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人工智能精密農業

市場調查報告書

商品編碼

1574130

農業人工智慧市場：2024-2029 年預測

AI for Agriculture Market - Forecasts from 2024 to 2029

出版日期: 2024年09月24日 | 出版商:

Knowledge Sourcing Intelligence | 英文 140 Pages | 商品交期: 最快1-2個工作天內

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簡介目錄

農業人工智慧市場預計複合年成長率為24.57%，市場規模從2024年的2,021,502,000美元成長到2029年的6,062,706,000美元。

農場每天都會生成溫度、土壤、用水量和天氣等變數。人工智慧 (AI) 和機器學習模型即時使用這些資料來提供見解，例如確定最佳播種時間、選擇作物、選擇混合種子以提高產量以及做出其他農業決策。精密農業，也稱為智慧型系統，有助於提高產量的整體價值和準確性。人工智慧可以幫助識別害蟲、植物疾病和營養不良侵擾農場。人工智慧感測器可以在選擇在某個區域散佈哪種除草劑之前檢測並瞄準雜草。

多家科技公司開發了利用影像處理技術和人工智慧，並用噴槍精確監測雜草的機器人。這些機器人可以透過消除經常散佈在農作物上的大量化學物質來降低除草劑價格。透過大幅減少田間所需農藥的數量，這些先進的人工智慧散佈可以提高農業生產的標準。

農業人工智慧市場的促進因素：

日益全球化和新技術的採用預計將推動市場成長

客戶對農產品的需求不斷成長預計將推動市場價值成長。現代農業技術、政府措施和法規也在促進工業化。研發成本的變化、無人機使用的增加以及形式的變化正在增加產品的意義並有助於市場擴張。為了增加農業產量，政府正在透過州立農業大學 (SAU) 和印度農業研究委員會 (ICAR) 鼓勵該領域的研究與發展 (R&D)。 2023-2024年，農業研究與教育部（DARE）的預算將為950.4億印度盧比，高於2019-20年的784.617億印度盧比。該預算旨在開發新技術，在農民田間進行示範，並為他們提供採用現代方法的知識。

農業人工智慧市場的地理格局

北美在預測期內將經歷指數級成長

北美經濟的特點是可支配收入不斷增加、對自動化的持續投資、對物聯網的大賭注以及政府越來越重視開發國產人工智慧設備。多家農業技術廠商對人工智慧解決方案的研究也讓市場受益。正如人工智慧所預測的那樣，農業正在經歷一場技術革命。無人機、機器人和智慧監控系統在研究和現場實驗中的使用預計在未來幾年將大幅增加。此外，由於人工智慧技術在農業領域的廣泛使用，預計該區域市場將快速成長。

為什麼要購買這份報告？

富有洞察力的分析：獲得涵蓋關鍵和新興地區的深入市場洞察，重點關注客戶細分、政府政策和社會經濟因素、消費者偏好、行業和其他子區隔。
競爭格局：了解世界各地主要企業採取的策略策略，並了解採用正確策略滲透市場的潛力。
市場促進因素和未來趨勢：檢視動態因素和關鍵市場趨勢，並探討它們將如何影響未來的市場發展。
可行的建議：利用洞察力做出策略決策，在動態環境中發現新的業務流和收益。
迎合廣泛的受眾：對於新興企業、研究機構、顧問、中小型企業和大型企業來說有用且具有成本效益。

公司使用我們的報告的目的是什麼？

產業與市場考量、機會評估、產品需求預測、打入市場策略、地理擴張、資本投資決策、法律規範與影響、新產品開拓、競爭影響

調查範圍

過去的資料/預測，2022-2029
成長機會、挑戰、供應鏈前景、法規結構、顧客行為、趨勢分析
競爭定位、策略和市場佔有率分析
區域分析，包括收益成長和預測細分市場、國家
公司概況（策略、產品、財務資訊、主要發展等）

Variables on temperature, soil, water use, weather, etc., are generated daily by farms. Artificial intelligence (AI) and machine learning models use this data in real-time to derive insightful conclusions, including determining the optimal time for planting seeds, selecting crops, choosing hybrid seeds for higher yields, and other agricultural decisions. Precision farming, also called intelligent systems, helps improve the general value and precision of yields. AI helps to identify infestations, plant diseases, and malnourishment in farms. AI sensors can detect and target weeds before choosing which herbicide to apply in a region.

Many technical firms created robots that accurately monitor weeds with spray guns using image processing techniques and artificial intelligence. These robots can lower the price of herbicides by eliminating large amounts of the chemicals that are often sprayed on crops. By dramatically reducing the number of pesticides required in the fields, these sophisticated AI sprayers can raise the standard of agricultural output.

AI for Agriculture Market Drivers:

Increased globalization and adoption of new technology is anticipated to propel the market growth

Rising customer demand for agricultural products is expected to drive market value growth. Contemporary agricultural technologies, government initiatives, and regulations are also promoting industrialization. The shifting costs of research and development, as well as the increasing use of drones and changes in form, have contributed to the product implications, thus expanding the market. To boost agricultural output, the government is encouraging research and development (R&D) in the field through the State Agricultural Universities (SAUs) and the Indian Council of Agricultural Research (ICAR). In 2023-24, the Department of Agricultural Research & Education (DARE) will have a budget of Rs. 9504 crores, up from Rs. 7846.17 crores in 2019-20. This budget is aimed at developing new techniques demonstrating these in farmers' fields and equipping them with the knowledge to adopt modern methods.

AI for Agriculture Market Geographical Outlook

North America is witnessing exponential growth during the forecast period

The North American economy is characterized by rising disposable income, continuous investments in automation, large bets on the Internet of Things, and an increasing focus from governments on developing domestic AI equipment. Several agricultural technology vendors' research into artificial intelligence solutions benefits the market as well. In farming, there is a technological revolution coming, as predicted by AI. As drones, robots, and intelligent monitoring systems are used in research and field experiments, it is expected that this will increase significantly in years to come. Regional markets also expect rapid growth with increased use of AI-powered technologies within the agricultural sector.

Reasons for buying this report:-

Insightful Analysis: Gain detailed market insights covering major as well as emerging geographical regions, focusing on customer segments, government policies and socio-economic factors, consumer preferences, industry verticals, other sub- segments.
Competitive Landscape: Understand the strategic maneuvers employed by key players globally to understand possible market penetration with the correct strategy.
Market Drivers & Future Trends: Explore the dynamic factors and pivotal market trends and how they will shape up future market developments.
Actionable Recommendations: Utilize the insights to exercise strategic decision to uncover new business streams and revenues in a dynamic environment.
Caters to a Wide Audience: Beneficial and cost-effective for startups, research institutions, consultants, SMEs, and large enterprises.

What do businesses use our reports for?

Industry and Market Insights, Opportunity Assessment, Product Demand Forecasting, Market Entry Strategy, Geographical Expansion, Capital Investment Decisions, Regulatory Framework & Implications, New Product Development, Competitive Intelligence

Report Coverage:

Historical data & forecasts from 2022 to 2029
Growth Opportunities, Challenges, Supply Chain Outlook, Regulatory Framework, Customer Behaviour, and Trend Analysis
Competitive Positioning, Strategies, and Market Share Analysis
Revenue Growth and Forecast Assessment of segments and regions including countries
Company Profiling (Strategies, Products, Financial Information, and Key Developments among others)

The AI for agriculture market is segmented and analyzed as follows:

By Technology

Machine Learning
Computer Vision
Predictive Analytics

By Application

Agricultural Robots
Precision Farming
Drone Analytics
Livestock Monitoring
Weather Tracking
Others

By Geography

North America
USA
Canada
Mexico
South America
Brazil
Argentina
Others
Europe
Germany
France
United Kingdom
Spain
Others
Middle East and Africa
Saudi Arabia
Israel
UAE
Other
Asia Pacific
China
Japan
India
South Korea
Indonesia
Vietnam
Thailand
Others

1. INTRODUCTION

1.1. Market Overview
1.2. Market Definition
1.3. Scope of the Study
1.4. Market Segmentation
1.5. Currency
1.6. Assumptions
1.7. Base and Forecast Years Timeline
1.8. Key Benefits to the Stakeholder

2. RESEARCH METHODOLOGY

2.1. Research Design
2.2. Research Processes

3. EXECUTIVE SUMMARY

3.1. Key Findings
3.2. CXO Perspective

4. MARKET DYNAMICS

4.1. Market Drivers
4.2. Market Restraints
4.3. Porter's Five Forces Analysis
- 4.3.1. Bargaining Power of Suppliers
- 4.3.2. Bargaining Power of Buyers
- 4.3.3. Threat of New Entrants
- 4.3.4. Threat of Substitutes
- 4.3.5. Competitive Rivalry in the Industry
4.4. Industry Value Chain Analysis
4.5. Analyst View

5. AI FOR AGRICULTURE MARKET BY TECHNOLOGY

5.1. Introduction
5.2. Machine Learning
5.3. Computer Vision
5.4. Predictive Analytics

6. AI FOR AGRICULTURE MARKET BY APPLICATION

6.1. Introduction
6.2. Agricultural Robots
6.3. Precision Farming
6.4. Drone Analytics
6.5. Livestock Monitoring
6.6. Weather Tracking
6.7. Others

7. AI FOR AGRICULTURE MARKET BY GEOGRAPHY

7.1. Introduction
7.2. North America
- 7.2.1. By Technology
- 7.2.2. By Application
- 7.2.3. By Country
  - 7.2.3.1. USA
  - 7.2.3.2. Canada
  - 7.2.3.3. Mexico
7.3. South America
- 7.3.1. By Technology
- 7.3.2. By Application
- 7.3.3. By Country
  - 7.3.3.1. Brazil
  - 7.3.3.2. Argentina
  - 7.3.3.3. Others
7.4. Europe
- 7.4.1. By Technology
- 7.4.2. By Application
- 7.4.3. By Country
  - 7.4.3.1. Germany
  - 7.4.3.2. France
  - 7.4.3.3. United Kingdom
  - 7.4.3.4. Spain
  - 7.4.3.5. Others
7.5. Middle East and Africa
- 7.5.1. By Technology
- 7.5.2. By Application
- 7.5.3. By Country
  - 7.5.3.1. Saudi Arabia
  - 7.5.3.2. Israel
  - 7.5.3.3. UAE
  - 7.5.3.4. Others
7.6. Asia Pacific
- 7.6.1. By Technology
- 7.6.2. By Application
- 7.6.3. By Country
  - 7.6.3.1. China
  - 7.6.3.2. Japan
  - 7.6.3.3. India
  - 7.6.3.4. South Korea
  - 7.6.3.5. Indonesia
  - 7.6.3.6. Vietnam
  - 7.6.3.7. Thailand
  - 7.6.3.8. Others