WOLA biosensors use two own-developed software. Whereas through the first one we control the biosensor functioning and measure and analyse the changes in our sensing microorganism respirometry, with the online monitoring software we can get data in different ways (xxxx) and interact with the biosensor devices either through website or smart devices (smartphones, tablets).

The treatment of the analytical data is processed and represented in the online interface, offering to the user the option of checking each parameter individually, combined with other selected parameters or even getting a chart representing all of them together. 


Totally brand new interface, fully intuitive, with complete information.

Multiple devices interface
Multiple sensors information
Display command response

Check sensor status
Time remaining for the next analysis step
Display cancellation indicator

Handle execution error
Handle cancellation events
Export button on samples and executions view

WOLA’s state-of-the-art data platforms meet a broader range of analytical requirements and applications, such as real-time analytics, data science and more. Allow better scalability and enable easy access to data via interfaces. Security, data governance and data discovery are all viable functions, too.

Powerful data pipeline tools allow authorised users, such as data engineers and data scientists, to write, deploy and monitor data workflows. Data visualisation and data dissemination tools, including dashboards, automated reports and REST APIs, present the information in useful and meaningful ways.

Smart and Sustainable Water treatment and Management

Integration of our device’s software with current market technology and data interaction requirements

The combination of our biosensors technology, the software integration and the potential capabilities open up new project opportunities linking the internet of things, machine learning, Geospatial data technologies and big data and analysis.

Data Technologies + Internet of Things + Machine Learning + Geospatial Data Technologies + Big Data & Analytics

Data Technologies

WOLA’s devices can be integrated in wider platforms and projects to meet a broader range of analytical requirements and applications, such as real-time analytics, data science and more. Allow better scalability and enable easy access to data via interfaces. Security, data governance and data discovery are all viable functions, too.

Internet of Things


Efficient and optimised management through precise use of information

The Internet of Things (IoT) brings continuous and dynamic processes to water quality monitoring. WOLA’s fast analysis biosensors allow real time water monitoring which is very valuable when it comes to building water quality measurement smart platforms, integrating big data and intelligent management systems.

  • Environmental monitoring of lakes, rivers and seawater.
  • Aquaponic and hydroponic agriculture systems prevention.
  • Spills and effluent, using real-time monitoring to ensure regulatory compliance.
  • Ensure healthy growth of aquatic creatures at aquaculture centres.
  • IoT sensors can also calculate the ideal irrigation scheme for farmers to keep crops in prime condition (smart irrigation). Data on plants, water status and the weather forecast are combined to ensure the use of the optimal water quantity to bring the best nutritional value and highest yield.
  • Contribution to Smart cities water management plan thanks to early detection.
  • WWTP performance control according to environmental standards, boosting decision-making process, preventive maintenance through analysis of big data, acting before disruptions occur.
  • Increasing public confidence in resource management and the quality of recreational and swimming waters.
  • Reducing CO2 print by reducing electricity consumption

Machine Learning


Machine learning brings more accurate outcome predictions.

Machine learning (ML) is a type of artificial intelligence (AI) that helps software improve its predictive ability, automatically learning about data, patterns and outcomes without being explicitly programmed to do so.  

Predictive models can be generated from historical data on water quality critical parameters levels.

Machine learning can diagnose errors in a system and learn how to react in the event of future alarms.


  • Machine learning models offer efficient, real-time analysis, allowing real-time decision-making.
  • Optimise operations and enhance distribution network efficiency, e.g. irrigation processes.
  • Boost risk analysis models.
  • Interpret previous data to identify systemic behaviours and patterns.

Geospatial Data Technologies


Geospatial data: Understanding why everything happens somewhere

Geospatial Data Technologies help us to understand the world around us. Combined with Copernicus Program, WOLA can analyse relationships that may exist between data provided by our sensors and the information provided by the satellites, and how they may be conditioned by geolocation.

Some of the uses for Geospatial Data Technologies:

  • Water Data Management and Analytics
  • Resources Monitoring Services
  • Water asset digitalisation and advanced management
  • Numerical weather forecasting systems
  • Crops monitoring


  • Improve decision making with an enhanced understanding of territories using data trends and patterns.
  • Use spatial data technologies to predict values at locations without measurement equipment using interpolation techniques.
  • Data and systems consultancy based on spatial data technologies.
  • Interoperability, connecting the physical and digital worlds through the integration of geospatial data with business data.

Big Data & Analytics


Improve thinking and decision-making with analysis of raw data

Modern analytical data platforms offer much more than classical data warehouses can handle; transaction support, scalable metadata handling, streaming and batch unification and schema enforcement.

Data provided by WOLA’s biosensors can be integrated in platforms in order to meet a broader range of analytical requirements and applications, such as real-time analytics, SQL, data science and more. Storage is decoupled from computing, allowing better scalability, and open storage formats enable easy access to data via interfaces (APIs). Security, access control, data governance and data discovery are all viable functions, too.

The cloud provides the environment for these data platforms, offering performance, scalability and reliability as well as a diverse set of analytic engines and massive economies of scale. The cloud also brings better security, faster deployment times, frequent feature and functionality updates, more elasticity and lower costs linked to actual usage.

Some examples of some of the multiple applications for big data and analytics include:

  • Detailed analytical data on water quality monitoring.
  • Protect water resources and reservoirs with tracking sensors.
  • Identify inefficiencies in the water treatment system.
  • Early warning systems for disasters.
  • Calculate harvest yields, fertiliser demands, schedule irrigation, identify optimisation strategies for future crops and mitigate environmental pollution, all of which can reduce costs.
  • Internet of Things (IoT) applied in the Smart cities water quality monitoring system.