Water quality analyzers are deployed in cloud computing applications through an integrated "cloud-edge-device" monitoring system. Serving as end-user sensing nodes, these devices leverage cloud computing's massive storage, elastic computing power, and remote collaboration capabilities to address critical water environment needs including municipal water management, watershed governance, industrial supervision, and ecological monitoring. Each application scenario aligns with cloud computing's core strengths in centralized control, intelligent analysis, and remote maintenance. Below are eight representative implementation scenarios that comprehensively meet mainstream industry requirements, featuring clear categorization and strong practical applicability:

1. Cloud-based Monitoring and Emergency Warning of Surface Water in the Basin

This is the core application scenario of cloud computing integrated with water quality analyzers, designed for large-scale water monitoring across regions including rivers, lakes, and reservoirs.

• Implementation approach: Deploy grid-based online water quality analyzers at key sections of river basins (including main and tributary streams) and critical monitoring points, as well as drinking water sources. Real-time data will be transmitted to the basin-wide water environment cloud platform via the Internet of Things (IoT). The cloud computing platform will handle comprehensive data storage and distributed processing, enabling "one-map" visualization of water quality data. Additionally, cloud-based models will facilitate water quality trend forecasting and traceability of sudden pollution incidents.
• Cloud computing value: It resolves data silo issues in cross-regional monitoring, leveraging elastic cloud computing power to enable synchronized analysis across multiple monitoring points. When sudden chemical leaks or water eutrophication occur, it rapidly identifies pollution sources and simulates dispersion pathways, providing cloud-based decision support for emergency response.

II. Full-Process Cloud Management and Process Optimization of Wastewater Treatment Plants

Adapting to the operational processes and water quality compliance management of municipal sewage treatment plants and industrial wastewater treatment stations represents a high-frequency industrial application scenario for cloud computing implementation.

• Application method: Deploy online water quality analyzers (for monitoring DO, ammonia nitrogen, COD, total phosphorus, etc.) at the influent inlet, biochemical tank, sedimentation tank, and effluent outlet of the wastewater treatment plant, with real-time data upload to the cloud. The cloud platform integrates process equipment operation data and optimizes aeration, dosing, and nitrogen/phosphorus removal strategies through big data modeling, while simultaneously enabling remote monitoring of water quality compliance across all processes.
• Value of Cloud Computing: Replacing traditional "manual empirical operations" by enabling intelligent adjustment of process parameters through massive data modeling in the cloud, which ensures stable and compliant effluent discharge while reducing chemical and energy consumption. Simultaneously, centralized cloud monitoring of all monitoring points minimizes on-site maintenance personnel requirements.

III. Cloud-based Water Treatment and Comprehensive Quality Assurance of Water Supply Networks

It covers the full-chain water quality monitoring of municipal waterworks, from raw water to process water, treated water, and pipeline networks, meeting the large-scale management requirements of urban water supply.

• Implementation Method: Deploy online water quality analyzers at raw water intake points, sedimentation tanks, filtration units, and treatment plants, as well as at urban water supply network nodes and end points. The data is uniformly integrated into the urban water supply cloud platform. The cloud enables real-time monitoring of raw water quality fluctuations, automatically optimizes dosing, filtration, and disinfection processes, and simultaneously monitors water quality at the network end points to promptly detect secondary pollution and pipeline leakage issues.
• Cloud computing value: Enables comprehensive and refined management of urban water supply. When raw water quality undergoes sudden changes, the cloud provides rapid alerts and adjusts processes. Centralized cloud analysis of pipeline water quality data extends water supply assurance from the 'water plant end' to the 'end-user end'.

IV. Cloud-based Supervision and Law Enforcement Traceability of Industrial Park Wastewater Discharge

Adapting to environmental protection authorities' emission supervision of industrial park enterprises represents the core application scenario of cloud computing in environmental law enforcement.

• Implementation method: Deploy national standard online water quality automatic monitoring instruments at the main discharge outlet of the industrial park and the discharge outlets of each enterprise. All test data (pH, COD, heavy metals, etc.) are uploaded in real-time to the environmental supervision cloud platform. The cloud computing platform conducts 24/7 uninterrupted monitoring of the data and sets up automatic early warning for exceedances.
• Value of Cloud Computing: Achieving automation and unmanned supervision of pollutant discharge, replacing traditional manual inspections. Real-time cloud recording of non-compliant data with tamper-proof features provides evidentiary data for environmental law enforcement. Concurrently, cloud-based analysis of comprehensive pollutant discharge data in industrial parks identifies high-pollution enterprises, enabling precise regulatory oversight.

V. Cloud Data Synchronization and Mobile Inspection of Portable Water Quality Analyzer

This lightweight solution leverages edge-cloud collaboration to address deployment blind spots in online analyzers, while supporting mobile inspection scenarios for outdoor, remote water sources, and rural drinking water systems.

• Application method: Inspection personnel carry portable water quality analyzers to the site for on-site testing, and synchronize the test data in real-time to the mobile inspection cloud platform via 4G/5G. The cloud automatically stores and organizes the inspection data, generating standardized inspection reports. Management personnel can remotely view the inspection results and issue inspection tasks from the cloud.
• Cloud computing delivers value by addressing traditional mobile inspection challenges: manual data entry, cumbersome report compilation, and untraceable results. It enables centralized cloud management of inspection data, seamlessly integrating mobile detection with comprehensive monitoring data.

VI. Cloud Monitoring and Ecological Early Warning of Water Quality in Marine / Coastal Waters

To optimize water quality monitoring for marine environments, coastal waters, and sewage discharge outlets, cloud computing's remote control capabilities are leveraged in high-salinity, high-humidity, and remote areas.

• Application method: Deploy salt-tolerant online water quality analyzers at marine discharge outlets, nearshore waters, and around islands to monitor parameters such as salinity, dissolved oxygen, chlorophyll a, and petroleum compounds. The data is transmitted via satellite and maritime base stations to the marine environment cloud platform. The cloud platform integrates marine hydrological and meteorological data to analyze the occurrence trends of red tides and petroleum pollution, enabling early warning.
• The value of cloud computing lies in addressing challenges such as remote locations and network accessibility in marine monitoring. By centrally storing vast amounts of marine water quality data in the cloud, it enables digital decision-making for marine ecosystem governance.

7. Cloud-based Centralized Operation and Maintenance of Water Quality Analyzers with Remote Management

This foundational support scenario covers all monitoring scenarios, enabling environmental protection authorities, water utilities, and maintenance companies to manage distributed analyzers at scale.

• Application method: All connected water quality analyzers (online, portable) upload operational data (sensor status, calibration records, reagent levels, pipeline pressure) to the equipment operation and maintenance cloud platform. The cloud platform monitors the health status of the equipment in real time, automatically identifies faults and provides maintenance recommendations, while also formulating personalized inspection and consumable replacement plans based on historical data.
• Cloud computing value: It upgrades traditional 'manual on-site inspections' to cloud-based remote maintenance, slashing operational costs (industry data shows over 60% reduction in on-site inspection workload), while enhancing equipment stability and preventing data loss from equipment failures.

VIII. Cloud-based Monitoring of Rural Drinking Water Safety and Village-to-Village Access Guarantee

Cloud computing is a practical application in public welfare, specifically designed to monitor water quality at rural small water supply stations and decentralized drinking water sources. This solution addresses the challenges of scattered monitoring points and limited operational capacity in rural areas.

• Implementation method: Low-cost small online water quality analyzers are deployed at village water supply stations, wells, and reservoirs to monitor core indicators such as pH, turbidity, and residual chlorine. The data is transmitted via NB-IoT low-power networks to the rural drinking water cloud platform. Township and county-level water authorities can remotely monitor water quality at all monitoring points in the cloud, with immediate alerts triggered when standards are exceeded, followed by dispatch of personnel for intervention.
• Value of cloud computing: Addressing the issue of 'no one to manage or unable to manage' in rural water quality monitoring, achieving comprehensive and automated monitoring of rural drinking water quality at low cost, thereby ensuring rural drinking water safety.

Supplement: Scenario Adaptation for Different Cloud Computing Models

The above scenarios can flexibly adopt public cloud, private cloud, or hybrid cloud models based on data security, computing power requirements, and implementation costs, ensuring applications better meet practical needs.

• Public cloud: Designed for lightweight scenarios like rural drinking water systems, small business wastewater treatment, and portable inspection devices, offering low deployment costs and rapid deployment.
• Private cloud: Designed for large-scale water treatment plants, core environmental regulators, and confidential water area monitoring, with local data storage and high security.
• Hybrid cloud architecture: Tailored for watershed governance and industrial park supervision, with core sensitive data stored in private clouds while routine monitoring data is shared on public clouds, ensuring both security and collaborative efficiency.