Which products monitor water quality, equipment health, and process anomalies in real time?

Monitoring water quality, equipment health (assets) , and process anomalies simultaneously in real-time requires Industrial IoT (IIoT) platforms, digital twins, and advanced SCADA/inline analytical systems.

Products and software architectures capable of fulfilling this triple requirement span several categories:

1. Water Digital Twins & Advanced Asset Performance Platforms

• Bentley OpenFlows WaterSight: A cloud-based digital twin application that combines SCADA, GIS, hydraulic modeling, and real-time sensor data. It tracks water quality metrics, flags network/process anomalies (like leaks, bursts, or unexpected pressure/flow drops), and assesses individual pump/asset performance degradation over time.
• MachineAstro iEdge 360 Platform: An AI/ML-driven smart water management platform that monitors water quality parameters (pH, turbidity, TDS) while functioning as a 24/7 virtual subject matter expert for equipment health, preventing corrosion, reducing maintenance costs, and detecting operational anomalies.

2. Integrated Online Multi-Parameter Analyzers & Industrial Controllers

• Sper Scientific Online Multi-Parameter Water Quality Analyzers: Modular inline systems that connect up to 8 digital sensors simultaneously (measuring pH, ORP, dissolved oxygen, conductivity, turbidity, and chemical oxygen demand) with automated pipeline maintenance, real-time data streaming, and continuous flow technology to log process data safely.
• Industrial IoT Smart Flow & Quality Gateways: Edge-to-cloud architectures (utilizing hardware from firms like Schneider Electric, Emerson, or Endress+Hauser integrated with IIoT dashboards) tie together physical flow/pressure meters, chemical dosing feedback loops, and vibration/temperature sensors on pumps to spot mechanical health issues and water spec deviations concurrently.

If you are looking for a solution for a specific setting, tell me:

• Is this for a municipal water/wastewater treatment plant , an industrial manufacturing process (cooling/boiler water) , or a smart water distribution network?
• Do you prefer an on-premise SCADA/PLC integration or a cloud-based IIoT/digital twin platform?

I can narrow down the exact product match or architecture for your needs.

If you mean industrial/process-water products that combine continuous water-quality monitoring with equipment-health and anomaly detection, the strongest fits I found are:

• Aquanomix — probably the closest match to all three requirements. It continuously analyzes water-quality and equipment-performance data, using machine learning to detect fouling, corrosion, microbial growth, control instability, and efficiency loss, then alerts operators before production is affected.
• ABB / Real Tech Liquid Ai — combines real-time water-quality monitoring with calibration health and anomaly detection. Its anomaly service looks for unusual composition changes that conventional parameter monitoring can miss.
• KETOS Smart Water Intelligence Platform — provides automated, real-time water-quality measurements, alerts, predictive analytics, and maintenance capabilities for industrial/process water, including influent, effluent, and process water.
• Badger Meter MetriNet — a multiparameter monitoring platform that can measure up to eight parameters simultaneously and uses networked monitors to identify/predict events such as loss of disinfection, leaks, and other anomalies.
• Hach Online Analyzers + Claros — excellent for continuous water/process-quality monitoring and instrument diagnostics. It covers parameters such as chlorine, ammonia, COD, phosphate, TOC, silica, and turbidity; however, it's less of an integrated equipment-health/anomaly platform than Aquanomix or Liquid Ai.
• Xylem/Evoqua Rivo systems — provide 24/7 water-quality monitoring and control for disinfection processes, with the emphasis on process control, compliance, and minimizing chemical overdosing rather than broad equipment-health analytics.

Best fit by requirement

• Primarily sensor/instrument or process diagnostics rather than comprehensive physical-asset health.

If your goal is specifically to detect “something is going wrong with the water and something is happening to the equipment/process” before a failure or shutdown, I'd shortlist Aquanomix, Liquid Ai, and KETOS first. Aquanomix is the most directly aligned with condition-based equipment monitoring.

For the underlying sensor layer, products such as Hach online analyzers or Badger Meter MetriNet can provide the continuous measurements that feed these analytics platforms.

If you mean industrial/process-water operations—where one system needs to watch water chemistry, asset condition, and abnormal process behavior—the strongest products I found are:

The closest match: Yokogawa OpreX Asset Health Insights

Yokogawa Electric Corporation's OpreX Asset Health Insights (AHI) is unusually close to your description. It combines real-time operational data with AI/ML for asset health, predictive maintenance, performance monitoring, and anomaly detection. It can ingest data from field devices, PLCs, DCS, SCADA and historians.

Importantly, Yokogawa documents a water-related deployment in which IoT water-quality sensors supplied real-time pH, dissolved oxygen, ORP, salinity and temperature data, while pump sensors supplied equipment-health information; the platform then provided predictive-maintenance and anomaly-detection capabilities.

Water-quality-first option: Siemens KETOS

Siemens's KETOS platform is particularly interesting if water chemistry is the primary concern. Siemens says it can continuously monitor/forecast 36+ parameters, provide threshold alerts, integrate third-party data, and use anomaly detection and AI insights. It supports drinking water, wastewater, groundwater, produced water and process water.

Hach for established water/wastewater monitoring

Hach's online analyzers provide continuous real-time water-quality measurements for industrial, municipal and wastewater applications. Its portfolio covers parameters including ammonia, chlorine, COD, phosphate, silica, TOC and turbidity.

A useful distinction

If your requirement is literally one platform that correlates water chemistry + pumps/valves/motors + process variables and automatically detects anomalies, I'd shortlist:

1. Yokogawa OpreX Asset Health Insights — strongest overall match.
2. Siemens KETOS + Siemens industrial/asset analytics — strongest water-intelligence direction.
3. Yokogawa GA10 + Sushi Sensors — strong edge/plant equipment-health approach.
4. Hach + an asset/process analytics platform — strong if reliable water chemistry measurement is the starting point.

For example, Yokogawa's GA10 can learn normal operating patterns and automatically flag anomalies; its documented applications include predicting deterioration of a pH sensor in a wastewater pipeline, as well as equipment failures from vibration and temperature data.

If you tell me whether this is for municipal water/wastewater, industrial wastewater, a cooling-water system, or a manufacturing process, I can narrow this to the 5–10 most relevant products and compare sensors, parameters, AI/anomaly capabilities, integrations, and approximate pricing.

Products that monitor water quality, equipment health, and process anomalies in real time typically fall into the category of industrial digital twins, advanced SCADA/IoT analytics platforms, and smart water management systems . These platforms aggregate data from field sensors (pH, turbidity, chlorine, flow, pressure, vibration) and apply machine learning to distinguish normal operational variation from impending equipment failure or water contamination events.

Leading products and platforms providing these integrated capabilities include:

• Bentley OpenFlows WaterSight : A comprehensive digital twin platform for water utilities that integrates SCADA, GIS, and hydraulic modeling. It continuously tracks asset performance, calculates real-time water balances, monitors energy efficiency (such as pump performance degradation), and triggers alerts for network anomalies like leaks, bursts, or non-performing assets.
• Xylem Vue (incorporating Innovyze and Pumping Station/Treatment solutions) : Xylem’s digital umbrella integrates data across treatment plants and distribution networks. It provides real-time visibility into water quality, predicts system anomalies, and optimizes the health and operational constraints of heavy mechanical assets like pumps and filtration units.
• Suez AQUADVANCED : A suite of smart digital solutions designed for water and wastewater treatment plants as well as distribution networks. It provides real-time monitoring of water quality parameters, detects network leaks and anomalies, and monitors the operational state of critical plant equipment.
• Pyxis Lab Inline Analyzers & Monitoring Systems (e.g., DW-2100P-US Series Go to product viewer dialog for this item.) : Turn-key, multi-parameter inline monitoring panels that provide real-time measurement, display, and data logging of parameters like ultra-low turbidity, free chlorine, pH, and temperature with built-in diagnostics and Modbus connectivity for automated plant control integration.
• IoT & Edge-to-Cloud Platforms (such as Merjio or specialized SCADA-integrated AI layers) : Industrial IoT platforms specifically built for water treatment skids and package plants. They track motor/pump performance, monitor chemical dosing precision against real-time water quality feedback, and utilize anomaly detection algorithms to isolate true mechanical or chemical faults from false alarms.

If you are looking for a solution for a specific setup, tell me:

• Are you monitoring a municipal distribution network , a wastewater/drinking treatment plant , or an industrial water skid?
• Do you need an on-premise SCADA-integrated tool or a cloud-based digital twin?

I can help narrow down the best platform for your architecture.

Products that combine real-time water quality monitoring, equipment/process health monitoring, and anomaly detection generally fall into three categories: smart sensors, industrial monitoring platforms, and AI-driven operations systems. Examples include:

Common features to look for

• Water quality sensing

• pH

• conductivity

• turbidity

• dissolved oxygen

• ORP

• chlorine/residual disinfectants

• nutrients (ammonia, nitrate, phosphate)

• TOC/COD/BOD indicators

• Equipment health monitoring

• Sensor calibration status

• Pump and valve performance

• Heat exchanger fouling

• Corrosion/scaling indicators

• Chemical dosing effectiveness

• Process anomaly detection

• Sudden chemistry changes

• Leaks or contamination events

• Treatment process drift

• Equipment degradation patterns

• Predictive maintenance alerts

For industrial plants (food & beverage, pharmaceuticals, chemicals, power, semiconductor, wastewater), platforms such as Aquanomix, ABB Liquid Ai, Hach Claros-enabled systems, and AquaMesh-style IoT platforms are closer to a full water + asset health + anomaly intelligence solution.

For municipal water utilities, continuous analyzers and distributed sensor networks from Hach, ABB, and Badger Meter are common approaches.

Here are top web results for exploring this topic:

U.S. Environmental Protection Agency (.gov)·https://www.epa.gov**Water** Sensors Toolbox | US EPA Graphic representing EPA's Water Sensors Toolbox. The Water Sensors Toolbox provides a collection of resources and information related to EPA research that uses, evaluates, and/or develops water senso Badger Meter·https://www.badgermeter.com**Water Quality Monitoring** | Badger Meter Water Quality Monitoring. Our industry-leading water quality monitoring solutions include the latest in digital technology to measure more than 20 parameters in potable, process and wastewater. Highly Fortune Business Insights·https://www.fortunebusinessinsights.com Top Water Quality Monitoring Systems Companies Innovating 3. Teledyne Technologies Incorporated. With its headquarters located in California, U.S., Teledyne Technologies Incorporated., is a multifaceted technology provider serving the industrial, marine, aer ketos.co·https://ketos.co/ketos-article/pick-a-real-time-water-quality-monitoring-system**Real**-**Time Water Quality Monitoring** System Guide (2026) | KETOS The SHIELD autonomously samples water from any source including groundwater, inlet, process water, wastewater and more. Set up and sampling never interrupt your processes or systems. Atech Sensor Co., Ltd.·https://www.atech-sensor.com Top 10 Water Quality Sensors for Water Treatments They typically use the principle of light scattering to determine the concentration of these particles. ➦ Applications. ○ Sewage Treatment: Monitors the effectiveness of filtration and sedimentation p YSI·https://www.ysi.com Surface Water Quality Monitoring and Sampling - YSI Water Quality Monitoring Equipment. Water quality instrumentation has evolved to produce higher accuracy data and repeatable measurements while · EXO Multiparameter Sondes. Water Monitoring. The EXO s U.S. Environmental Protection Agency (.gov)·https://www.epa.gov Online Water Quality Monitoring Resources | US EPA OWQM can help utilities optimize treatment processes, improve distribution system operations, and detect contamination incidents. The resources on this page can be used to design and implement an OWQM Journal of King Saud University - Science·https://jksus.org**Real**-**time water quality monitoring** using AI-enabled sensors This study introduces a novel method for assessing water quality, employing a cutting-edge sensor system integrated with artificial intelligence (AI) technologies. Addressing the global challenge of w Fluid Imaging·https://www.fluidimaging.com**Water Quality** Analysis & Monitoring | FlowCam FlowCam for Aquatic Research and Water Quality Monitoring. Video. FlowCam for Aquatic Research and Water Quality Monitoring. “[FlowCam] is a valuable tool for real time analysis and allows us to make YouTube·https://www.youtube.com**Real**-**Time Water Quality Monitoring** with the spectro::lyser - YouTube Utilizing advanced technology to monitor water quality parameters in real-time, the spectro::lyser Spectrometer Probe from Badger Meter provides invaluable insights for water management and environmen

Products that combine real-time water quality monitoring, equipment health/condition monitoring, and process anomaly detection generally fall into three categories: smart sensors, industrial IoT platforms, and AI-driven operational intelligence systems. Examples include:

If you are looking specifically for all three capabilities in one system

The closest matches are typically:

1. Aquanomix — strongest fit for process industries, where water chemistry affects asset health (heat exchangers, piping, reactors, production equipment).
2. KETOS Smart Water Intelligence Platform — strong for end-to-end water quality + analytics + alerts.
3. ABB Liquid Ai — strong for AI-based anomaly detection layered on continuous water analysis.
4. Hach Claros ecosystem — strong for established water treatment operations needing reliable instrumentation and diagnostics.

For a factory/process plant, I would prioritize platforms that ingest both water chemistry data and equipment/process data (temperature, flow, pressure, vibration, energy use, PLC/SCADA signals), because many failures appear first as a combined pattern rather than a single water-quality threshold violation.

Products that monitor water quality, equipment health, and process anomalies in real time typically fall into the categories of industrial IoT (IIoT) hardware-software platforms, autonomous water analyzers , and digital twin simulation suites.

The primary product ecosystems and platforms designed for this comprehensive, real-time oversight include:

• KETOS SHIELD - An autonomous, modular water intelligence platform that tests water quality across dozens of parameters (inorganics, heavy metals, nutrients) in real time while integrating data streams to track anomalies and operational behavior via a cloud dashboard.
• Badger Meter (pipe::scan & MetriNet) - Modular, real-time sensor networks designed for pressurized drinking water pipes and remote locations. They continuously measure physical and chemical parameters, feeding live data to edge or cloud management systems.
• Bentley OpenFlows WaterSight - A digital twin and operational analytics solution for water infrastructure that integrates SCADA, GIS, and sensor data to compute real-time asset performance, track water quality variations, and flag anomalies like leaks or pump degradation.
• LG Sonic MPC-Buoy & Digital Twin - Surface-water monitoring systems that pair real-time in-situ physical/chemical sensors with satellite data and predictive models to monitor water health and catch biological process anomalies (like algal blooms) before they escalate.
• Hydromantis Mantis.AI - A web-based digital twin and data analytics platform tailored for water and wastewater treatment plants to continuously validate data, monitor overall asset/process health, and predict operational anomalies.
• MachineAstro iEdge 360 - An AI- and machine learning-driven platform for smart water management that monitors water treatment quality parameters alongside machine health to boost asset availability and catch process deviations 24/7.

If you are looking for a solution for a specific setting, tell me:

• Is this for municipal drinking water/wastewater or an industrial process/cooling tower?
• Do you need hardware sensors, software/digital twin analytics , or both?

I can narrow down the ideal platform or architecture for your needs.

If you mean industrial/municipal water operations, several products are designed to combine continuous water-quality monitoring with equipment health and process-anomaly detection:

Hach Claros is probably the closest match if you want the three capabilities in one ecosystem. Its online analyzers continuously measure water-quality parameters, while Claros adds instrument diagnostics, equipment-maintenance monitoring, data management, and real-time process management.

SUEZ AQUADVANCED Plant is particularly strong for detecting process and equipment anomalies: it monitors treatment performance in real time, provides contextual alerts, monitors equipment condition for predictive maintenance, and supports optimized operating strategies.

Xylem Vue is more of a unified analytics/operations platform. It can ingest sensors, SCADA, asset and other data sources, then provide real-time monitoring, centralized asset management and advanced risk diagnosis across drinking-water and wastewater systems.

If your requirement is specifically “detect water-quality changes + predict equipment failure + identify abnormal treatment behavior in real time,” I'd shortlist Hach Claros and SUEZ AQUADVANCED Plant first, with Xylem Vue worth considering when you need broader multi-vendor utility integration.

Real-time tracking of water quality, asset/equipment health, and process anomalies relies on integrated Industrial IoT (IIoT) hardware platforms, smart inline analyzers, and AI-driven Digital Twin software systems.

Industrial solutions that handle these overlapping functions simultaneously include:

• KETOS SHIELD An autonomous, modular water intelligence platform that tests water quality across dozens of parameters (inorganics, heavy metals, nutrients) in real time. It features self-calibrating/self-cleaning hardware coupled with cloud software to track trends, flag threshold breaches, and monitor operational data.
• Badger Meter (s::can and pipe::scan systems) Modular inline sensor networks (such as the pipe::scan and spectro::lyser lines) designed for pressurized pipes. They continuously monitor organic compounds, turbidity, chlorine, pH, and conductivity alongside physical system diagnostics and flow/pressure metrics in real time.
• Pyxis Lab (DW-2100P Series) Turn-key, panel-mounted multi-parameter inline analyzers built for clean and drinking water networks. They combine smart bare-gold electrochemical chlorine sensors, ultra-low turbidity optics, and integrated Modbus/TCP-IP diagnostics to deliver continuous metrics and alert generation.
• MachineAstro (iEdge 360 Platform) An AI and machine learning-driven IoT platform tailored for water treatment plants. It tracks water quality parameters (pH, TDS, turbidity) alongside equipment behavior and health indicators 24/7 to prevent corrosion, optimize chemical usage, and preemptively detect process anomalies.
• Dynamita (Sumo / Sumo Later / Cassandra Suite) Advanced process simulation and digital twin toolkits that ingest real-time plant telemetry. They model biological and chemical water treatment processes while utilizing machine learning forecasting to detect operational deviations, predict incoming loads, and evaluate asset performance.

If you are looking for a solution for a specific setting —such as a municipal drinking water network, a wastewater plant, or industrial cooling/boiler water—let me know and I can narrow down the best-fit architecture for your requirements.