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市場調查報告書

全球農業AI市場:提供,技術,用途,各地區 - 趨勢分析,競爭市場佔有率,及預測(2016年∼2026年)

AI in Agriculture Market by Offering, Technology, Technology, Application, by Region ; Trend Analysis, Competitive Market Share & Forecast, 2016-2026

出版商 Blueweave Consulting & Research Private Limited 商品編碼 926557
出版日期 內容資訊 英文
商品交期: 最快1-2個工作天內
價格
全球農業AI市場:提供,技術,用途,各地區 - 趨勢分析,競爭市場佔有率,及預測(2016年∼2026年) AI in Agriculture Market by Offering, Technology, Technology, Application, by Region ; Trend Analysis, Competitive Market Share & Forecast, 2016-2026
出版日期: 2020年01月02日內容資訊: 英文
簡介

全球農業AI市場在預測期間內預計將以21.6%的年複合成長率成長,2026年達到30億1,300萬美元的規模。該市場的成長,有對農業生產的需求高漲,先進的技術和智慧感應器的採用增加,在農場無人機的迅速需求,監視家畜的必要性增加等要素。還有無人曳引機和農業用無人機等預計促進今後的市場成長。

本報告提供全球農業AI市場的相關調查,市場機會和課題,成長及阻礙因素,各提供、技術、用途、地區的市場分析,競爭情形,主要企業的簡介等資訊。

目錄

第1章 調查架構

  • 調查目的
  • 產品概要
  • 市場區隔

第2章 調查方法

  • 質性調查
  • 數量的調查
  • 主要的調查受訪者的明細:各地區
  • 一次調查受訪者的明細
  • 市場規模的估計
  • 調查的前提條件
  • 市場分析與資料三角測量

第3章 摘要整理

第4章 農業洞察的全球的AI

  • 產業價值鏈分析
  • DROC分析
    • 成長要素
    • 阻礙因素
    • 市場機會
    • 課題
  • 技術預測
  • 法律規範
  • 企業的市場佔有率分析
  • 波特的五力分析
  • 策略性預測

第5章 市場概要

  • 市場估計及預測:各銷售額
  • 市場佔有率及預測
    • 各提供
    • 各技術
    • 各用途
    • 各地區

第6章 北美

第7章 歐洲

第8章 亞太地區

第9章 南美

第10章 中東及非洲

第11章 企業簡介(公司概要,財務矩陣,產品風景,主要人員,主要競爭,聯絡原住所,策略性展望)

  • IBM Corporation
  • Microsoft Corporation
  • Bayer AG
  • Deere & Company
  • A.A.A. Taranis Visual Ltd
  • AgEagle Aerial Systems Inc.
  • AGCO Corporation
  • Raven Industries
  • Ag Leader Technology
  • Trimble Inc.
  • Google LLC
  • Gamaya SA
  • Granular Inc.
  • PrecisionHawk
  • SAP
  • 其他的主要企業
目錄
Product Code: BWC19397

According to BlueWeave Consulting, The Global AI in Agriculture market is projected to reach the valuation of US$ 3013 million by the year 2026 by growing at a CAGR of 21.6%. This can be attributed to factors such as rising demand for agricultural production, increased adoption of advanced technologies and smart sensors, rapid demand for drones in farms, and increased need for monitoring of livestock.

Using AI in agriculture provides various focal points, such as maximizing product yields using machine learning and Image recognition methods. For example, the International Crops Research Institute for Semi-Arid Tropics (ICRISAT) partnered with Microsoft to develop an AI-based sowing app that sends sowing alerts to ranchers indicating the following date. Earlier technological innovations and the modernization of GPS make ranchers and agricultural specialist cooperatives expect that further changes would increase profitability. For example, in addition to the present non-military benefits offered by GPS, nations are preparing to upgrade a second and a third signal on GPS satellites. This execution of new flags will improve the quality and, in addition, the ability of farming activities, and in the coming years will increase the overall productivity.

Driverless tractor is trending in agriculture global market

Driverless tractor is a technological development as these tractors can automatically steer using GPS-based technology, raise tools from the ground, identify a farm's boundaries and can be remotely operated using a smartphone. A smaller fleet of automated tractors could increase farmers ' incomes by more than 10 per cent and increased farm labor costs. The market is driven by a rise in the adoption of cattle face recognition technology. Through applying advanced metrics including facial recognition systems for cattle and image classification combined with body condition score and feeding habits, dairy farms are now able to monitor all behavioral factors in a cattle group individually. Increasing use of Unmanned Aerial Vehicles (UAVs) across agricultural farms is driving the market as the use of drones in the agricultural industry can be used in crop field scanning with compact multi-spectral imaging sensors, GPS map production through on-board cameras, heavy payload transport and monitoring of livestock with thermal camera-equipped drones, which increases the demand for UAVs.

Agricultural Drones to Drive the Growth of AI in Agriculture global market

Drones fitted with hyperspectral, multispectral, or thermal sensors can locate areas that require irrigation changes. When crops have begun to develop, these sensors can measure their vegetation index and health indicator via AI by measuring the heat signature of the crop. As the global population is projected to exceed XX billion by 2050, it is expected that agricultural consumption will increase by a massive ratio, where drones have now been mainstreamed for smart farming to assist farmers in a range of tasks from analysis and planning to actual crop planting, and subsequent field monitoring to determine health and growth. AgEagle Aerial Systems (company that acquired Agrobotix LLC) plans to develop new products with new technologies, such as weather data, advanced image recognition and precise analysis, to give farmers / consumers better recommendations.

Asia-Pacific expected to witness significant growth in the market in upcoming years

Followed by North America, high growth rates in Asia Pacific are expected in the coming years due to growing demand from developing nations such as India and China. In addition, increasing adoption of mechanical technology and IoT gadgets in agriculture is also evaluated in order to drive the AI in the agricultural industry. In addition, Europe is leading in the agricultural sector with a lucrative pace in global AI. Farmers are managing nearly half of the European land area, making agriculture a dominant sector in Europe. The trend in monitoring and reporting tools for indoor and outdoor farms, and providing a visualization of the entire farmer's production using computer vision and artificial intelligence, is increasing the agricultural AI market. Row cultivation is performed by AI in various European countries, where the robot uses 20x less herbicide due to its high accuracy in row crop weeding.

AI In Agriculture: Competitive Landscape

Artificial intelligence in Agriculture market is fragmented owing to the presence of number of large-sized companies, mid-sized & small-sized companies, and many start-ups that provide artificial intelligence in Agriculture industry. However, the companies that hold the majority share of artificial intelligence in Agriculture market are IBM Corporation, Microsoft Corporation, Bayer AG, Deere & Company, A.A.A. Taranis Visual Ltd, AgEagle Aerial Systems Inc., AGCO Corporation, Raven Industries, Ag Leader Technology, Trimble Inc., Google LLC, Gamaya SA, Granular Inc., PrecisionHawk, SAP and Other Prominent Players

Don't miss the business opportunity of the AI in Agriculture market. Consult our analyst and gain crucial insights and facilitate your business growth.

The in-depth analysis of the report provides the growth potential, upcoming trends, and statistics of the AI in Agriculture market size & forecast. The report promises to provide state-of-the-art technology of AI in Agriculture and industry insights which help decision-makers to make sound strategic decisions. Furthermore, the report also analyzes the market drivers and challenges and competitive analysis of the market.

Table of Contents

1. Research Framework

  • 1.1. Research Objective
  • 1.2. Product Overview
  • 1.3. Market Segmentation

2. Research Methodology

  • 2.1. Qualitative Research
    • 2.1.1. Primary & Secondary Sources
  • 2.2. Quantitative Research
    • 2.2.1. Primary & Secondary Sources
  • 2.3. Breakdown of Primary Research Respondents, By Region
    • 2.3.1. Secondary Research
    • 2.3.2. Primary Research
  • 2.4. Breakdown of Primary Research Respondents
  • 2.5. Market Size Estimation
  • 2.6. Assumption for The Study
  • 2.7. Market Breakdown & Data Triangulation

3. Executive Summary

4. Global AI in Agriculture Insights

  • 4.1. Industry Value Chain Analysis
  • 4.2. DROC Analysis
    • 4.2.1. Growth Drivers
    • 4.2.2. Restraints
    • 4.2.3. Opportunities
    • 4.2.4. Challenges
  • 4.3. Technological Landscape
  • 4.4. Regulatory Framework
  • 4.5. Company Market Share Analysis,2019
  • 4.6. Porter's Five forces analysis
    • 4.6.1. Bargaining Power of Suppliers
    • 4.6.2. Bargaining Power of Buyers
    • 4.6.3. Threat of New Entrants
    • 4.6.4. Threat of Substitutes
    • 4.6.5. Intensity of Rivalry
  • 4.7. Strategic Outlook

5. Global AI in Agriculture Market Overview

  • 5.1. Market Estimates & Forecast by Value, 2016-2026
    • 5.1.1. By Value (USD)
  • 5.2. Market Share & Forecast
    • 5.2.1. By Offering
      • 5.2.1.1. Hardware
      • 5.2.1.1.1. Processor
      • 5.2.1.1.2. Storage Device
      • 5.2.1.1.3. Network
      • 5.2.1.2. Software
      • 5.2.1.2.1. AI Solutions
      • 5.2.1.2.2. AI Platform
      • 5.2.1.3. Services
      • 5.2.1.3.1. Deployment & Integration
      • 5.2.1.3.2. Support & Maintenance
    • 5.2.2. By Technology
      • 5.2.2.1. Machine Learning
      • 5.2.2.2. Computer Vision
      • 5.2.2.3. Predictive Analytics
    • 5.2.3. By Application
      • 5.2.3.1. Precision Farming
      • 5.2.3.2. Yield Monitoring
      • 5.2.3.2.1. Field Mapping
      • 5.2.3.2.2. Crop Scouting
      • 5.2.3.2.3. Weather Tracking and Forecasting
      • 5.2.3.2.4. Irrigation Management
      • 5.2.3.3. Livestock Monitoring
      • 5.2.3.4. Drone Analytics
      • 5.2.3.5. Agriculture Robots
      • 5.2.3.6. Other Applications (Smart Greenhouse Application, Soil Management etc.)
    • 5.2.4. By Region
      • 5.2.4.1. North America
      • 5.2.4.2. Europe
      • 5.2.4.3. Asia Pacific
      • 5.2.4.4. Latin America
      • 5.2.4.5. Middle East & Africa

6. North America AI in Agriculture Market

  • 6.1. Market Estimates & Forecast by Value, 2016-2026
    • 6.1.1. By Value (USD)
  • 6.2. Market Share & Forecast
    • 6.2.1. By Offering
    • 6.2.2. By Technology
    • 6.2.3. By Application
    • 6.2.4. By Country
      • 6.2.4.1. U.S
      • 6.2.4.2. Canada

7. Europe AI in Agriculture Market

  • 7.1. Market Estimates & Forecast by Value, 2016-2026
    • 7.1.1. By Value (USD)
  • 7.2. Market Share & Forecast
    • 7.2.1. By Offering
    • 7.2.2. By Technology
    • 7.2.3. By Application
    • 7.2.4. By Country
      • 7.2.4.1. Germany
      • 7.2.4.2. U.K
      • 7.2.4.3. France
      • 7.2.4.4. Italy
      • 7.2.4.5. Rest of Europe

8. Asia Pacific AI in Agriculture Market

  • 8.1. Market Estimates & Forecast by Value, 2016-2026
    • 8.1.1. By Value (USD)
  • 8.2. Market Share & Forecast
    • 8.2.1. By Offering
    • 8.2.2. By Technology
    • 8.2.3. By Application
    • 8.2.4. By Country
      • 8.2.4.1. China
      • 8.2.4.2. India
      • 8.2.4.3. Japan
      • 8.2.4.4. South Korea
      • 8.2.4.5. Rest of APAC

9. Latin America AI in Agriculture Market

  • 9.1. Market Estimates & Forecast by Value, 2016-2026
    • 9.1.1. By Value (USD)
  • 9.2. Market Share & Forecast
    • 9.2.1. By Offering
    • 9.2.2. By Technology
    • 9.2.3. By Application
    • 9.2.4. By Country
      • 9.2.4.1. Brazil
      • 9.2.4.2. Mexico
      • 9.2.4.3. Argentina
      • 9.2.4.4. Rest of Latin America

10.Middle East & Africa AI in Agriculture Market

  • 10.1. Market Estimates & Forecast by Value, 2016-2026
    • 10.1.1. By Value (USD)
  • 10.2. Market Share & Forecast
    • 10.2.1. By Offering
    • 10.2.2. By Technology
    • 10.2.3. By Application
    • 10.2.4. By Country
      • 10.2.4.1. Saudi Arabia
      • 10.2.4.2. UAE
      • 10.2.4.3. South Africa
      • 10.2.4.4. Rest of MEA

11.Company Profile (Company Overview, Financial Matrix, Product landscape, Key Personnel, Key Competitors, Contact Address, and Strategic Outlook) *

  • 11.1. IBM Corporation
  • 11.2. Microsoft Corporation
  • 11.3. Bayer AG
  • 11.4. Deere & Company
  • 11.5. A.A.A. Taranis Visual Ltd
  • 11.6. AgEagle Aerial Systems Inc.
  • 11.7. AGCO Corporation
  • 11.8. Raven Industries
  • 11.9. Ag Leader Technology
  • 11.10. Trimble Inc.
  • 11.11. Google LLC
  • 11.12. Gamaya SA
  • 11.13. Granular Inc.
  • 11.14. PrecisionHawk
  • 11.15. SAP
  • 11.16. Other Prominent Players