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1776746

物聯網和人工智慧智慧農業市場預測至 2032 年：按組件、農場規模、部署模式、應用、最終用戶和地區進行的全球分析

Smart Farming Market by IoT & AI Forecasts to 2032 - Global Analysis By Component (Hardware, Software and Services), Farm Size, Deployment Model, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，全球物聯網和人工智慧智慧農業市場預計在 2025 年達到 241.8 億美元，到 2032 年將達到 551.6 億美元，預測期內的複合年成長率為 12.5%。

智慧農業利用物聯網、人工智慧、機器人和巨量資料等先進技術來提高農業生產力、效率和永續性。智慧農業能夠實現精密農業實踐，例如即時監測、數據主導決策以及最佳化灌溉、施肥和病蟲害防治。透過整合數位工具，智慧農業可以幫助農民減少資源消耗、降低成本、提高作物產量，同時最大限度地減少對環境的影響並適應不斷變化的氣候條件。

根據美國環保署（EPA）的報告，精密農業可減少用水量高達30%，並提高作物產量20%。

全球糧食需求不斷成長

智慧農業技術正在成為提高生產力和永續性的關鍵解決方案。精密農業工具，例如物聯網感測器、人工智慧主導的分析和GPS導航設備，使農民能夠最佳化投入並最大限度地提高產量。這些創新有助於減少廢棄物、節約用水並改善土壤健康，從而解決糧食安全和環境問題。各國政府和私相關人員正在加大對農業技術的投資，以滿足未來的糧食需求。因此，智慧農業正成為全球現代農業策略的基石。

資料隱私和安全問題

數位科技與農業的融合引發了人們對資料隱私和網路安全的擔憂。農民和相關企業會產生大量敏感數據，包括作物生長、土壤條件和專有耕作方法等資訊。如果沒有強大的安全通訊協定，這些資料很容易遭到洩漏、濫用和未授權存取。尤其是中小型農場，可能缺乏實施先進網路安全措施的資源。這些擔憂可能會減緩智慧農業技術的普及，尤其是在數位基礎設施有限的地區。

農業供應鏈中的區塊鏈整合

區塊鏈技術為提升農業供應鏈的透明度和可追溯性提供了變革潛力。透過在分散式帳本上記錄所有交易和商品流動，區塊鏈可確保資料完整性並減少詐欺。智慧支付可以實現支付和物流自動化，提高效率並減少糾紛。隨著消費者要求食品採購更加課責，區塊鏈在生產商和零售商中的應用日益增加。區塊鏈與物聯網和人工智慧的整合有望將農業商業業務的信任度和效率提升到新的水平。

標準化和互通性問題

智慧農業生態系統由來自不同供應商的硬體、軟體和數據平台組成。主要挑戰在於這些系統之間缺乏標準化和互通性。不相容的技術阻礙了數據的無縫交換和整合，從而限制了精密農業的有效性。農民往往難以同步設備和平台，導致效率低下和成本增加。這種碎片化也阻礙了對新技術的投資，尤其是對小農戶而言。

COVID-19的影響

新冠疫情加速了智慧農業技術的普及，因為勞動力短缺和供應鏈中斷暴露了傳統農業的脆弱性。農民轉向自動化、遠端監控和數據主導的決策，以便在受限條件下維持生產力。無人機、自動駕駛曳引機和基於感測器的灌溉系統成為流行的非接觸式解決方案。這場危機也凸顯了韌性和在地化食品體系的重要性，激發了人們對垂直農業和智慧溫室的興趣。疫情引發了農業科技格局的長期結構性轉變。

預計軟體領域將成為預測期內最大的領域

軟體領域預計將在預測期內佔據最大的市場佔有率，這得益於其在數據分析、決策支援和農場管理方面的核心作用。先進的平台能夠即時監測作物健康狀況、天氣模式和設備性能。雲端基礎的解決方案提供擴充性和遠端存取功能，使其成為大規模分散式農業營運的理想選擇。與人工智慧和機器學習的整合增強了預測能力，使農民能夠主動管理風險。

預計智慧溫室領域將在預測期內見證最高的複合年成長率。

預計智慧溫室領域將在預測期內實現最高成長率。這些系統利用物聯網感測器、氣候控制技術和人工智慧演算法來最佳化溫度、濕度和光照，從而提高作物產量，減少資源消費量，並最大限度地減少農藥使用。都市化和垂直農業的興起進一步推動了對智慧溫室解決方案的需求。

佔比最大的地區：

預計亞太地區將在預測期內佔據最大的市場佔有率，這得益於其龐大的農業基礎和快速的技術應用。中國、印度和日本等國家正大力投資農業技術，以提高生產力並確保糧食安全。智慧型手機和價格實惠的物聯網設備的日益普及，甚至使小農戶也能參與數位革命。市場參與企業為推動數位農業和農村互聯互通所做的努力，正在推動市場成長。

複合年成長率最高的地區：

在預測期內，北美預計將實現最高的複合年成長率，這得益於其先進的基礎設施和精密農業的早期應用。美國和加拿大擁有主要的農業科技公司和研究機構，推動技術創新。該地區的農民擴大採用人工智慧、機器人技術和數據分析來提高效率和永續性。政府透過補貼和氣候智慧型農業計畫提供的支持進一步推動了成長。

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  • 區域細分
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目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 研究途徑
  • 研究材料
    • 主要研究資料
    • 次級研究資訊來源
    • 先決條件

第3章市場走勢分析

  • 驅動程式
  • 抑制因素
  • 機會
  • 威脅
  • 應用分析
  • 最終用戶分析
  • 新興市場
  • COVID-19的影響

第4章 波特五力分析

  • 供應商的議價能力
  • 買家的議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

第5章全球物聯網與人工智慧智慧農業市場（按組成部分）

  • 硬體
    • 感應器
    • 無人機和無人駕駛飛行器
    • 控制系統
    • GPS/GNSS設備
    • 機器人和自動化工具
    • 顯示器和手持電腦
    • 智慧型相機
  • 軟體
    • 人工智慧演算法和機器學習平台
    • 雲端基礎的分析平台
    • 預測分析工具
    • GIS 和遙感探測軟體
    • 農場管理軟體（FMS）
  • 服務
    • 系統整合
    • 數據分析服務
    • 維護和支援
    • 託管服務
    • 連線服務

第6章 全球物聯網與人工智慧智慧農業市場（依農場規模）

  • 小型農場
  • 中型農場
  • 大型農場

第7章全球物聯網與人工智慧智慧農業市場（按部署模式）

  • 本地
  • 雲端基礎

第8章全球物聯網與人工智慧智慧農業市場（按應用）

  • 精密農業
  • 自動收割和播種
  • 牲畜監控
  • 作物健康監測和疾病檢測
  • 智慧溫室
  • 天氣預報
  • 水產養殖
  • 土壤監測
  • 灌溉管理
  • 最佳化供應鍊和市場進入
  • 其他用途

第9章全球物聯網和人工智慧智慧農業市場（按最終用戶）

  • 私人農場主
  • 農業合作社
  • 科學研究機構和大學
  • 政府
  • 農業業務
  • 其他最終用戶

第 10 章全球物聯網與人工智慧智慧農業市場（按地區）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第11章 重大進展

  • 協議、夥伴關係、合作和合資企業
  • 收購與合併
  • 新產品發布
  • 業務擴展
  • 其他關鍵策略

第12章 公司概況

  • Deere & Company
  • Ag Leader Technology
  • Trimble Inc.
  • Arugga
  • AGCO Corporation
  • FarmWise
  • Topcon Corporation
  • Small Robot Company
  • CropIn Technology Solutions Pvt. Ltd.
  • Intello Labs Pvt Ltd
  • DeHaat
  • Stellapps
  • Fasal
  • BouMatic Robotic BV
  • Raven Industries, Inc.
Product Code: SMRC30077

According to Stratistics MRC, the Global Smart Farming Market by IoT & AI is accounted for $24.18 billion in 2025 and is expected to reach $55.16 billion by 2032 growing at a CAGR of 12.5% during the forecast period.Smart farming is the use of advanced technologies like IoT, AI, robotics, and big data to enhance agricultural productivity, efficiency, and sustainability. It enables real-time monitoring, data-driven decision-making, and precision farming practices, such as optimized irrigation, fertilization, and pest control. By integrating digital tools, smart farming helps farmers reduce resource use, lower costs, and increase crop yields while minimizing environmental impact and adapting to changing climate conditions.

According to a report by the U.S. Environmental Protection Agency (EPA), precision agriculture can reduce water usage by up to 30% and enhance crop yields by 20%.

Market Dynamics:

Driver:

Rising global food demand

Smart farming technologies are emerging as a critical solution to enhance productivity and sustainability. Precision agriculture tools such as IoT sensors, AI-driven analytics, and GPS-guided equipment enable farmers to optimize input usage and maximize yields. These innovations help reduce waste, conserve water, and improve soil health, addressing both food security and environmental concerns. Governments and private stakeholders are increasingly investing in agri-tech to meet future food demands. As a result, smart farming is becoming a cornerstone of modern agricultural strategies worldwide.

Restraint:

Data privacy and security concerns

The integration of digital technologies in agriculture raises significant concerns around data privacy and cybersecurity. Farmers and agribusinesses are generating vast amounts of sensitive data, including crop performance, soil conditions, and proprietary farming practices. Without robust security protocols, this data is vulnerable to breaches, misuse, or unauthorized access. Small and medium-sized farms, in particular, may lack the resources to implement advanced cybersecurity measures. These concerns can slow the adoption of smart farming technologies, especially in regions with limited digital infrastructure.

Opportunity:

Integration of blockchain in agri-supply chains

Blockchain technology offers transformative potential for enhancing transparency and traceability in agricultural supply chains. By recording every transaction and movement of goods on a decentralized ledger, blockchain ensures data integrity and reduces fraud. Smart contracts can automate payments and logistics, improving efficiency and reducing disputes. As consumers demand more accountability in food sourcing, blockchain adoption is gaining momentum among producers and retailers. The convergence of blockchain with IoT and AI is expected to unlock new levels of trust and efficiency in agri-business operations.

Threat:

Standardization and interoperability issues

The smart farming ecosystem comprises a wide array of hardware, software, and data platforms from different vendors. A major challenge lies in the lack of standardization and interoperability among these systems. Incompatible technologies hinder seamless data exchange and integration, limiting the effectiveness of precision agriculture. Farmers often struggle to synchronize equipment and platforms, leading to inefficiencies and increased costs. This fragmentation also discourages investment in new technologies, especially for smallholders.

Covid-19 Impact

The COVID-19 pandemic accelerated the adoption of smart farming technologies as labour shortages and supply chain disruptions exposed vulnerabilities in traditional agriculture. Farmers turned to automation, remote monitoring, and data-driven decision-making to maintain productivity under restricted conditions. Drones, autonomous tractors, and sensor-based irrigation systems gained traction as contactless solutions. The crisis also highlighted the importance of resilient and localized food systems, boosting interest in vertical farming and smart greenhouses. The pandemic served as a catalyst for long-term structural changes in the agri-tech landscape.

The software segment is expected to be the largest during the forecast period

The software segment is expected to account for the largest market share during the forecast period, due to its central role in data analytics, decision support, and farm management. Advanced platforms enable real-time monitoring of crop health, weather patterns, and equipment performance. Cloud-based solutions offer scalability and remote access, making them ideal for large-scale and distributed farming operations. Integration with AI and machine learning enhances predictive capabilities, allowing farmers to proactively manage risks.

The smart greenhouses segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the smart greenhouses segment is predicted to witness the highest growth rate, due totheir ability to provide controlled environments for year-round cultivation. These systems leverage IoT sensors, climate control technologies, and AI algorithms to optimize temperature, humidity, and lighting. The result is higher crop yields, reduced resource consumption, and minimal pesticide use. Urbanization and the rise of vertical farming are further driving demand for smart greenhouse solutions.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market sharedue toits vast agricultural base and rapid technological adoption. Countries like China, India, and Japan are investing heavily in agri-tech to boost productivity and ensure food security. Increasing smartphone penetration and affordable IoT devices are enabling smallholder farmers to participate in the digital revolution.Government initiatives promoting digital agriculture and rural connectivity are accelerating market growth.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR, owing to its advanced infrastructure and early adoption of precision agriculture. The U.S. and Canada are home to leading agri-tech companies and research institutions driving innovation. Farmers in the region are increasingly adopting AI, robotics, and data analytics to enhance efficiency and sustainability. Government support through subsidies and climate-smart agriculture programs is further fuelling growth.

Key players in the market

Some of the key players profiled in the Smart Farming Market by IoT & AI include Deere & Company, Ag Leader Technology, Trimble Inc., Arugga, AGCO Corporation, FarmWise, Topcon Corporation, Small Robot Company, CropIn Technology Solutions Pvt. Ltd., Intello Labs Pvt Ltd, DeHaat, Stellapps, Fasal, BouMatic Robotic B.V., and Raven Industries, Inc.

Key Developments:

In May 2025, John Deere announced the acquisition of Sentera, a leading provider of remote imagery solutions for agriculture headquartered in St. Paul, Minnesota. This acquisition will advance the capabilities of John Deere's existing technology offerings, providing farmers and ag service providers with a more comprehensive set of tools to generate and use data to make decisions that improve farm profitability, efficiency, and sustainability.

In April 2025, Trimble announced a new integration between its B2W Track and Trimble Siteworks software systems to automate and enhance progress quantity tracking for earthwork and civil contractors. This unique field-to-office connection allows contractors to compare actual material production quantities achieved to planned quantities more easily and accurately. Continuous assessment of field progress can be critical for civil contractors, enabling them to make timely operational adjustments.

Components Covered:

  • Hardware
  • Software
  • Services

Farm Sizes Covered:

  • Small Farms
  • Medium-Sized Farms
  • Large-Scale Farms

Deployment Models Covered:

  • On-Premise
  • Cloud-Based

Applications Covered:

  • Precision Farming
  • Automated Harvesting & Seeding
  • Livestock Monitoring
  • Crop Health Monitoring & Disease Detection
  • Smart Greenhouses
  • Weather Forecasting
  • Fish Farming / Aquaculture
  • Soil Monitoring
  • Irrigation Management
  • Supply Chain & Market Access Optimization
  • Other Applications

End Users Covered:

  • Individual Farmers
  • Agricultural Cooperatives
  • Research Institutes & Universities
  • Government Agencies
  • Agribusinesses
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Smart Farming Market by IoT & AI, By Component

  • 5.1 Introduction
  • 5.2 Hardware
    • 5.2.1 Sensors
    • 5.2.2 Drones & UAVs
    • 5.2.3 Control Systems
    • 5.2.4 GPS/GNSS Devices
    • 5.2.5 Robotics & Automation Tools
    • 5.2.6 Displays and Handheld Computers
    • 5.2.7 Smart Cameras
  • 5.3 Software
    • 5.3.1 AI Algorithms & Machine Learning Platforms
    • 5.3.2 Cloud-based Analytics Platforms
    • 5.3.3 Predictive Analytics Tools
    • 5.3.4 GIS & Remote Sensing Software
    • 5.3.5 Farm Management Software (FMS)
  • 5.4 Services
    • 5.4.1 System Integration
    • 5.4.2 Data Analytics Services
    • 5.4.3 Maintenance & Support
    • 5.4.4 Managed Services
    • 5.4.5 Connectivity Services

6 Global Smart Farming Market by IoT & AI, By Farm Size

  • 6.1 Introduction
  • 6.2 Small Farms
  • 6.3 Medium-Sized Farms
  • 6.4 Large-Scale Farms

7 Global Smart Farming Market by IoT & AI, By Deployment Model

  • 7.1 Introduction
  • 7.2 On-Premise
  • 7.3 Cloud-Based

8 Global Smart Farming Market by IoT & AI, By Application

  • 8.1 Introduction
  • 8.2 Precision Farming
  • 8.3 Automated Harvesting & Seeding
  • 8.4 Livestock Monitoring
  • 8.5 Crop Health Monitoring & Disease Detection
  • 8.6 Smart Greenhouses
  • 8.7 Weather Forecasting
  • 8.8 Fish Farming / Aquaculture
  • 8.9 Soil Monitoring
  • 8.10 Irrigation Management
  • 8.11 Supply Chain & Market Access Optimization
  • 8.12 Other Applications

9 Global Smart Farming Market by IoT & AI, By End User

  • 9.1 Introduction
  • 9.2 Individual Farmers
  • 9.3 Agricultural Cooperatives
  • 9.4 Research Institutes & Universities
  • 9.5 Government Agencies
  • 9.6 Agribusinesses
  • 9.7 Other End Users

10 Global Smart Farming Market by IoT & AI, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 Deere & Company
  • 12.2 Ag Leader Technology
  • 12.3 Trimble Inc.
  • 12.4 Arugga
  • 12.5 AGCO Corporation
  • 12.6 FarmWise
  • 12.7 Topcon Corporation
  • 12.8 Small Robot Company
  • 12.9 CropIn Technology Solutions Pvt. Ltd.
  • 12.10 Intello Labs Pvt Ltd
  • 12.11 DeHaat
  • 12.12 Stellapps
  • 12.13 Fasal
  • 12.14 BouMatic Robotic B.V.
  • 12.15 Raven Industries, Inc.

List of Tables

  • Table 1 Global Smart Farming Market by IoT & AI Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Smart Farming Market by IoT & AI Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global Smart Farming Market by IoT & AI Outlook, By Hardware (2024-2032) ($MN)
  • Table 4 Global Smart Farming Market by IoT & AI Outlook, By Sensors (2024-2032) ($MN)
  • Table 5 Global Smart Farming Market by IoT & AI Outlook, By Drones & UAVs (2024-2032) ($MN)
  • Table 6 Global Smart Farming Market by IoT & AI Outlook, By Control Systems (2024-2032) ($MN)
  • Table 7 Global Smart Farming Market by IoT & AI Outlook, By GPS/GNSS Devices (2024-2032) ($MN)
  • Table 8 Global Smart Farming Market by IoT & AI Outlook, By Robotics & Automation Tools (2024-2032) ($MN)
  • Table 9 Global Smart Farming Market by IoT & AI Outlook, By Displays and Handheld Computers (2024-2032) ($MN)
  • Table 10 Global Smart Farming Market by IoT & AI Outlook, By Smart Cameras (2024-2032) ($MN)
  • Table 11 Global Smart Farming Market by IoT & AI Outlook, By Software (2024-2032) ($MN)
  • Table 12 Global Smart Farming Market by IoT & AI Outlook, By AI Algorithms & Machine Learning Platforms (2024-2032) ($MN)
  • Table 13 Global Smart Farming Market by IoT & AI Outlook, By Cloud-based Analytics Platforms (2024-2032) ($MN)
  • Table 14 Global Smart Farming Market by IoT & AI Outlook, By Predictive Analytics Tools (2024-2032) ($MN)
  • Table 15 Global Smart Farming Market by IoT & AI Outlook, By GIS & Remote Sensing Software (2024-2032) ($MN)
  • Table 16 Global Smart Farming Market by IoT & AI Outlook, By Farm Management Software (FMS) (2024-2032) ($MN)
  • Table 17 Global Smart Farming Market by IoT & AI Outlook, By Services (2024-2032) ($MN)
  • Table 18 Global Smart Farming Market by IoT & AI Outlook, By System Integration (2024-2032) ($MN)
  • Table 19 Global Smart Farming Market by IoT & AI Outlook, By Data Analytics Services (2024-2032) ($MN)
  • Table 20 Global Smart Farming Market by IoT & AI Outlook, By Maintenance & Support (2024-2032) ($MN)
  • Table 21 Global Smart Farming Market by IoT & AI Outlook, By Managed Services (2024-2032) ($MN)
  • Table 22 Global Smart Farming Market by IoT & AI Outlook, By Connectivity Services (2024-2032) ($MN)
  • Table 23 Global Smart Farming Market by IoT & AI Outlook, By Farm Size (2024-2032) ($MN)
  • Table 24 Global Smart Farming Market by IoT & AI Outlook, By Small Farms (2024-2032) ($MN)
  • Table 25 Global Smart Farming Market by IoT & AI Outlook, By Medium-Sized Farms (2024-2032) ($MN)
  • Table 26 Global Smart Farming Market by IoT & AI Outlook, By Large-Scale Farms (2024-2032) ($MN)
  • Table 27 Global Smart Farming Market by IoT & AI Outlook, By Deployment Model (2024-2032) ($MN)
  • Table 28 Global Smart Farming Market by IoT & AI Outlook, By On-Premise (2024-2032) ($MN)
  • Table 29 Global Smart Farming Market by IoT & AI Outlook, By Cloud-Based (2024-2032) ($MN)
  • Table 30 Global Smart Farming Market by IoT & AI Outlook, By Application (2024-2032) ($MN)
  • Table 31 Global Smart Farming Market by IoT & AI Outlook, By Precision Farming (2024-2032) ($MN)
  • Table 32 Global Smart Farming Market by IoT & AI Outlook, By Automated Harvesting & Seeding (2024-2032) ($MN)
  • Table 33 Global Smart Farming Market by IoT & AI Outlook, By Livestock Monitoring (2024-2032) ($MN)
  • Table 34 Global Smart Farming Market by IoT & AI Outlook, By Crop Health Monitoring & Disease Detection (2024-2032) ($MN)
  • Table 35 Global Smart Farming Market by IoT & AI Outlook, By Smart Greenhouses (2024-2032) ($MN)
  • Table 36 Global Smart Farming Market by IoT & AI Outlook, By Weather Forecasting (2024-2032) ($MN)
  • Table 37 Global Smart Farming Market by IoT & AI Outlook, By Fish Farming / Aquaculture (2024-2032) ($MN)
  • Table 38 Global Smart Farming Market by IoT & AI Outlook, By Soil Monitoring (2024-2032) ($MN)
  • Table 39 Global Smart Farming Market by IoT & AI Outlook, By Irrigation Management (2024-2032) ($MN)
  • Table 40 Global Smart Farming Market by IoT & AI Outlook, By Supply Chain & Market Access Optimization (2024-2032) ($MN)
  • Table 41 Global Smart Farming Market by IoT & AI Outlook, By Other Applications (2024-2032) ($MN)
  • Table 42 Global Smart Farming Market by IoT & AI Outlook, By End User (2024-2032) ($MN)
  • Table 43 Global Smart Farming Market by IoT & AI Outlook, By Individual Farmers (2024-2032) ($MN)
  • Table 44 Global Smart Farming Market by IoT & AI Outlook, By Agricultural Cooperatives (2024-2032) ($MN)
  • Table 45 Global Smart Farming Market by IoT & AI Outlook, By Research Institutes & Universities (2024-2032) ($MN)
  • Table 46 Global Smart Farming Market by IoT & AI Outlook, By Government Agencies (2024-2032) ($MN)
  • Table 47 Global Smart Farming Market by IoT & AI Outlook, By Agribusinesses (2024-2032) ($MN)
  • Table 48 Global Smart Farming Market by IoT & AI Outlook, By Other End Users (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.