クラウドベースの水質分析市場- 世界の産業規模、シェア、動向、機会、予測、コンポーネント別、展開モード別、用途別、地域別、競合別、2020～2030年

クラウドベースの水質分析の世界市場規模は2024年に184億3,000万米ドルで、2030年のCAGRは11.48%で2030年には353億7,000万米ドルに達すると予測されています。

クラウドベースの水質分析とは、クラウドコンピューティングプラットフォームを利用して、水関連データをリアルタイムで収集、分析、管理し、モニタリング、最適化、予測洞察を行うことを指します。

これらのプラットフォームは、センサ、IoTデバイス、AIアルゴリズム、ビッグデータ分析を活用して、水質、使用量、配水、漏水、環境への影響を追跡します。クラウドベースのシステムは、重要な水データへの一元的なアクセスを可能にすることで、公益事業、産業、政府による意思決定の強化、資源利用の最適化、規制遵守を支援します。従来型水管理システムとは異なり、クラウドベースの分析は、拡大性、リモートアクセス、インフラコストの削減、スマートシティのフレームワークとのシームレスな統合を実現します。

クラウドベースの水質分析の市場は、世界の水不足、インフラの老朽化、厳しい環境規制の増加により、公益事業や産業がよりスマートなソリューションを求めるようになっています。都市化と工業化は水資源への圧力を強めており、効率的なモニタリングと管理が不可欠となっています。さらに、洪水、干ばつ、汚染物質の発生といった気候変動に起因する事象は、予測的な水質分析の必要性を浮き彫りにしています。政府や自治体は、スマートシティプロジェクトの一環としてデジタル水ソリューションに多額の投資を行っており、一方、産業は、より優れた資産管理と運用効率のためのツールを求めています。AI、機械学習、IoT技術のクラウドプラットフォームへの統合は、予知保全、漏水検知、リアルタイムアラートを可能にすることで、その価値提案をさらに強化します。

世界のクラウドベースの水質分析市場の今後の成長は、クラウドコンピューティングの進歩、スマートデバイスの普及、MaaS（Monitoring-as-a-Service）ビジネスモデルの採用増加によって促進されます。サブスクリプションベースモデルにより初期費用が削減されるため、小規模の公益企業や新興経済国でも先進的水質分析ツールにアクセスできるようになります。技術プロバイダ、水道事業体、政府間のパートナーシップは、技術革新を促進し、市場範囲を拡大しています。アジア太平洋のは急速な都市化と水管理の課題から高成長地域として浮上しており、市場は世界的に持続的な成長が見込まれています。全体として、効率的でインテリジェントかつコンプライアンスに準拠した水管理システムに対する需要が、今後数年間、クラウドベースの分析の採用を促進すると考えられます。

主要市場促進要因

世界の水不足と効率的な資源管理に対する需要の高まり

主要市場課題

従来型インフラや既存の水管理システムとの統合

主要市場動向

水質分析における人工知能と機械学習の採用

目次

第1章 ソリューション概要

• 市場の定義
• 市場の範囲
  • 対象市場
  • 調査対象年
  • 主要市場セグメンテーション

第2章 調査手法

第3章 エグゼクティブサマリー

第4章 顧客の声

第5章 世界のクラウドベースの水質分析市場展望

• 市場規模・予測
  • 金額別
• 市場シェア・予測
  • コンポーネント別（ソリューション、サービス）
  • 展開モード別（パブリッククラウド、プライベートクラウド、ハイブリッドクラウド）
  • 用途別（水質モニタリング、漏水検知と管理、資産管理、需要予測と消費分析、洪水モニタリングと災害管理、規制遵守と報告、廃水処理分析）
  • 地域別（北米、欧州、南米、中東・アフリカ、アジア太平洋）
• 企業別（2024年）
• 市場マップ

第6章 北米のクラウドベースの水質分析市場展望

• 市場規模・予測
• 市場シェア・予測
• 北米：国別分析
  • 米国
  • カナダ
  • メキシコ

第7章 欧州のクラウドベースの水質分析市場展望

• 市場規模・予測
• 市場シェア・予測
• 欧州：国別分析
  • ドイツ
  • フランス
  • 英国
  • イタリア
  • スペイン

第8章 アジア太平洋のクラウドベースの水質分析市場展望

• 市場規模・予測
• 市場シェア・予測
• アジア太平洋：国別分析
  • 中国
  • インド
  • 日本
  • 韓国
  • オーストラリア

第9章 中東・アフリカのクラウドベースの水質分析市場展望

• 市場規模・予測
• 市場シェア・予測
• 中東・アフリカ：国別分析
  • サウジアラビア
  • アラブ首長国連邦
  • 南アフリカ

第10章 南米のクラウドベースの水質分析市場展望

• 市場規模・予測
• 市場シェア・予測
• 南米：国別分析
  • ブラジル
  • コロンビア
  • アルゼンチン

第11章 市場力学

• 促進要因
• 課題

第12章 市場動向と発展

• 合併と買収
• 製品上市

第13章 企業プロファイル

• ABB Ltd.
• General Electric Company
• IBM Corporation
• Microsoft Corporation
• Schneider Electric SE
• Siemens AG
• Oracle Corporation
• Suez SA

第14章 戦略的提言

第15章 調査会社について・免責事項

Global Cloud-based Water Analytics Market was valued at USD 18.43 Billion in 2024 and is expected to reach USD 35.37 Billion by 2030 with a CAGR of 11.48% through 2030. Cloud-based water analytics refers to the use of cloud computing platforms to collect, analyze, and manage water-related data in real time for monitoring, optimization, and predictive insights.

These platforms leverage sensors, IoT devices, AI algorithms, and big data analytics to track water quality, usage, distribution, leakages, and environmental impacts. By enabling centralized access to critical water data, cloud-based systems help utilities, industries, and governments enhance decision-making, optimize resource usage, and meet regulatory compliance. Unlike traditional water management systems, cloud-based analytics offer scalability, remote access, lower infrastructure costs, and seamless integration with smart city frameworks.

The market for cloud-based water analytics is rising due to increasing global water scarcity, aging infrastructure, and stringent environmental regulations pushing utilities and industries toward smarter solutions. Urbanization and industrialization have intensified pressure on water resources, making efficient monitoring and management essential. Furthermore, climate change-driven events like floods, droughts, and contamination outbreaks highlight the need for predictive water analytics. Governments and municipalities are investing heavily in digital water solutions as part of smart city projects, while industries demand tools for better asset management and operational efficiency. The integration of AI, machine learning, and IoT technologies into cloud platforms further enhances their value proposition by enabling predictive maintenance, leakage detection, and real-time alerts.

The future growth of the global cloud-based water analytics market will be propelled by advancements in cloud computing, the proliferation of smart devices, and the increasing adoption of Monitoring-as-a-Service (MaaS) business models. As subscription-based models reduce upfront costs, even small utilities and emerging economies can access advanced water analytics tools. Partnerships between technology providers, water utilities, and governments are fostering innovation and expanding market reach. With Asia Pacific emerging as a high-growth region due to its rapid urbanization and water management challenges, the market is poised for sustained growth globally. Overall, the demand for efficient, intelligent, and compliant water management systems will drive the adoption of cloud-based analytics in the years ahead.

Key Market Drivers

Rising Global Water Scarcity and Demand for Efficient Resource Management

The increasing scarcity of freshwater resources is compelling governments, industries, and utilities worldwide to seek advanced solutions for monitoring and managing water usage. Population growth, rapid urbanization, and climate change have collectively stressed global water supplies. Cloud-based water analytics platforms allow organizations to track consumption patterns, detect inefficiencies, and optimize distribution systems in real time. These platforms support sustainable water management by enabling data-driven decisions, predictive maintenance, and leakage detection-functions critical to minimizing wastage and ensuring equitable distribution.

For instance, agriculture accounts for approximately 70% of global freshwater withdrawals according to the Food and Agriculture Organization (FAO). Cloud-based analytics help optimize irrigation systems by analyzing water needs based on soil moisture data, weather forecasts, and historical usage patterns. Similarly, urban utilities leverage real-time analytics to identify leakages-responsible for up to 30% of water loss in distribution networks-and take timely corrective action. By integrating cloud platforms with IoT-enabled sensors, utilities and industrial users gain actionable insights, which support both operational efficiency and environmental sustainability. By 2025, an estimated 1.8 billion people will live in regions suffering from absolute water scarcity, as reported by the United Nations. This projection emphasizes the urgent global need for advanced water management solutions like cloud-based analytics, which help optimize usage, detect leakages, and improve overall water resource sustainability in increasingly strained environments.

Key Market Challenges

Integration with Legacy Infrastructure and Existing Water Management Systems

One of the most significant challenges facing the global cloud-based water analytics market is the complexity involved in integrating modern analytics platforms with existing, often outdated, water management infrastructure. Water utilities and industrial operators in many regions, particularly in emerging economies, have traditionally relied on legacy systems characterized by manual operations, analog instrumentation, and siloed data environments. These legacy infrastructures were never designed with digital transformation in mind, making it difficult to seamlessly implement cloud-based analytics solutions. The process of retrofitting old systems with advanced sensors, real-time data acquisition tools, and cloud gateways requires both significant capital investment and specialized technical expertise. Furthermore, legacy infrastructure may lack the necessary digital interfaces or compatibility standards, resulting in extended project timelines, unexpected costs, and operational disruptions during the transition phase.

The challenge of integration is compounded by the diversity of water management systems across regions and industries. Different utilities may operate varying types of hardware, communication protocols, and software systems, creating fragmented environments that resist standardized cloud deployment. This heterogeneity necessitates customized integration strategies for each deployment, further driving up implementation complexity and cost. Moreover, water management is often critical infrastructure, and utilities are understandably cautious about adopting technologies that may compromise operational reliability or data integrity. Ensuring continuous service delivery while upgrading systems remains a delicate balance for operators. Cloud-based solutions must offer robust interoperability, secure data migration capabilities, and minimal downtime assurances to gain acceptance within such environments. Until these integration hurdles are systematically addressed, especially for small to medium-sized utilities with limited budgets, the growth potential of cloud-based water analytics will remain partially constrained.

Key Market Trends

Adoption of Artificial Intelligence and Machine Learning in Water Analytics

The increasing integration of artificial intelligence and machine learning into cloud-based water analytics platforms is transforming the way water resources are monitored, managed, and optimized. Artificial intelligence-driven solutions enable predictive analysis, anomaly detection, and automated decision-making, which enhance operational efficiency and reduce water loss. These advanced technologies process large volumes of real-time data collected from various sources, including sensors, smart meters, and satellite imagery, to provide actionable insights. Predictive maintenance models based on artificial intelligence help utilities anticipate equipment failures, pipeline leaks, or contamination events, minimizing service disruptions and maintenance costs.

Machine learning algorithms continuously improve the accuracy of water demand forecasting, leakage detection, and consumption pattern analysis by learning from historical and real-time data. This ability allows water utilities, municipalities, and industrial operators to make data-driven decisions and proactively manage water distribution networks. The integration of artificial intelligence into cloud platforms also supports dynamic optimization of water usage in agriculture, industrial processes, and smart city applications. As these technologies mature and become more accessible through cloud services, the adoption of artificial intelligence and machine learning in water analytics is expected to increase steadily, providing enhanced predictive capabilities and operational intelligence for users across diverse sectors.

Key Market Players

• ABB Ltd.
• General Electric Company
• IBM Corporation
• Microsoft Corporation
• Schneider Electric SE
• Siemens AG
• Oracle Corporation
• Suez SA

Report Scope:

In this report, the Global Cloud-based Water Analytics Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Cloud-based Water Analytics Market, By Component:

• Solutions
• Services

Cloud-based Water Analytics Market, By Deployment Mode:

• Public Cloud
• Private Cloud
• Hybrid Cloud

Cloud-based Water Analytics Market, By Application:

• Water Quality Monitoring
• Leakage Detection & Management
• Asset Management
• Demand Forecasting & Consumption Analytics
• Flood Monitoring & Disaster Management
• Regulatory Compliance & Reporting
• Wastewater Treatment Analytics

Cloud-based Water Analytics Market, By Region:

• North America
  • United States
  • Canada
  • Mexico
• Europe
  • Germany
  • France
  • United Kingdom
  • Italy
  • Spain
• Asia Pacific
  • China
  • India
  • Japan
  • South Korea
  • Australia
• Middle East & Africa
  • Saudi Arabia
  • UAE
  • South Africa
• South America
  • Brazil
  • Colombia
  • Argentina

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Cloud-based Water Analytics Market.

Available Customizations:

Global Cloud-based Water Analytics Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

• Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Solution Overview

• 1.1. Market Definition
• 1.2. Scope of the Market
  • 1.2.1. Markets Covered
  • 1.2.2. Years Considered for Study
  • 1.2.3. Key Market Segmentations

2. Research Methodology

• 2.1. Objective of the Study
• 2.2. Baseline Methodology
• 2.3. Key Industry Partners
• 2.4. Major Association and Secondary Sources
• 2.5. Forecasting Methodology
• 2.6. Data Triangulation & Validation
• 2.7. Assumptions and Limitations

3. Executive Summary

• 3.1. Overview of the Market
• 3.2. Overview of Key Market Segmentations
• 3.3. Overview of Key Market Players
• 3.4. Overview of Key Regions/Countries
• 3.5. Overview of Market Drivers, Challenges, and Trends

4. Voice of Customer

5. Global Cloud-based Water Analytics Market Outlook

• 5.1. Market Size & Forecast
  • 5.1.1. By Value
• 5.2. Market Share & Forecast
  • 5.2.1. By Component (Solutions, Services)
  • 5.2.2. By Deployment Mode (Public Cloud, Private Cloud, Hybrid Cloud)
  • 5.2.3. By Application (Water Quality Monitoring, Leakage Detection & Management, Asset Management, Demand Forecasting & Consumption Analytics, Flood Monitoring & Disaster Management, Regulatory Compliance & Reporting, Wastewater Treatment Analytics)
  • 5.2.4. By Region (North America, Europe, South America, Middle East & Africa, Asia Pacific)
• 5.3. By Company (2024)
• 5.4. Market Map

6. North America Cloud-based Water Analytics Market Outlook

• 6.1. Market Size & Forecast
  • 6.1.1. By Value
• 6.2. Market Share & Forecast
  • 6.2.1. By Component
  • 6.2.2. By Deployment Mode
  • 6.2.3. By Application
  • 6.2.4. By Country
• 6.3. North America: Country Analysis
  • 6.3.1. United States Cloud-based Water Analytics Market Outlook
    • 6.3.1.1. Market Size & Forecast
      • 6.3.1.1.1. By Value
    • 6.3.1.2. Market Share & Forecast
      • 6.3.1.2.1. By Component
      • 6.3.1.2.2. By Deployment Mode
      • 6.3.1.2.3. By Application
  • 6.3.2. Canada Cloud-based Water Analytics Market Outlook
    • 6.3.2.1. Market Size & Forecast
      • 6.3.2.1.1. By Value
    • 6.3.2.2. Market Share & Forecast
      • 6.3.2.2.1. By Component
      • 6.3.2.2.2. By Deployment Mode
      • 6.3.2.2.3. By Application
  • 6.3.3. Mexico Cloud-based Water Analytics Market Outlook
    • 6.3.3.1. Market Size & Forecast
      • 6.3.3.1.1. By Value
    • 6.3.3.2. Market Share & Forecast
      • 6.3.3.2.1. By Component
      • 6.3.3.2.2. By Deployment Mode
      • 6.3.3.2.3. By Application

7. Europe Cloud-based Water Analytics Market Outlook

• 7.1. Market Size & Forecast
  • 7.1.1. By Value
• 7.2. Market Share & Forecast
  • 7.2.1. By Component
  • 7.2.2. By Deployment Mode
  • 7.2.3. By Application
  • 7.2.4. By Country
• 7.3. Europe: Country Analysis
  • 7.3.1. Germany Cloud-based Water Analytics Market Outlook
    • 7.3.1.1. Market Size & Forecast
      • 7.3.1.1.1. By Value
    • 7.3.1.2. Market Share & Forecast
      • 7.3.1.2.1. By Component
      • 7.3.1.2.2. By Deployment Mode
      • 7.3.1.2.3. By Application
  • 7.3.2. France Cloud-based Water Analytics Market Outlook
    • 7.3.2.1. Market Size & Forecast
      • 7.3.2.1.1. By Value
    • 7.3.2.2. Market Share & Forecast
      • 7.3.2.2.1. By Component
      • 7.3.2.2.2. By Deployment Mode
      • 7.3.2.2.3. By Application
  • 7.3.3. United Kingdom Cloud-based Water Analytics Market Outlook
    • 7.3.3.1. Market Size & Forecast
      • 7.3.3.1.1. By Value
    • 7.3.3.2. Market Share & Forecast
      • 7.3.3.2.1. By Component
      • 7.3.3.2.2. By Deployment Mode
      • 7.3.3.2.3. By Application
  • 7.3.4. Italy Cloud-based Water Analytics Market Outlook
    • 7.3.4.1. Market Size & Forecast
      • 7.3.4.1.1. By Value
    • 7.3.4.2. Market Share & Forecast
      • 7.3.4.2.1. By Component
      • 7.3.4.2.2. By Deployment Mode
      • 7.3.4.2.3. By Application
  • 7.3.5. Spain Cloud-based Water Analytics Market Outlook
    • 7.3.5.1. Market Size & Forecast
      • 7.3.5.1.1. By Value
    • 7.3.5.2. Market Share & Forecast
      • 7.3.5.2.1. By Component
      • 7.3.5.2.2. By Deployment Mode
      • 7.3.5.2.3. By Application

8. Asia Pacific Cloud-based Water Analytics Market Outlook

• 8.1. Market Size & Forecast
  • 8.1.1. By Value
• 8.2. Market Share & Forecast
  • 8.2.1. By Component
  • 8.2.2. By Deployment Mode
  • 8.2.3. By Application
  • 8.2.4. By Country
• 8.3. Asia Pacific: Country Analysis
  • 8.3.1. China Cloud-based Water Analytics Market Outlook
    • 8.3.1.1. Market Size & Forecast
      • 8.3.1.1.1. By Value
    • 8.3.1.2. Market Share & Forecast
      • 8.3.1.2.1. By Component
      • 8.3.1.2.2. By Deployment Mode
      • 8.3.1.2.3. By Application
  • 8.3.2. India Cloud-based Water Analytics Market Outlook
    • 8.3.2.1. Market Size & Forecast
      • 8.3.2.1.1. By Value
    • 8.3.2.2. Market Share & Forecast
      • 8.3.2.2.1. By Component
      • 8.3.2.2.2. By Deployment Mode
      • 8.3.2.2.3. By Application
  • 8.3.3. Japan Cloud-based Water Analytics Market Outlook
    • 8.3.3.1. Market Size & Forecast
      • 8.3.3.1.1. By Value
    • 8.3.3.2. Market Share & Forecast
      • 8.3.3.2.1. By Component
      • 8.3.3.2.2. By Deployment Mode
      • 8.3.3.2.3. By Application
  • 8.3.4. South Korea Cloud-based Water Analytics Market Outlook
    • 8.3.4.1. Market Size & Forecast
      • 8.3.4.1.1. By Value
    • 8.3.4.2. Market Share & Forecast
      • 8.3.4.2.1. By Component
      • 8.3.4.2.2. By Deployment Mode
      • 8.3.4.2.3. By Application
  • 8.3.5. Australia Cloud-based Water Analytics Market Outlook
    • 8.3.5.1. Market Size & Forecast
      • 8.3.5.1.1. By Value
    • 8.3.5.2. Market Share & Forecast
      • 8.3.5.2.1. By Component
      • 8.3.5.2.2. By Deployment Mode
      • 8.3.5.2.3. By Application

9. Middle East & Africa Cloud-based Water Analytics Market Outlook

• 9.1. Market Size & Forecast
  • 9.1.1. By Value
• 9.2. Market Share & Forecast
  • 9.2.1. By Component
  • 9.2.2. By Deployment Mode
  • 9.2.3. By Application
  • 9.2.4. By Country
• 9.3. Middle East & Africa: Country Analysis
  • 9.3.1. Saudi Arabia Cloud-based Water Analytics Market Outlook
    • 9.3.1.1. Market Size & Forecast
      • 9.3.1.1.1. By Value
    • 9.3.1.2. Market Share & Forecast
      • 9.3.1.2.1. By Component
      • 9.3.1.2.2. By Deployment Mode
      • 9.3.1.2.3. By Application
  • 9.3.2. UAE Cloud-based Water Analytics Market Outlook
    • 9.3.2.1. Market Size & Forecast
      • 9.3.2.1.1. By Value
    • 9.3.2.2. Market Share & Forecast
      • 9.3.2.2.1. By Component
      • 9.3.2.2.2. By Deployment Mode
      • 9.3.2.2.3. By Application
  • 9.3.3. South Africa Cloud-based Water Analytics Market Outlook
    • 9.3.3.1. Market Size & Forecast
      • 9.3.3.1.1. By Value
    • 9.3.3.2. Market Share & Forecast
      • 9.3.3.2.1. By Component
      • 9.3.3.2.2. By Deployment Mode
      • 9.3.3.2.3. By Application

10. South America Cloud-based Water Analytics Market Outlook

• 10.1. Market Size & Forecast
  • 10.1.1. By Value
• 10.2. Market Share & Forecast
  • 10.2.1. By Component
  • 10.2.2. By Deployment Mode
  • 10.2.3. By Application
  • 10.2.4. By Country
• 10.3. South America: Country Analysis
  • 10.3.1. Brazil Cloud-based Water Analytics Market Outlook
    • 10.3.1.1. Market Size & Forecast
      • 10.3.1.1.1. By Value
    • 10.3.1.2. Market Share & Forecast
      • 10.3.1.2.1. By Component
      • 10.3.1.2.2. By Deployment Mode
      • 10.3.1.2.3. By Application
  • 10.3.2. Colombia Cloud-based Water Analytics Market Outlook
    • 10.3.2.1. Market Size & Forecast
      • 10.3.2.1.1. By Value
    • 10.3.2.2. Market Share & Forecast
      • 10.3.2.2.1. By Component
      • 10.3.2.2.2. By Deployment Mode
      • 10.3.2.2.3. By Application
  • 10.3.3. Argentina Cloud-based Water Analytics Market Outlook
    • 10.3.3.1. Market Size & Forecast
      • 10.3.3.1.1. By Value
    • 10.3.3.2. Market Share & Forecast
      • 10.3.3.2.1. By Component
      • 10.3.3.2.2. By Deployment Mode
      • 10.3.3.2.3. By Application

11. Market Dynamics

• 11.1. Drivers
• 11.2. Challenges

12. Market Trends and Developments

• 12.1. Merger & Acquisition (If Any)
• 12.2. Product Launches (If Any)
• 12.3. Recent Developments

13. Company Profiles

• 13.1. ABB Ltd.
  • 13.1.1. Business Overview
  • 13.1.2. Key Revenue and Financials
  • 13.1.3. Recent Developments
  • 13.1.4. Key Personnel
  • 13.1.5. Key Product/Services Offered
• 13.2. General Electric Company
• 13.3. IBM Corporation
• 13.4. Microsoft Corporation
• 13.5. Schneider Electric SE
• 13.6. Siemens AG
• 13.7. Oracle Corporation
• 13.8. Suez SA

14. Strategic Recommendations

15. About Us & Disclaimer