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市场调查报告书
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1776746

物联网和人工智慧智慧农业市场预测至 2032 年：按组件、农场规模、部署模式、应用、最终用户和地区进行的全球分析

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个工作天内

价格

根据 Stratistics MRC 的数据，全球物联网和人工智慧智慧农业市场预计在 2025 年达到 241.8 亿美元，到 2032 年将达到 551.6 亿美元，预测期内的复合年增长率为 12.5%。

智慧农业利用物联网、人工智慧、机器人和巨量资料等先进技术来提高农业生产力、效率和永续性。智慧农业能够实现精密农业实践，例如即时监测、数据主导决策以及优化灌溉、施肥和病虫害防治。透过整合数位工具，智慧农业可以帮助农民减少资源消耗、降低成本、提高作物产量，同时最大限度地减少对环境的影响并适应不断变化的气候条件。

根据美国环保署（EPA）的报告，精密农业可减少用水量高达30%，并提高作物产量20%。

全球粮食需求不断成长

智慧农业技术正在成为提高生产力和永续性的关键解决方案。精密农业工具，例如物联网感测器、人工智慧主导的分析和GPS导航设备，使农民能够优化投入并最大限度地提高产量。这些创新有助于减少废弃物、节约用水并改善土壤健康，从而解决粮食安全和环境问题。各国政府和私相关人员正在加大对农业技术的投资，以满足未来的粮食需求。因此，智能农业正成为全球现代农业策略的基石。

资料隐私和安全问题

数位科技与农业的融合引发了人们对资料隐私和网路安全的担忧。农民和相关企业会产生大量敏感数据，包括作物生长、土壤条件和专有耕作方法等资讯。如果没有强大的安全通讯协定，这些资料很容易遭到洩漏、滥用和未授权存取。尤其是中小型农场，可能缺乏实施先进网路安全措施的资源。这些担忧可能会减缓智慧农业技术的普及，尤其是在数位基础设施有限的地区。

农业供应链中的区块链整合

区块链技术为提升农业供应链的透明度和可追溯性提供了变革潜力。透过在分散式帐本上记录所有交易和商品流动，区块链可确保资料完整性并减少诈欺。智慧支付可以实现支付和物流自动化，提高效率并减少纠纷。随着消费者要求食品采购更加课责，区块链在生产商和零售商中的应用日益增加。区块链与物联网和人工智慧的整合有望将农业商业业务的信任度和效率提升到新的水平。

标准化和互通性问题

智慧农业生态系统由来自不同供应商的硬体、软体和数据平台组成。主要挑战在于这些系统之间缺乏标准化和互通性。不相容的技术阻碍了数据的无缝交换和集成，从而限制了精密农业的有效性。农民往往难以同步设备和平台，导致效率低下和成本增加。这种碎片化也阻碍了对新技术的投资，尤其是对小农户而言。

COVID-19的影响

新冠疫情加速了智慧农业技术的普及，因为劳动力短缺和供应链中断暴露了传统农业的脆弱性。农民转向自动化、远端监控和数据主导的决策，以便在受限条件下维持生产力。无人机、自动驾驶拖拉机和基于感测器的灌溉系统成为流行的非接触式解决方案。这场危机也凸显了韧性和在地化食品体系的重要性，激发了人们对垂直农业和智慧温室的兴趣。疫情引发了农业科技格局的长期结构性转变。

预计软体领域将成为预测期内最大的领域

软体领域预计将在预测期内占据最大的市场占有率，这得益于其在数据分析、决策支援和农场管理方面的核心作用。先进的平台能够即时监测作物健康状况、天气模式和设备性能。云端基础的解决方案提供扩充性和远端存取功能，使其成为大规模分散式农业运营的理想选择。与人工智慧和机器学习的整合增强了预测能力，使农民能够主动管理风险。

预计智慧温室领域将在预测期内见证最高的复合年增长率。

预计智慧温室领域将在预测期内实现最高成长率。这些系统利用物联网感测器、气候控制技术和人工智慧演算法来优化温度、湿度和光照，从而提高作物产量，减少资源消费量，并最大限度地减少农药使用。都市化和垂直农业的兴起进一步推动了对智慧温室解决方案的需求。

占比最大的地区：

预计亚太地区将在预测期内占据最大的市场占有率，这得益于其庞大的农业基础和快速的技术应用。中国、印度和日本等国家正大力投资农业技术，以提高生产力并确保粮食安全。智慧型手机和价格实惠的物联网设备的日益普及，甚至使小农户也能参与数位革命。市场参与企业为推动数位农业和农村互联互通所做的努力，正在推动市场成长。

复合年增长率最高的地区：

在预测期内，北美预计将实现最高的复合年增长率，这得益于其先进的基础设施和精密农业的早期应用。美国和加拿大拥有主要的农业科技公司和研究机构，推动技术创新。该地区的农民越来越多地采用人工智慧、机器人技术和数据分析来提高效率和永续性。政府透过补贴和气候智慧型农业计画提供的支持进一步推动了成长。

提供免费客製化：

订阅此报告的客户可享有以下免费自订选项之一：

  • 公司简介
    • 对最多三家其他市场公司进行全面分析
    • 主要企业的SWOT分析（最多3家公司）
  • 区域细分
    • 根据客户兴趣对主要国家进行的市场估计、预测和复合年增长率（註：基于可行性检查）
  • 竞争基准化分析
    • 根据产品系列、地理分布和策略联盟对主要企业基准化分析

目录

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 调查范围
  • 调查方法
    • 资料探勘
    • 数据分析
    • 数据检验
    • 研究途径
  • 研究材料
    • 主要研究资料
    • 次级研究资讯来源
    • 先决条件

第三章市场走势分析

  • 驱动程式
  • 抑制因素
  • 机会
  • 威胁
  • 应用分析
  • 最终用户分析
  • 新兴市场
  • COVID-19的影响

第四章 波特五力分析

  • 供应商的议价能力
  • 买家的议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

第五章全球物联网与人工智慧智慧农业市场（按组成部分）

  • 硬体
    • 感应器
    • 无人机和无人驾驶飞行器
    • 控制系统
    • GPS/GNSS设备
    • 机器人和自动化工具
    • 显示器和手持电脑
    • 智慧型相机
  • 软体
    • 人工智慧演算法和机器学习平台
    • 云端基础的分析平台
    • 预测分析工具
    • GIS 和遥感探测软体
    • 农场管理软体（FMS）
  • 服务
    • 系统整合
    • 数据分析服务
    • 维护和支援
    • 託管服务
    • 连线服务

第六章 全球物联网与人工智慧智慧农业市场（依农场规模）

  • 小型农场
  • 中型农场
  • 大型农场

第七章全球物联网与人工智慧智慧农业市场（按部署模式）

  • 本地
  • 云端基础

第八章全球物联网与人工智慧智慧农业市场（按应用）

  • 精密农业
  • 自动收割和播种
  • 牲畜监控
  • 作物健康监测和疾病检测
  • 智慧温室
  • 天气预报
  • 水产养殖
  • 土壤监测
  • 灌溉管理
  • 优化供应炼和市场进入
  • 其他用途

第九章全球物联网和人工智慧智慧农业市场（按最终用户）

  • 私人农场主
  • 农业合作社
  • 科学研究机构和大学
  • 政府
  • 农业业务
  • 其他最终用户

第 10 章全球物联网与人工智慧智慧农业市场（按地区）

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲国家
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 其他亚太地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地区
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十一章 重大进展

  • 协议、伙伴关係、合作和合资企业
  • 收购与合併
  • 新产品发布
  • 业务扩展
  • 其他关键策略

第十二章 公司概况

  • 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.