In recent years, artificial intelligence (AI) and increasing digitalization have radically transformed the industrial landscape, becoming key elements for optimizing production processes and advanced data management. In this transformation scenario, traditional monitoring platforms represent an outdated model, designed primarily to capture data from IoT devices and transfer it to external analysis tools, as standard business intelligence spreadsheets or software. This operating logic, based on a static and fragmented management of information, is now being replaced by next-generation intelligent platforms. The result is a digital ecosystem capable of transforming monitoring from a passive reading to a proactive strategic management tool.
Digital Twin, Machine and Deep Learning: the engine of predictive models
The latest generation of industrial AI platforms are based on a new operational paradigm based on the integration of multiple advanced technologies.
A central element is the creation of a Digital Twin of the network: a dynamic and always updated digital model that faithfully reproduces the physical infrastructure, allowing to simulate operational scenarios and evaluate the impact of possible interventions in a predictive way.
To complete this architecture, we find the advanced management of predictive models, built and constantly updated thanks to the combined use of machine learning and deep learning.
- Machine learning: uses algorithms that learn from data to make predictions or decisions; it is particularly useful for anticipating failures and optimizing production processes.
- Deep learning: leverage artificial neural networks to model complex data, reducing the need for human intervention during Data Analysis.
These advanced solutions, thanks to the use of artificial intelligence algorithms, are able not only to process and correlate data in real time, but also to anticipate future operational scenarios, automating predictive analytics and suggesting corrective actions directly within the platform. In this way, companies can optimize the efficiency, safety and sustainability of their infrastructures.
Main functionalities of industrial AI platforms:
- Connectivity and integration: connect devices and machines ensuring continuous data flow and centralized control.
- Data collection and management: data from IoT sensors is securely stored and used for real-time monitoring.
- Advanced analysis: through predictive analysis, they identify recurring patterns, predict failures and optimize processes.
- Security and compliance: they ensure high standards of security through encryption, authentication and compliance with industry regulations.
- Interoperability and scalability: designed to easily integrate with existing systems and adapt to business growth.
Onyax ACE platform: the “turnkey” answer for operators and industries
The operation of an AI platform depends on the collection and processing of data from sensors and IoT devices that, especially in the field of water, gas and energy distribution networks, monitor important parameters such as temperatures, pressures, vibrations, losses and emissions, electrical quantities and energy consumption.
To meet the remote monitoring needs of industrial sectors, Onyax has designed and implemented the ACE (Acquisition, Control, Ecosystem) multi-service platform; a full-cloud solution ready for use, able to combine in a single digital ecosystem data from proprietary or third-party IoT devices and advanced features acquired through the constant use of Artificial Intelligence logics.
Integration of machine learning, deep learning and mathematical-model algorithms into ACE, it allows not only to analyse large volumes of information and detect anomalies in a timely manner but also to manage the scalability and security of networks and installations together with the power of the Cloud.
These innovative features facilitate the implementation of large-scale predictive maintenance strategies, improving the operational efficiency and sustainability of distribution networks.
To ensure maximum operational flexibility, the platform offers two access modes:
- ACE Web: provides a complete view of the network, allowing data monitoring and automatic daily report generation to support predictive analytics and process optimization.
- ACE Mobile: optimizes field operations by offering advanced tools such as alarms, detailed geographic information, integrated navigation and real-time notifications. Operators can manage the IoT sensor network directly from smartphones, improving efficiency and timeliness of interventions.
EVALD: the advanced leak detection solution
One of the main applications of Artificial Intelligence in ACE is the EVALD project (Electro-Vibro-Acoustic-Leakage-Detect), an innovative solution for the search of leaks and fugitive emissions in water and gas distribution networks.
EVALD uses the full-cloud platform ACE to manage data from IoT devices and deep learning algorithms in a single digital ecosystem, integrating acoustic analysis, pressure, electrical and vibration to detect areas with a higher probability of loss and predictive analysis on possible deterioration of the network involved.
Conclusion
Industrial AI platforms are a transformative engine for multiple industries, thanks to their ability to collect, analyze and act on data in real time. Solutions such as ACE demonstrate how digitalization and artificial intelligence can generate added value, optimizing production processes and reducing operating costs.
Onyax, with its technological expertise and the continuous development of cutting-edge solutions, is confirmed as a strategic partner for companies that want to face the challenge of digitalization with innovative and high-performance tools.
