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시장보고서
상품코드
1778904
클라우드 기반 수질 분석 시장 - 세계 산업 규모, 점유율, 동향, 기회, 예측, 컴포넌트별, 전개 모드별, 용도별, 지역별, 경쟁별(2020-2030년)Cloud-based Water Analytics Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Component, By Deployment Mode, By Application, By Region & Competition, 2020-2030F |
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클라우드 기반 수질 분석 세계 시장 규모는 2024년에 184억 3,000만 달러로 평가되었고, CAGR 11.48%로 성장하여 2030년에는 353억 7,000만 달러에 이를 것으로 예측됩니다.
클라우드 기반 수질 분석은 클라우드 컴퓨팅 플랫폼을 활용하여 물 관련 데이터를 실시간으로 수집, 분석, 관리, 모니터링, 최적화, 예측 통찰력을 제공하는 것을 말합니다.
| 시장 개요 | |
|---|---|
| 예측 기간 | 2026-2030년 |
| 시장 규모 : 2024년 | 184억 3,000만 달러 |
| 시장 규모 : 2030년 | 353억 7,000만 달러 |
| CAGR : 2025-2030년 | 11.48% |
| 급성장 부문 | 수요 예측 및 소비 분석 |
| 최대 시장 | 북미 |
이 플랫폼은 센서, IoT 장치, AI 알고리즘, 빅데이터 분석을 활용하여 수질, 사용량, 배수, 누수, 환경 영향 등을 추적합니다. 클라우드 기반 시스템은 중요한 물 데이터에 대한 중앙 집중식 액세스를 통해 유틸리티, 산업 및 정부의 의사결정 강화, 자원 사용 최적화 및 규제 준수를 지원합니다. 기존 물 관리 시스템과 달리 클라우드 기반 분석은 확장성, 원격 액세스, 인프라 비용 절감, 스마트시티 프레임워크와의 원활한 통합을 실현합니다.
클라우드 기반 수질 분석 시장은 세계 물 부족, 인프라 노후화, 엄격한 환경 규제 증가로 인해 유틸리티 및 산업계가 보다 스마트한 솔루션을 요구하고 있습니다. 도시화와 산업화는 수자원에 대한 압력을 가중시키고 있으며, 효율적인 모니터링과 관리가 필수적입니다. 또한, 홍수, 가뭄, 오염물질 발생과 같은 기후 변화로 인한 사건은 예측 가능한 수질 분석의 필요성을 강조하고 있습니다. 정부와 지자체는 스마트시티 프로젝트의 일환으로 디지털 물 솔루션에 많은 투자를 하고 있으며, 산업계는 더 나은 자산 관리와 운영 효율을 위한 도구를 찾고 있습니다. AI, 머신러닝, IoT 기술을 클라우드 플랫폼에 통합하여 예지보전, 누수 감지, 실시간 알림을 가능하게 함으로써 그 가치 제안을 더욱 강화할 수 있습니다.
세계 클라우드 기반 수질 분석 시장의 향후 성장은 클라우드 컴퓨팅의 발전, 스마트 기기의 보급, 서비스형 모니터링(MaaS) 비즈니스 모델의 채택 증가에 의해 촉진될 것입니다. 구독 기반 모델을 통해 초기 비용을 절감할 수 있기 때문에 소규모 공익 기업이나 신흥 경제국에서도 첨단 수질 분석 도구에 접근할 수 있게 됩니다. 기술 제공업체, 상수도 사업자, 정부 간의 파트너십은 기술 혁신을 촉진하고 시장 범위를 확장하고 있습니다. 아시아태평양은 급속한 도시화와 물 관리 문제로 인해 고성장 지역으로 부상하고 있으며, 시장은 전 세계적으로 지속적인 성장이 예상됩니다. 전반적으로, 효율적이고 지능적이며 규정을 준수하는 물 관리 시스템에 대한 수요가 향후 몇 년 동안 클라우드 기반 분석의 채택을 촉진할 것으로 예측됩니다.
세계 물 부족과 효율적인 자원 관리에 대한 수요 증가
기존 인프라 및 기존 물 관리 시스템과의 통합
수질 분석에 인공지능과 머신러닝을 도입
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.
| Market Overview | |
|---|---|
| Forecast Period | 2026-2030 |
| Market Size 2024 | USD 18.43 Billion |
| Market Size 2030 | USD 35.37 Billion |
| CAGR 2025-2030 | 11.48% |
| Fastest Growing Segment | Demand Forecasting & Consumption Analytics |
| Largest Market | North America |
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.
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:
Company Profiles: Detailed analysis of the major companies present in the Global Cloud-based Water Analytics Market.
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: