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市場調査レポート

農業における人工知能市場:成長、動向、予測(2020~2025)

Artificial Intelligence in Agriculture Market - Growth, Trends and Forecasts (2020 - 2025)

発行 Mordor Intelligence LLP 商品コード 925451
出版日 ページ情報 英文 105 Pages
納期: 2-3営業日
価格
本日の銀行送金レート: 1USD=108.53円で換算しております。
農業における人工知能市場:成長、動向、予測(2020~2025) Artificial Intelligence in Agriculture Market - Growth, Trends and Forecasts (2020 - 2025)
出版日: 2020年04月01日 ページ情報: 英文 105 Pages
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概要

農業における世界の人工知能市場は、予測期間(2019-2024)中に26.2%のCAGRになると考えられます。

機械学習技術を使用して作物収量を最大化することが市場を牽引しています。水と栄養素の使用の効果、気候変動への適応、耐病性、栄養素の含有量やより良い味を決定する特定の遺伝子を探す面倒なプロセスを通して種の選別が行われています。機械学習、特にディープラーニングアルゴリズムは、さまざまな気候における作物のパフォーマンスを分析するために数十年のフィールドデータを使用し、このデータに基づいて、どの遺伝子が植物に有益な形質をもたらす可能性が最も高いかを予測する確率モデルを構築できます。

牛の顔認識技術の採用の増加も、市場を牽引しています。牛の顔認識プログラムや、体調スコアと摂食パターンを組み込んだ画像分類などの高度なメトリックを適用することで、酪農場は、牛のグループのすべての行動面を個別に監視できるようになりました。

ただし、標準化の不足は市場の成長抑制要因となっています。なぜなら、データ収集における基準の不足、およびデータ共有の不足が高く、機械学習と人工知能、および高度なアルゴリズム設計が非常に速く動いているため、適切にタグ付けされた意味のある収集農業データがかなり遅れているためです。

当レポートでは、農業における人口知能市場を調査し、市場概要、市場の成長要因および阻害要因の分析、用途別・配置別・地域別の市場規模の推移と予測、競合情勢、主要企業のプロファイル、市場機会など、包括的な情報を提供しています。

目次

第1章 イントロダクション

  • 調査成果
  • 調査の前提条件
  • 調査範囲

第2章 調査手法

第3章 エグゼクティブサマリー

第4章 市場力学

  • 市場概要
  • 市場の推進要因と制約のイントロダクション
  • 市場成長要因
  • 市場の抑制要因
  • 業界の魅力-ポーターのファイブフォース分析
    • 新規参入の脅威
    • バイヤー/消費者の交渉力
    • サプライヤーの交渉力
    • 代替製品の脅威
    • 競争の激化

第5章 市場細分化

  • 用途別
    • 天気追跡
    • 精密農業
    • ドローン分析
  • 配置別
    • クラウド
    • オンプレミス
    • ハイブリッド
  • 地域別
    • 北米
    • 欧州
    • アジア太平洋地域
    • 南米
    • その他の地域

第6章 競合情勢

  • ベンダーの市場シェア
  • 最も採用されている戦略
  • 企業プロファイル
    • Microsoft Corporation
    • IBM Corporation
    • Granular, Inc.
    • aWhere, Inc.
    • Prospera Technologies Ltd.
    • Gamaya SA
    • ec2ce
    • PrecisionHawk Inc.
    • Cainthus Corp.
    • Tule Technologies Inc.

第7章 市場機会および将来動向

目次
Product Code: 61298

The global Artificial Intelligence in agriculture market is witnessing a CAGR of 26.2% during the forecast period (2019-2024).

  • Maximize crop yield using machine learning technique is driving the market. Species selection is a tedious process of searching for specific genes that determine the effectiveness of water and nutrients use, adaptation to climate change, disease resistance, as well as nutrients content or a better taste. Machine learning, in particular, deep learning algorithms, take decades of field data to analyze crops performance in various climates and based on this data one can build a probability model that would predict which genes will most likely contribute a beneficial trait to a plant.
  • Increase in the adoption of cattle face recognition technology is driving the market. Through the application of advanced metrics, including cattle facial recognition programs and image classification incorporated with body condition score and feeding patterns, dairy farms are now being able to individually monitor all behavioral aspects in a group of cattle.
  • However, lack of standardization is restraining the market growth as lack of standards in data collection, and lack of data sharing is high, and machine learning and artificial intelligence and advanced algorithm design have moved so fast, but the collection of well-tagged, meaningful agricultural data is way behind.

Key Market Trends

Labor Shortage and Increasing Costs of Labor to Drive the Artificial Intelligence Market

Across the world, a huge decline of the workforce is observed due to many reasons, like the lack of skilled labor, aging of farmers, and young farmers finding farming an unattractive profession, thus encouraging trends for automated farming operations. According to the International Labor Organization(ILO), agricultural labors in the percentage of the workforce declined from 81% to 48.2% in developing countries. Also, developed countries are not an exception in such a huge decline. Asia-Pacific, where agriculture occupies a major part of the economy, has a huge decline in workforce, which was nearly about 9% from 2015 to 2017. In Japan, the number of people working in farms witnessed a steep fall to 1.7 million in the year 2015, a 15% decline from the previous year.

The European agriculture sector has also faced such a huge decline in the workforce, which is nearly accounting to 12.8% for the corresponding period. The trend of decline in the agricultural workforce is encouraging government and private organizations to focus on automation operations by adopting artificial intelligence technologies in the agriculture sector. Owing to the above factors, the market for artificial intelligence in the agricultural sector is likely to boom in the years to come.

China's Technological Innovations to Accelerate the Agriculture Sector

The technological innovations pertaining to the Chinese market, are also accelerating the growth and transforming the global artificial intelligence market in the agriculture sector. For instance, McFly's Intelligent agricultural monitoring drone, GAGO's large scale application of AI technology in crop production and livestock farming, and UniStrong's "Huinong" Beidou navigation agricultural automatic driving system are few recent innovations prevailing in the Chinese Ai sector. Additionally, few technological giants have also begun to make deployment in the agricultural sector. For instance in the year 2018, JD.com's "Jing Dong Farm" has made its debut, similarly in June 2018, Alibaba's Et agricultural brain has been launched. Thus, increasing innovation in the Chinese AI sector is likely to further boost the adoption of AI in the agriculture in the coming future.

Competitive Landscape

The AI market in agriculture is fragmented, as a number of players supplying the same product on lower-cost make market competition stiff. Also, technological advancements by players and the high presence of local and regional players pose a major threat in a price-sensitive market. Key players are Microsoft Corp., IBM Corp. (NITI Aayog), Agribotix LLC, etc.

May 2019 - XAG, a Chinese firm, presented its innovative solutions of combining drones with AI and IoT technology to achieve precision agriculture and induce transformational changes to the food system in 3rd AI for Good Global Summit, in Geneva. XAG is driving AI-powered intelligent devices such as drones and sensors to establish digital farming infrastructure in rural areas and enable precision agriculture which, for example, accurately targets pesticides, seeds, fertilizers, and water to wherever it is needed.

Reasons to Purchase this report:

  • The market estimate (ME) sheet in Excel format
  • Report customization as per the client's requirements
  • 3 months of analyst support

Table of Contents

1 INTRODUCTION

  • 1.1 Study Deliverables
  • 1.2 Study Assumptions
  • 1.3 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET DYNAMICS

  • 4.1 Market Overview
  • 4.2 Introduction to Market Drivers and Restraints
  • 4.3 Market Drivers
  • 4.4 Market Restraints
  • 4.5 Industry Attractiveness - Porter's Five Force Analysis
    • 4.5.1 Threat of New Entrants
    • 4.5.2 Bargaining Power of Buyers/Consumers
    • 4.5.3 Bargaining Power of Suppliers
    • 4.5.4 Threat of Substitute Products
    • 4.5.5 Intensity of Competitive Rivalry

5 MARKET SEGMENTATION

  • 5.1 Application
    • 5.1.1 Weather Tracking
    • 5.1.2 Precision Farming
    • 5.1.3 Drone Analytics
  • 5.2 Deployment
    • 5.2.1 Cloud
    • 5.2.2 On-Premise
    • 5.2.3 Hybrid
  • 5.3 Geography
    • 5.3.1 North America
      • 5.3.1.1 US
      • 5.3.1.2 Canada
      • 5.3.1.3 Mexico
      • 5.3.1.4 Rest of North America
    • 5.3.2 Europe
      • 5.3.2.1 Germany
      • 5.3.2.2 UK
      • 5.3.2.3 Italy
      • 5.3.2.4 Spain
      • 5.3.2.5 Rest of Europe
    • 5.3.3 Asia Pacific
      • 5.3.3.1 China
      • 5.3.3.2 Japan
      • 5.3.3.3 India
      • 5.3.3.4 Australia
      • 5.3.3.5 Rest of Asia-Pacific
    • 5.3.4 South America
      • 5.3.4.1 Brazil
      • 5.3.4.2 Argentina
      • 5.3.4.3 Rest of South America
    • 5.3.5 Rest of the World

6 COMPETITIVE LANDSCAPE

  • 6.1 Vendor Market Share
  • 6.2 Most Adopted Strategies
  • 6.3 Company Profiles
    • 6.3.1 Microsoft Corporation
    • 6.3.2 IBM Corporation
    • 6.3.3 Granular, Inc.
    • 6.3.4 aWhere, Inc.
    • 6.3.5 Prospera Technologies Ltd.
    • 6.3.6 Gamaya SA
    • 6.3.7 ec2ce
    • 6.3.8 PrecisionHawk Inc.
    • 6.3.9 Cainthus Corp.
    • 6.3.10 Tule Technologies Inc.

7 MARKET OPPORTUNITIES AND FUTURE TRENDS