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市場調查報告書
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2102404

智慧灌溉分析市場：預測至 2034 年 - 按組件、分析類型、應用、最終用戶和地區分類的全球分析

Smart Irrigation Analytics Market Forecasts to 2034 - Global Analysis By Component (Software, Sensors, Controllers, Communication Devices, Cloud Platforms, Services and Mobile Applications), Analytics Type, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，預計到 2026 年，全球智慧灌溉分析市場規模將達到 8 億美元，並在預測期內以 25.3% 的複合年成長率成長，到 2034 年將達到 31 億美元。

智慧灌溉分析是指利用數據驅動的軟體解決方案和演算法平台，分析土壤濕度、天氣模式、作物需水量和灌溉系統性能，從而最佳化農業和園林綠化用水。這些分析平台整合了感測器網路、衛星影像、機器學習模型和預測演算法，產生可操作的灌溉建議，最大限度地提高作物產量和質量，同時最大限度地減少水資源浪費。智慧灌溉分析包括即時監控儀錶板、需水量預測、自動灌溉調度以及能夠適應不斷變化的環境條件和作物生長階段的指導性建議。

水資源短缺日益加劇

隨著全球水資源短缺日益加劇，農業用水面臨越來越多的監管和環境限制，智慧灌溉分析技術的應用正在加速。聯合國估計，2030年，全球用水需求將超過供應量40%，其中農業用水約佔全球淡水消耗量的70%。透過利用精準灌溉分析技術，農民可以透過數據驅動的最佳化灌溉計劃，在維持或提高作物產量的同時，減少20%至40%的灌溉用水量。政府在缺水地區的節水義務和農業補貼計劃，正在推動政策主導的對利用分析技術進行灌溉管理的需求。此外，整個食品飲料供應鏈的企業永續性措施也要求供應商透過分析檢驗的灌溉效率提升，來證明其在水資源管理方面的績效。

高昂的實施成本

智慧灌溉分析市場面臨巨大的推廣障礙，這主要是由於部署感測器、連接基礎設施以及訂閱分析平台等全面灌溉最佳化所需的前期成本高昂。佔全球農民絕大多數的中小農業企業往往缺乏資金投資物聯網感測器網路和雲端分析平台。將分析平台與現有灌溉硬體和農場管理系統整合也增加了部署成本和技術挑戰。不同作物類型、氣候帶和農場規模的投資回收期各不相同，這使得生產者難以證明投資分析工具的合理性。此外，農村農業地區寬頻連線有限，限制了分析平台發揮最佳效能所需的即時資料傳輸能力。

人工智慧驅動的預測分析

將人工智慧 (AI) 和機器學習與智慧灌溉分析相結合，為預測性水資源管理創造了巨大機遇，使其從被動監測轉向主動最佳化。人工智慧驅動的分析平台能夠將天氣預報、土壤濕度趨勢和作物生長模型整合到統一的預測框架中，從而提前數天預測作物需水量。基於歷史灌溉和產量資料訓練的機器學習演算法不斷提高建議的準確性，使平台能夠提供更精準的灌溉指導，並根據具體的田間條件進行調整。灌溉分析與精密農業平台的融合，為能夠同時最佳化水、肥料和能源投入的綜合農場管理解決方案創造了機會。隨著市場的成熟，這些人工智慧功能將推動平台差異化和客戶留存。

氣候變遷帶來的挑戰

智慧灌溉分析市場面臨許多挑戰，包括氣候變遷加劇和極端天氣事件增多，這些都威脅預測模型的準確性和感測器網路的可靠性。前所未有的乾旱、山洪爆發和極端溫度波動正在造成農業環境變化，而這些變化並未包含在用於訓練灌溉分析演算法的歷史資料模式中。感測器網路易受極端天氣事件、農機運作和野生動物干擾的影響，造成數據缺口，降低分析的準確性。與氣候變遷相關的新型作物病蟲害的出現，引入了灌溉分析平台可能無法充分應對的額外變數。這些與氣候相關的挑戰會削弱客戶對分析建議的信心，並可能延緩風險規避型農業管理中對這些建議的採納。

新型冠狀病毒（COVID-19）的影響：

新冠疫情導致農業價值鏈人手不足，經濟的不確定性迫使農民推遲技術投資，阻礙了智慧灌溉分析技術的應用。然而，旅行限制使得現場訪問和技術支援活動難以開展，凸顯了遠端監控能力的重要性。疫情後，主要農業經濟體的政府推出了一系列經濟措施，其中包括對精密農業和節水技術的激勵措施，加速了分析平台的普及應用。這項經驗再次印證了自動化、數據驅動型灌溉管理的重要性，它能夠減少對人工和現場專業知識的依賴。

在預測期內，軟體領域預計將佔據最大的市場佔有率。

在預測期內，軟體領域預計將佔據最大的市場佔有率。這是因為分析軟體在處理感測器數據、產生灌溉建議以及為農場管理者提供決策儀錶板方面發揮核心作用。灌溉分析軟體平台整合了來自多種資訊來源的數據，包括土壤濕度感測器、氣象站、衛星影像和作物模型，從而提供全面的水資源管理洞察。這些軟體解決方案擴大採用基於訂閱的SaaS模式，從而實現持續更新、雲端擴充性以及從多個裝置遠端存取。

預計在預測期內，預測分析領域將呈現最高的複合年成長率。

在預測期內，預測分析領域預計將呈現最高的成長率，這主要得益於人們對灌溉資訊的需求不斷成長，從而能夠進行主動式水資源管理，而非被動地應對當前狀況。預測分析平台利用機器學習演算法、天氣預報模型和歷史作物產量數據來預測未來的用水需求，並提前最佳化灌溉計畫。這些功能對於管理跨多個田地和多種作物的大規模商業農業企業而言尤其重要，因為它們需要維護大規模的灌溉基礎設施。

市佔率最大的地區：

在預測期內，北美地區預計將佔據最大的市場佔有率，這主要得益於美國和加拿大對先進農業技術的廣泛應用、完善的精密農業基礎設施以及強力的節水政策。美國是全球智慧灌溉系統應用領域的領導者，其中加州、德克薩斯州和中西部地區是關鍵市場。在這些地區，水資源短缺和人事費用上升正在推動對分析平台的需求。在加拿大農業領域，為應對氣候變遷和主要農業省份的水資源管理法規，精準灌溉技術的應用正在增加。領先的智慧灌溉分析服務供應商，例如 Toro 公司、Rain Bird 公司和 Lindsay 公司，其總部均設在北美，並擁有廣泛的銷售網路。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率，這主要得益於中國、印度和澳洲農業的快速現代化、政府主導的水資源保護工作以及精密農業技術的廣泛應用。中國的國家水資源管理政策要求提高全部區域的灌溉效率，從而對能夠最佳化大規模用水的分析平台產生了顯著需求。印度的「總理農業灌溉計畫」（Pradhan Mantri Krishi Sinchayee Yojana）和各邦的微灌計畫為小規模農戶採用智慧灌溉技術提供補貼。澳洲墨累-達令河流域的水資源管理改革推動了對精準灌溉分析工具的需求，這些工具能夠在遵守用水配額限制的同時，維持農業生產力。

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目錄

第1章執行摘要

  • 市場概覽及主要亮點
  • 促進因素、挑戰與機遇
  • 競爭格局概述
  • 戰略洞察與建議

第2章：研究框架

  • 研究目標和範圍
  • 相關人員分析
  • 研究假設和限制
  • 調查方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 技術與創新展望
  • 新興市場/高成長市場
  • 監管和政策環境
  • 新冠疫情的影響及復甦前景

第4章：競爭環境與策略評估

  • 波特五力分析
    • 供應商的議價能力
    • 買方的議價能力
    • 替代品的威脅
    • 新進入者的威脅
    • 競爭公司之間的競爭
  • 主要公司市佔率分析
  • 產品基準評效和效能比較

第5章 全球智慧灌溉分析市場：按組件分類

  • 軟體
  • 感應器
  • 控制器
  • 通訊設備
  • 雲端平台
  • 服務
  • 行動應用

第6章：全球智慧灌溉分析市場：依分析類型分類

  • 預測分析
  • 指示性分析
  • 即時分析
  • 天氣分析
  • 用水量分析
  • 作物分析

第7章 全球智慧灌溉分析市場：依應用分類

  • 田間作物
  • 果園
  • 溫室
  • 草坪和景觀美化
  • 葡萄園
  • 高爾夫球場
  • 園藝

第8章 全球智慧灌溉分析市場：依最終用戶分類

  • 商業農場
  • 溫室經營者
  • 地方政府
  • 園林綠化公司
  • 高爾夫球場
  • 研究機構

第9章 全球智慧灌溉分析市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 世界其他地區（RoW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第10章 戰略市場資訊

  • 工業價值網路和供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第11章 產業趨勢與策略舉措

  • 併購
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第12章：公司簡介

  • The Toro Company
  • Rain Bird Corporation
  • Hunter Industries
  • Netafim Ltd.
  • Lindsay Corporation
  • Jain Irrigation Systems Ltd.
  • Valmont Industries, Inc.
  • HydroPoint Data Systems
  • Rachio Inc.
  • CropX Technologies Ltd.
  • Trimble Inc.
  • John Deere
  • Weathermatic
  • Orbit Irrigation
  • Galcon Ltd.
  • OpenET
  • Moisture Meter Company
Product Code: SMRC38296

According to Stratistics MRC, the Global Smart Irrigation Analytics Market is accounted for $0.8 billion in 2026 and is expected to reach $3.1 billion by 2034 growing at a CAGR of 25.3% during the forecast period. Smart irrigation analytics refer to data-driven software solutions and algorithmic platforms that analyze soil moisture, weather patterns, crop water requirements, and irrigation system performance to optimize water application in agricultural and landscape settings. These analytics platforms integrate sensor networks, satellite imagery, machine learning models, and predictive algorithms to generate actionable irrigation recommendations that minimize water waste while maximizing crop yield and quality. Smart irrigation analytics encompass real-time monitoring dashboards, predictive water demand forecasting, automated irrigation scheduling, and prescriptive recommendations that adapt to changing environmental conditions and crop growth stages.

Market Dynamics:

Driver:

Water scarcity intensification

Smart irrigation analytics are experiencing accelerated adoption as global water scarcity intensifies and agricultural water consumption faces increasing regulatory and environmental constraints. The United Nations estimates that water demand will exceed supply by forty percent by 2030, with agriculture accounting for approximately seventy percent of global freshwater withdrawals. Precision irrigation analytics enable farmers to reduce water application volumes by twenty to forty percent while maintaining or improving crop yields through data-optimized scheduling. Government water conservation mandates and agricultural subsidy programs in water-stressed regions are creating policy-driven demand for analytics-enabled irrigation management. Corporate sustainability commitments across food and beverage supply chains are requiring suppliers to demonstrate water stewardship through analytics-verified irrigation efficiency improvements.

Restraint:

High implementation costs

The smart irrigation analytics market faces significant adoption barriers from the high upfront costs associated with sensor deployment, connectivity infrastructure, and analytics platform subscriptions required for comprehensive irrigation optimization. Small and medium-sized farming operations, which represent the majority of global agricultural producers, frequently lack the capital resources to invest in IoT sensor networks and cloud-based analytics platforms. The complexity of integrating analytics platforms with existing irrigation hardware and farm management systems creates additional implementation costs and technical challenges. Variable return on investment timelines across different crop types, climate zones, and farm scales make it difficult for producers to justify analytics investments. Limited broadband connectivity in rural agricultural regions constrains the real-time data transmission capabilities that analytics platforms require for optimal performance.

Opportunity:

AI-powered predictive analytics

The integration of artificial intelligence and machine learning with smart irrigation analytics is creating substantial opportunities for predictive water management that extends beyond reactive monitoring to anticipatory optimization. AI-driven analytics platforms can forecast crop water requirements days in advance by integrating weather predictions, soil moisture trends, and crop growth models into unified predictive frameworks. Machine learning algorithms trained on historical irrigation and yield data continuously improve recommendation accuracy, enabling platforms to deliver increasingly precise water application guidance tailored to specific field conditions. The convergence of irrigation analytics with precision agriculture platforms creates opportunities for unified farm management solutions that optimize water, fertilizer, and energy inputs simultaneously. These AI capabilities will drive platform differentiation and customer retention as the market matures.

Threat:

Climate variability challenges

The smart irrigation analytics market faces significant threats from increasing climate variability and extreme weather events that challenge the accuracy of predictive models and the reliability of sensor networks. Unprecedented drought conditions, flash flooding, and temperature extremes are creating agricultural conditions that fall outside historical data patterns used to train irrigation analytics algorithms. Sensor networks are vulnerable to damage from severe weather events, field equipment operations, and wildlife interference, creating data gaps that compromise analytics accuracy. The emergence of novel crop diseases and pest pressures associated with changing climate patterns introduces additional variables that irrigation analytics platforms may not adequately address. These climate-related challenges threaten customer confidence in analytics recommendations and may slow adoption among risk-averse farming operations.

Covid-19 Impact:

The COVID-19 pandemic disrupted smart irrigation analytics adoption as agricultural supply chains faced labor shortages and farmers deferred technology investments amid economic uncertainty. However, the crisis highlighted the value of remote monitoring capabilities as travel restrictions prevented in-person field visits and technical support activities. Post-pandemic, government stimulus packages in major agricultural economies included precision agriculture and water conservation technology incentives that accelerated analytics platform deployments. The experience reinforced the importance of automated, data-driven irrigation management that reduces dependency on manual labor and on-site expertise.

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 the central role that analytics software plays in processing sensor data, generating irrigation recommendations, and providing decision support dashboards for farm operators. Irrigation analytics software platforms integrate data from diverse sources, including soil moisture sensors, weather stations, satellite imagery, and crop models, to deliver comprehensive water management insights. These software solutions are increasingly offered through subscription-based SaaS models that provide continuous updates, cloud scalability, and remote accessibility across multiple devices.

The predictive analytics segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the predictive analytics segment is predicted to witness the highest growth rate, driven by the increasing demand for forward-looking irrigation insights that enable proactive water management rather than reactive responses to current conditions. Predictive analytics platforms leverage machine learning algorithms, weather forecasting models, and historical crop performance data to anticipate future water requirements and optimize irrigation schedules in advance. These capabilities are particularly valuable for large-scale commercial farming operations managing extensive irrigation infrastructure across multiple fields and crop varieties.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, due to advanced agricultural technology adoption, extensive precision farming infrastructure, and strong water conservation policies across the United States and Canada. The United States leads global adoption of smart irrigation systems, with California, Texas, and the Midwest representing major markets where water scarcity and labor costs drive analytics platform demand. Canada's agricultural sector is increasingly adopting precision irrigation technologies in response to climate variability and water management regulations in major farming provinces. Major smart irrigation analytics providers, including The Toro Company, Rain Bird Corporation, and Lindsay Corporation, are headquartered in North America and maintain extensive distribution networks.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, due to rapid agricultural modernization, government-led water conservation initiatives, and expanding adoption of precision farming technologies across China, India, and Australia. China's national water resource management policies are mandating irrigation efficiency improvements across major agricultural regions, creating substantial demand for analytics platforms that can optimize water application at scale. India's Pradhan Mantri Krishi Sinchayee Yojana and state-level micro-irrigation programs are subsidizing smart irrigation technology adoption among smallholder farmers. Australia's Murray-Darling Basin water management reforms are driving demand for precision irrigation analytics that enable compliance with water allocation limits while maintaining agricultural productivity.

Key players in the market

Some of the key players in Smart Irrigation Analytics Market include The Toro Company, Rain Bird Corporation, Hunter Industries, Netafim Ltd., Lindsay Corporation, Jain Irrigation Systems Ltd., Valmont Industries, Inc., HydroPoint Data Systems, Rachio Inc., CropX Technologies Ltd., Trimble Inc., John Deere, Weathermatic, Orbit Irrigation, Galcon Ltd., OpenET, and Moisture Meter Company.

Key Developments:

In June 2026, The Toro Company launched an AI-powered irrigation analytics platform integrating real-time soil moisture and weather data to optimize water application across golf course and agricultural installations with predictive scheduling capabilities.

In May 2026, Rain Bird Corporation introduced an advanced cloud-based analytics dashboard for commercial agriculture, enabling multi-field irrigation optimization through machine learning algorithms trained on historical yield and water usage patterns.

In April 2026, Netafim Ltd. expanded its precision irrigation analytics suite with satellite-based crop water stress monitoring, allowing growers to adjust drip irrigation schedules remotely through a unified mobile application interface.

Components Covered:

  • Software
  • Sensors
  • Controllers
  • Communication Devices
  • Cloud Platforms
  • Services
  • Mobile Applications

Analytics Types Covered:

  • Predictive Analytics
  • Prescriptive Analytics
  • Real-Time Analytics
  • Weather Analytics
  • Water Usage Analytics
  • Crop Analytics

Applications Covered:

  • Field Crops
  • Orchards
  • Greenhouses
  • Turf & Landscape
  • Vineyards
  • Golf Courses
  • Horticulture

End Users Covered:

  • Commercial Farms
  • Greenhouse Operators
  • Municipal Authorities
  • Landscape Companies
  • Golf Courses
  • Research Organizations

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of 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 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
  • 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

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global Smart Irrigation Analytics Market, By Component

  • 5.1 Software
  • 5.2 Sensors
  • 5.3 Controllers
  • 5.4 Communication Devices
  • 5.5 Cloud Platforms
  • 5.6 Services
  • 5.7 Mobile Applications

6 Global Smart Irrigation Analytics Market, By Analytics Type

  • 6.1 Predictive Analytics
  • 6.2 Prescriptive Analytics
  • 6.3 Real-Time Analytics
  • 6.4 Weather Analytics
  • 6.5 Water Usage Analytics
  • 6.6 Crop Analytics

7 Global Smart Irrigation Analytics Market, By Application

  • 7.1 Field Crops
  • 7.2 Orchards
  • 7.3 Greenhouses
  • 7.4 Turf & Landscape
  • 7.5 Vineyards
  • 7.6 Golf Courses
  • 7.7 Horticulture

8 Global Smart Irrigation Analytics Market, By End User

  • 8.1 Commercial Farms
  • 8.2 Greenhouse Operators
  • 8.3 Municipal Authorities
  • 8.4 Landscape Companies
  • 8.5 Golf Courses
  • 8.6 Research Organizations

9 Global Smart Irrigation Analytics Market, By Geography

  • 9.1 North America
    • 9.1.1 United States
    • 9.1.2 Canada
    • 9.1.3 Mexico
  • 9.2 Europe
    • 9.2.1 United Kingdom
    • 9.2.2 Germany
    • 9.2.3 France
    • 9.2.4 Italy
    • 9.2.5 Spain
    • 9.2.6 Netherlands
    • 9.2.7 Belgium
    • 9.2.8 Sweden
    • 9.2.9 Switzerland
    • 9.2.10 Poland
    • 9.2.11 Rest of Europe
  • 9.3 Asia Pacific
    • 9.3.1 China
    • 9.3.2 Japan
    • 9.3.3 India
    • 9.3.4 South Korea
    • 9.3.5 Australia
    • 9.3.6 Indonesia
    • 9.3.7 Thailand
    • 9.3.8 Malaysia
    • 9.3.9 Singapore
    • 9.3.10 Vietnam
    • 9.3.11 Rest of Asia Pacific
  • 9.4 South America
    • 9.4.1 Brazil
    • 9.4.2 Argentina
    • 9.4.3 Colombia
    • 9.4.4 Chile
    • 9.4.5 Peru
    • 9.4.6 Rest of South America
  • 9.5 Rest of the World (RoW)
    • 9.5.1 Middle East
      • 9.5.1.1 Saudi Arabia
      • 9.5.1.2 United Arab Emirates
      • 9.5.1.3 Qatar
      • 9.5.1.4 Israel
      • 9.5.1.5 Rest of Middle East
    • 9.5.2 Africa
      • 9.5.2.1 South Africa
      • 9.5.2.2 Egypt
      • 9.5.2.3 Morocco
      • 9.5.2.4 Rest of Africa

10 Strategic Market Intelligence

  • 10.1 Industry Value Network and Supply Chain Assessment
  • 10.2 White-Space and Opportunity Mapping
  • 10.3 Product Evolution and Market Life Cycle Analysis
  • 10.4 Channel, Distributor, and Go-to-Market Assessment

11 Industry Developments and Strategic Initiatives

  • 11.1 Mergers and Acquisitions
  • 11.2 Partnerships, Alliances, and Joint Ventures
  • 11.3 New Product Launches and Certifications
  • 11.4 Capacity Expansion and Investments
  • 11.5 Other Strategic Initiatives

12 Company Profiles

  • 12.1 The Toro Company
  • 12.2 Rain Bird Corporation
  • 12.3 Hunter Industries
  • 12.4 Netafim Ltd.
  • 12.5 Lindsay Corporation
  • 12.6 Jain Irrigation Systems Ltd.
  • 12.7 Valmont Industries, Inc.
  • 12.8 HydroPoint Data Systems
  • 12.9 Rachio Inc.
  • 12.10 CropX Technologies Ltd.
  • 12.11 Trimble Inc.
  • 12.12 John Deere
  • 12.13 Weathermatic
  • 12.14 Orbit Irrigation
  • 12.15 Galcon Ltd.
  • 12.16 OpenET
  • 12.17 Moisture Meter Company

List of Tables

  • Table 1 Global Smart Irrigation Analytics Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global Smart Irrigation Analytics Market Outlook, By Component (2023-2034) ($MN)
  • Table 3 Global Smart Irrigation Analytics Market Outlook, By Software (2023-2034) ($MN)
  • Table 4 Global Smart Irrigation Analytics Market Outlook, By Sensors (2023-2034) ($MN)
  • Table 5 Global Smart Irrigation Analytics Market Outlook, By Controllers (2023-2034) ($MN)
  • Table 6 Global Smart Irrigation Analytics Market Outlook, By Communication Devices (2023-2034) ($MN)
  • Table 7 Global Smart Irrigation Analytics Market Outlook, By Cloud Platforms (2023-2034) ($MN)
  • Table 8 Global Smart Irrigation Analytics Market Outlook, By Services (2023-2034) ($MN)
  • Table 9 Global Smart Irrigation Analytics Market Outlook, By Mobile Applications (2023-2034) ($MN)
  • Table 10 Global Smart Irrigation Analytics Market Outlook, By Analytics Type (2023-2034) ($MN)
  • Table 11 Global Smart Irrigation Analytics Market Outlook, By Predictive Analytics (2023-2034) ($MN)
  • Table 12 Global Smart Irrigation Analytics Market Outlook, By Prescriptive Analytics (2023-2034) ($MN)
  • Table 13 Global Smart Irrigation Analytics Market Outlook, By Real-Time Analytics (2023-2034) ($MN)
  • Table 14 Global Smart Irrigation Analytics Market Outlook, By Weather Analytics (2023-2034) ($MN)
  • Table 15 Global Smart Irrigation Analytics Market Outlook, By Water Usage Analytics (2023-2034) ($MN)
  • Table 16 Global Smart Irrigation Analytics Market Outlook, By Crop Analytics (2023-2034) ($MN)
  • Table 17 Global Smart Irrigation Analytics Market Outlook, By Application (2023-2034) ($MN)
  • Table 18 Global Smart Irrigation Analytics Market Outlook, By Field Crops (2023-2034) ($MN)
  • Table 19 Global Smart Irrigation Analytics Market Outlook, By Orchards (2023-2034) ($MN)
  • Table 20 Global Smart Irrigation Analytics Market Outlook, By Greenhouses (2023-2034) ($MN)
  • Table 21 Global Smart Irrigation Analytics Market Outlook, By Turf & Landscape (2023-2034) ($MN)
  • Table 22 Global Smart Irrigation Analytics Market Outlook, By Vineyards (2023-2034) ($MN)
  • Table 23 Global Smart Irrigation Analytics Market Outlook, By Golf Courses (2023-2034) ($MN)
  • Table 24 Global Smart Irrigation Analytics Market Outlook, By Horticulture (2023-2034) ($MN)
  • Table 25 Global Smart Irrigation Analytics Market Outlook, By End User (2023-2034) ($MN)
  • Table 26 Global Smart Irrigation Analytics Market Outlook, By Commercial Farms (2023-2034) ($MN)
  • Table 27 Global Smart Irrigation Analytics Market Outlook, By Greenhouse Operators (2023-2034) ($MN)
  • Table 28 Global Smart Irrigation Analytics Market Outlook, By Municipal Authorities (2023-2034) ($MN)
  • Table 29 Global Smart Irrigation Analytics Market Outlook, By Landscape Companies (2023-2034) ($MN)
  • Table 30 Global Smart Irrigation Analytics Market Outlook, By Golf Courses (2023-2034) ($MN)
  • Table 31 Global Smart Irrigation Analytics Market Outlook, By Research Organizations (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) Regions are also represented in the same manner as above.