of Figures

  • Figure 1.1: Area and yield trend for wheat, rice, soybean and corn (World 2016)
  • Figure 1.2: Moving 10-year average growth in crop yield (World 2016)
  • Figure 1.3: Land use and agricultural land (World 2014)
  • Figure 1.4: Top ten countries by planted area (World 2014)
  • Figure 1.5: Employment in agriculture (2016)
  • Figure 1.6: The agribusiness value chain
  • Figure 1.7: Major crop production statistics (World 2016)
  • Figure 1.8: Leading producers of major crops (World 2016)
  • Figure 1.9: Meat and milk production statistics (World 2016)
  • Figure 1.10: Live animal stock (World 2014)
  • Figure 1.11: Agricultural commodity prices
  • Figure 1.12: Population in billion (World)
  • Figure 1.13: Use of cereal grains (World 2016)
  • Figure 1.14: Agricultural tractor shipments (World 2016)
  • Figure 2.1: Smart farming infrastructure overview
  • Figure 2.2: Shipments and installed base of GNSS devices for ag (World 2016-2021)
  • Figure 2.3: Example of smart farming backoffice segment
  • Figure 2.4: Example of monitored variables in precision livestock farming
  • Figure 2.5: Wearable devices for cattle monitoring
  • Figure 3.1: Unit shipments and installed base by segment (World 2016-2021)
  • Figure 3.2: Unit shipments and installed base by region (World 2016-2021)
  • Figure 3.3: Unit shipments and installed base by technology (World 2016-2021)
  • Figure 3.4: Precision agriculture market value (World 2016-2021)
  • Figure 3.5: Activity monitoring solutions market value (World 2016-2021)
  • Figure 3.6: Financial data for precision technology companies.
  • Figure 3.7: Mergers and acquisitions among companies active in smart farming
  • Figure 3.8: Financial data for companies and groups active in precision agriculture
  • Figure 3.9: Revenues of top providers of crop protection chemicals and seeds
  • Figure 3.10: Financial data for top providers of dairy equipment
  • Figure 3.11: Mobile operators by M2M subscriber base (World Q2-2017)
  • Figure 5.1: Topcon's AM-53 telematics module
  • Figure 5.2: The CropX sensor
  • Figure 5.3: Sensors supported by Davis Instruments' EviroMonitor system
  • Figure 5.4: Libelium's IoT value chain
  • Figure 5.5: The Z-Trap 1 insect trapping device
  • Figure 5.6: Stakeholders connected to DKE-Data's Agrirouter
  • Figure 5.7: Overview of Granular Farm Management System
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