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農業におけるIoT市場の展望と予測:2020-2025年

IoT in Agriculture Market Outlook and Forecasts 2020 - 2025

発行 Mind Commerce 商品コード 936584
出版日 ページ情報 英文 182 Pages
納期: 即日から翌営業日
価格
本日の銀行送金レート: 1USD=107.17円で換算しております。
農業におけるIoT市場の展望と予測:2020-2025年 IoT in Agriculture Market Outlook and Forecasts 2020 - 2025
出版日: 2020年05月18日 ページ情報: 英文 182 Pages
概要

AIおよびIoTにより、従来型農業からデータ主導型農業への移行が加速しています。ドローンベースのアグリテックイメージングは、CAGR76.4%CAGRの成長が見込まれ、2025年までに8億5,000万米ドルに達すると予測されています。

当レポートでは、世界の農業におけるIoT市場について調査し、市場概要、各セグメントおよび地域別によるの市場分析と予測、市場発展への影響要因、競合環境、および主要企業などについて、体系的な情報を提供しています。

第1章 エグゼクティブサマリー

第2章 概要

  • 農産業
    • スマート農業 vs. と従来型農業
    • 農産業の技術革新
    • 農産業の見通し
  • スマート農業市場の展望
  • 農産業を形作るIoTAg (農業におけるIoT) 技術
  • IoT対応のスマート農業ソリューション
    • 精密農業
    • 屋内農業
    • 家畜モニタリング
    • 魚の養殖
  • スマート農業システムと機能

第3章 農業市場力学におけるIoT

  • IoTAg市場の成長要因
    • 高収量を生み出す技術の採用の拡大
    • 政府によるアグリテック導入のサポート
    • 精密農業の採用拡大
  • IoTAg市場の課題
    • コストの増加と限られた技術スキル
    • 技術統合

第4章 農業におけるIoTの機会分析

  • 農業におけるIoT市場
    • 自然災害管理と低減
    • 農業損失の削減におけるIoTの役割
    • IoTと農業経営の統合
    • 農業におけるIoTの監視/制御におけるスマートフォンの役割
    • 農業ビジネスモデルにおける新たなIoT
  • 大規模農業経営向けIoT
  • 中小規模農業向けのIoT

第5章 農業におけるIoT市場の分析と予測

  • 世界のIoT農業収益:用途別
  • 世界のIoT農業収益:セグメント別
    • 世界のインテリジェント農業機器市場
    • 農業における世界のスマートセンサー市場
    • 農業におけるIoT市場:スマートセンサータイプ別
    • 世界の農業ドローン市場
    • 世界のスマートファームロボット市場
    • 世界の農業ソフトウェアソリューション市場
  • 農業ソリューションにおけるIoTの世界市場
    • 世界のIoT精密農業収益
    • 世界のIoT屋内農業収益
    • 世界のIoT畜産農業収益
    • 世界のIoT水産・養殖収益
  • 農業におけるIoT収益:地域別
    • 北米市場
    • の欧州市場
    • APAC市場
    • その他市場
  • IoT農業における世界のマネージドサービス
  • スマート農業における予測分析と人工知能

第6章 農業におけるIoTのベンダー分析

  • スマート農業ベンダーのエコシステム
  • 農業におけるIoT のベンダー戦略
  • 主なスマート農業ソリューションを
    • Accenture
    • AgEagle
    • Cattle Watch
    • Climate Corporation (Monsanto)
    • Decagon (METER Environment)
    • Deepfield Robotics (Bosch)
    • DroneDeploy
    • FarmersEdge
    • IBM
    • Euravka
    • FluxFarm Inc.
    • John Deere
    • Kaa Open Source IoT Platform
    • Libelium Comunicaciones Distribuidas S.L.
    • MTN
    • SWIM
    • SlantRange
    • Telit
    • ThingWorx (PTC)
    • TopCon
    • Intrinsyc Technologies Corp
    • Raven Industries
    • Semtech
    • Trackit

第7章 付録:IoTデータ分析

  • 農業データ分析市場におけるIoT
  • 農業データ分析におけるIoT
図表

Figures

  • Figure 1: Global Aggregate Revenue for IoT in Agriculture 2020-2025
  • Figure 2: Global IoT Agriculture Revenue by Application 2020-2025
  • Figure 3: Global IoT Agriculture Revenue by Segment 2020-2025
  • Figure 4: Global IoT Agriculture Solution Deployment 2020-2025
  • Figure 5: Global Intelligent Farm Equipment Unit Deployment vs. Revenue 2020-2025
  • Figure 6: Intelligent Farm Equipment Revenue by Region 2020-2025
  • Figure 7: Intelligent Farm Equipment Deployment by Region 2020-2025
  • Figure 8: Global Smart Sensors in Agriculture Unit Deployment vs. Revenue 2020-2025
  • Figure 9: Smart Sensors in Agriculture Revenue by Region 2020-2025
  • Figure 10: Regional Smart Sensors in Agriculture Deployment 2020-2025
  • Figure 11: Global Revenue by Smart Sensors Type 2020-2025
  • Figure 12: Global Smart Sensors in Agriculture Deployment by Type 2020-2025
  • Figure 13: Global Agricultural Drone Unit Deployment vs. Revenue 2020-2025
  • Figure 14: Agricultural Drone Revenue by Region 2020-2025
  • Figure 15: Agricultural Drone by Region 2020-2025
  • Figure 16: Global Agricultural Revenue by Drone Type 2020-2025
  • Figure 17: Global Agricultural Drone Deployment by Type 2020-2025
  • Figure 18: Global Smart Farm Robot Unit Deployment vs. Revenue 2020-2025
  • Figure 19: Smart Farm Robot Regional Revenue 2020-2025
  • Figure 20: Smart Farm Robot Deployment by Region 2020-2025
  • Figure 21: Global Agriculture Software Solutions Deployment vs. Revenue 2020-2025
  • Figure 22: IoT Software Solutions in Agriculture Revenue by Region 2020-2025
  • Figure 23: IoT Software Solutions in Agriculture Deployment by Region 2020-2025
  • Figure 24: Global IoT in Agriculture Revenue by Solution Type 2020-2025
  • Figure 25: IoT in Agriculture by Region 2020-2025
  • Figure 26: IoT in Agriculture Deployment by Region 2020-2025
  • Figure 27: North America IoT in Agriculture Deployment vs. Revenue 2020-2025
  • Figure 28: European IoT in Agriculture Deployment vs. Revenue 2020-2025
  • Figure 29: APAC IoT in Agriculture Deployment vs. Revenue 2020-2025
  • Figure 30: RoW IoT in Agriculture Deployment vs. Revenue 2020-2025
  • Figure 31: Big Data and Analytics Framework for Agriculture

Tables

  • Table 1: Global Aggregate Revenue for IoT in Agriculture
  • Table 2: Global IoT Agriculture Revenue by Application
  • Table 3: Global IoT Agriculture Revenue by Segment 2020-2025
  • Table 4: Global IoT Agriculture Solution Deployment 2020-2025
  • Table 5: Global Intelligent Farm Equipment Unit Deployment vs. Revenue 2020-2025
  • Table 6: Intelligent Farm Equipment Revenue by Region 2020-2025
  • Table 7: Intelligent Farm Equipment Deployment by Region 2020-2025
  • Table 8: Global Smart Sensors in Agriculture Unit Deployment vs. Revenue 2020-2025
  • Table 9: Global Smart Sensors in Agriculture Revenue 2020-2025
  • Table 10: Smart Sensors in Agriculture Regional Deployment 2020-2025
  • Table 11: Global Revenue by Smart Sensor Type 2019 - 2025
  • Table 12: Global Smart Sensors in Agriculture Deployment by Type 2020-2025
  • Table 13: Global Agricultural Drone Unit Deployment vs. Revenue 2020-2025
  • Table 14: Agricultural Drone Revenue by Region 2020-2025
  • Table 15: Agricultural Drone Deployment by Region 2020-2025
  • Table 16: Global Agricultural Revenue by Drone Type 2020-2025
  • Table 17: Global Agricultural Drone Deployment by Type 2020-2025
  • Table 18: Global Smart Farm Robot Unit Deployment vs. Revenue 2020-2025
  • Table 19: Smart Farm Robot Regional Revenue 2020-2025
  • Table 20: Smart Farm Robot Deployment by Region 2020-2025
  • Table 21: Global Agriculture Software Solutions Deployment vs. Revenue 2020-2025
  • Table 22: IoT Software Solutions in Agriculture Revenue by Region 2020-2025
  • Table 23: IoT Software Solutions in Agriculture Deployment by Region 2020-2025
  • Table 24: Global IoT in Agriculture Revenue by Solution Type 2020-2025
  • Table 25: Global Revenue for IoT Precision Agriculture by Solution 2020-2025
  • Table 26: Global Revenue for IoT Indoor Farming by Solution 2020-2025
  • Table 27: Global Revenue for IoT Livestock Farming by Solution 2020-2025
  • Table 28: Global Revenue for IoT Fisheries and Aquaculture by Solution 2020-2025
  • Table 29: IoT in Agriculture by Region 2020-2025
  • Table 30: IoT in Agriculture Deployment by Region 2020-2025
  • Table 31: North America IoT in Agriculture Deployment vs. Revenue 2020-2025
  • Table 32: North American IoT in Agriculture Revenue by Segment 2020-2025
  • Table 33: North American IoT in Agriculture Deployment by Segment 2020-2025
  • Table 34: European IoT in Agriculture Deployment vs. Revenue 2020-2025
  • Table 35: European IoT in Agriculture Revenue by Segment 2020-2025
  • Table 36: European IoT in Agriculture Deployment by Segment 2020-2025
  • Table 37: APAC IoT in Agriculture Deployment vs. Revenue 2020-2025
  • Table 38: APAC IoT in Agriculture Revenue by Segment 2020-2025
  • Table 39: APAC IoT in Agriculture Deployment by Segment 2020-2025
  • Table 40: RoW IoT in Agriculture Deployment vs. Revenue 2020-2025
  • Table 41: RoW IoT in Agriculture Revenue by Segment 2020-2025
  • Table 42: RoW IoT in Agriculture Deployment by Segment 2020-2025
  • Table 43: Global Managed IoT Services in Agriculture 2020-2025
  • Table 44: Services offered by Deepfield Robotics
  • Table 45: OnFarm Data Management Platform Economics
  • Table 46: IoT Driven Big Data Analytics in Agriculture Revenue 2020-2025
目次

Overview:

This research assesses the technologies, companies, and solutions for IoT in agriculture. The report evaluates the overall marketplace and provides forecasts for sensors (and other devices), services, solutions, and data analytics globally, and regionally for the period 2020 to 2025. Forecasts include precision agriculture, indoor farming, livestock, and fisheries. Forecasts cover IoT in Agriculture solutions globally and regionally including: Intelligent Farm Equipment, Smart Sensor Systems, Intelligent Drones, Smart Farm Robots, and Software.

Within the Smart Sensor area, the report forecasts the following: Sensors for Detecting Physical Properties, Sensors for Chemical Analysis and Applications, Sensors for General Monitoring, Sensors for Quality, Sensors for Autonomous Agriculture, and Others. All purchases of Mind Commerce reports include time with an expert analyst who will help you link key findings in the report to the business issues you're addressing. This needs to be used within three months of purchasing the report.

Increasingly, the agriculture business is becoming controlled by companies that are not conventional agriculture experts. Mind Commerce sees a shift from conventional agriculture to farm management systems through 2025. With this shift, software developers and predictive data analytics companies will take control of end-to-end agricultural operations. Agriculture has transformed in the last few decades from small to medium farming operations to highly industrialized, commercial farming that is concentrated among a few large corporations.

With this agricultural transformation, farming operations are increasingly a highly mechanized and computer-driven operation. This allows corporations to treat agriculture like manufacturing in the sense that measurements, data, and control is very important to manage costs, maximize yields, and boost profits. This shift in managing agricultural operations will bring various benefits to farming and livestock management, including enhanced crop quality and quantity, improved use of resources and farm equipment, real-time monitoring of farms, animals and machines, automated irrigation systems, fertilizer spraying and pest control.

The general term, AgriTech, represents the use of technology in agriculture, horticulture, and aquaculture for purposes of improving yield, efficiency, and profitability. The commercial agriculture industry is rapidly becoming one of the most IoT data-driven markets. With the emergence of M2M, IoT, and advanced data analytics technologies, data is becoming available that was previously uncollectible. The application of various AgriTech analytics tools and methodologies, such as predictive analytics will provide substantial enhancements to agriculture operations.

The Internet of Things (IoT) in Agriculture (IoTAg) represents a more specific use of technology wherein agricultural planning and operations becomes connected in ways previously impossible if it were not for advances in sensors, communications, data analytics and other areas. Virtually every aspect of agriculture that can be automated, digitally planned, and managed will benefit from IoT technologies and solutions.

Accordingly, Mind Commerce sees IoTAg fundamentally transforming the way agricultural operations and farms are managed, which will bring various benefits to farming, including enhanced crop quality and quantity; improved use of resources and farm equipment; real-time monitoring of farms, animals, and machines; and automated irrigation systems, fertilizer spraying, and pest control.

Monitoring will be the highest revenue earning application in IoTAg. Crop health monitoring will be the highest revenue generating application. Livestock monitoring and animal health monitoring to follow next. In fisheries, monitoring oxygen levels, pH and water quality will be the highest revenue generating applications. Through 2025, IoTAg-enabled monitoring will be a leading component of connected agriculture with market share of 69% and a value of $4.5 billion with a CAGR of 72.4%.

Connected agriculture is also realized through the increasing use of emerging observation and automation technologies such as the use of Unmanned Aerial Vehicles (UAV) for detecting differences in heat signatures and use of robotics for planting, spraying, and harvesting. As various IoT technologies mature beyond the R&D phase and go into general production, costs for everything from drones/UAVs to sensors will continually decrease, making connected agriculture more accessible to smaller farms and third world countries.

Mapping farms using aerial drones and terrestrial robots is rapidly becoming table-stakes for connected agriculture. Agribusiness will also deploy drones/robots to obtain real-time data regarding many aspects of farming operations. This will be a combination of aerial and land perspectives/images captured using multi-spectrum cameras and sensors installed on agricultural drones/robots. The revenue associated with this market opportunity will grow by 76.4% CAGR with a value of $850 million.

Target Audience:

  • Sensor providers
  • AgriTech companies
  • IoT service providers
  • IoT network providers
  • Semiconductor companies
  • Embedded systems companies

Select Research Findings:

  • The shift from conventional to data-driven farming is accelerating thanks to AI and IoT
  • IoT enabled systems are rapidly democratizing AgriTech for increasingly small farm ops
  • Consumption, weather, and distribution data analytics will dominate the macro-factors
  • Drone-based AgriTech imaging will witness 76.4% CAGR growth reaching $850M by 2025
  • IoTAg-enabled monitoring will be a leading component at $4.5B by 2025 with 72.4% CAGR

Table of Contents

1. Executive Summary

  • 1.1. Global Market for Smart Agriculture
  • 1.2. Outlook for Top Line Revenue Growth
  • 1.3. Success Factors
    • 1.3.1. Markets will be Largely Driven by Scale of Farming Operations
    • 1.3.2. Production and Enhancing Quality will be Marketplace Movers
    • 1.3.3. Key Go-to-Market Strategies

2. Overview

  • 2.1. Agriculture Industry
    • 2.1.1. Smart Farming vs. Traditional Farming
    • 2.1.2. Agriculture Industry Technological Transformation
    • 2.1.3. Vision for Agriculture Industry 2050
  • 2.2. Smart Agriculture Market Outlook
  • 2.3. IoTAg Technologies Shaping the Agriculture Industry
  • 2.4. IoT Enabled Smart Agriculture Solutions
    • 2.4.1. Precision Agriculture
    • 2.4.2. Indoor Farming
    • 2.4.3. Livestock Monitoring
    • 2.4.4. Fish Farming
  • 2.5. Smart Agriculture Systems and Functionality

3. IoT in Agriculture Market Dynamics

  • 3.1. IoTAg Market Drivers
    • 3.1.1. Growing Adoption of Technologies for Producing Higher Yields
    • 3.1.2. Governments Support for AgriTech Adoption
    • 3.1.3. Higher adoption of Precision Farming
  • 3.2. IoTAg Market Challenges
    • 3.2.1. Increasing Cost and Limited Technical Skills
    • 3.2.1. Technology Integration

4. IoT in Agriculture Opportunity Analysis

  • 4.1. Market for IoT in Agriculture
    • 4.1.1. Natural Disaster Management and Mitigation
    • 4.1.2. The Role of IoT in Reducing Agricultural Losses
    • 4.1.3. Integrating IoT with Farming Operations
    • 4.1.4. Smartphone Role in Monitoring/Controlling IoT in Agriculture
    • 4.1.5. Emerging IoT in Agriculture Business Models
  • 4.2. IoT for Large-scale Agriculture Operations
  • 4.3. IoT for Small to Medium Scale Farming

5. IoT in Agriculture Market Analysis and Forecasts

  • 5.1. Global IoT Agriculture Revenue by Application 2020-2025
  • 5.2. Global IoT Agriculture Revenue by Segment 2020-2025
    • 5.2.1. Global Intelligent Farm Equipment Market 2020-2025
    • 5.2.2. Global Smart Sensors in Agriculture Market 2020-2025
    • 5.2.3. Market by Smart Sensor Type for IoT in Agriculture 2020-2025
    • 5.2.4. Global Agricultural Drone Market 2020-2025
    • 5.2.5. Global Smart Farm Robot Market 2020-2025
    • 5.2.6. Global Agriculture Software Solutions Market 2020-2025
  • 5.3. Global IoT in Agriculture Solution Market
    • 5.3.1. Global Revenue for IoT Precision Agriculture
    • 5.3.2. Global Revenue for IoT Indoor Farming
    • 5.3.3. Global Revenue for IoT Livestock Farming
    • 5.3.4. Global Revenue for IoT Fisheries and Aquaculture
  • 5.4. IoT in Agriculture Revenue by Region
    • 5.4.1. North American Market for IoT in Agriculture
    • 5.4.2. European Market for IoT in Agriculture
    • 5.4.3. APAC Market for IoT in Agriculture
    • 5.4.4. Rest of World Market for IoT in Agriculture
  • 5.5. Global Managed Services in IoT Agriculture
  • 5.6. Predictive Analytics and Artificial Intelligence in Smart Agriculture

6. IoT in Agriculture Vendor Analysis

  • 6.1. Smart Agriculture Vendor Ecosystem
  • 6.2. IoT in Agriculture Vendor Strategies
  • 6.3. Select Smart Agriculture Solutions
    • 6.3.1. Accenture
    • 6.3.2. AgEagle
    • 6.3.3. Cattle Watch
    • 6.3.4. Climate Corporation (Monsanto)
    • 6.3.5. Decagon (METER Environment)
    • 6.3.6. Deepfield Robotics (Bosch)
    • 6.3.7. DroneDeploy
    • 6.3.8. FarmersEdge
    • 6.3.9. IBM
    • 6.3.10. Euravka
    • 6.3.11. FluxFarm Inc.
    • 6.3.12. John Deere
    • 6.3.13. Kaa Open Source IoT Platform
    • 6.3.14. Libelium Comunicaciones Distribuidas S.L.
    • 6.3.15. MTN
    • 6.3.16. SWIM
    • 6.3.17. SlantRange
    • 6.3.18. Telit
    • 6.3.19. ThingWorx (PTC)
    • 6.3.20. TopCon
    • 6.3.21. Intrinsyc Technologies Corp
    • 6.3.22. Raven Industries
    • 6.3.23. Semtech
    • 6.3.24. Trackit

7. Appendix: IoT Data Analytics

  • 7.1. IoT in Agriculture Data Analytics Market
  • 7.2. IoT in Agriculture Data Analytics 2020-2025