DigitalPlant

An advanced tool for integrated air‑quality management

DigitalPlant is an innovative software platform that implements an integrated methodology combining sensors and numerical models for air‑quality assessment and the management of emission sources.

DigitalPlant merges environmental monitoring with forecasting models and machine‑learning techniques to provide an advanced decision‑support system able to identify and prevent environmental issues in real time, both in the short and medium term.

Its main application areas include urban environments, industrial facilities, and natural or environmental areas.

The platform enables:

Real‑time data visualization and statistical analysis of historical series

Configuration of multi‑parameter and multi‑site alert thresholds with automatic warning generation

Identification of emission sources through back‑trajectory models

Assessment of short‑ and medium‑term potential impacts to enable timely corrective actions

Key Features

Real‑time monitoring

Compatibility with all continuous‑measurement sensors and devices

Visualization and analysis of observed data

Automatic detection of “critical events”

Back‑trajectory models for source identification

Dispersion models for short‑ and medium‑term impact assessment

Machine‑learning‑based data propagation and forecast calibration

Early‑warning systems and decision support

DigitalPlant is designed to automatically and promptly provide all information needed to prevent environmental issues. Identifying an event through a detailed monitoring system is essential to highlight its potential consequences. Knowing the origin of the issue helps determine which stakeholders may need to intervene and how corrective actions should be configured or scaled. Territorial administrators can evaluate the most relevant measures, while operators of potentially impactful activities can assess their contribution and identify areas and methods for intervention.

Application Contexts

Industrial Applications

Assess real‑time emissions from industrial plants by integrating data from internal or territorial monitoring networks.
Identify and characterize point, diffuse and fugitive sources, distinguishing industrial emissions from other territorial sources through retrospective models and multiparametric analyses.
Activate customized early‑warning systems capable of automatically signaling anomalies or threshold exceedances and supporting timely corrective actions.
Optimize operational efficiency by minimizing unnecessary interventions thanks to the ability to distinguish internal events from external contributions and evaluate the real evolution of impacts in the short and medium term.
Monitor and assess odor impact, enabling timely and targeted mitigation actions and supporting citizen‑reported complaints with scientifically robust analyses.

DigitalPlant consente agli operatori industriali di agire in un quadro di trasparenza tecnica, migliorare le proprie performance ambientali, rispondere con maggiore efficacia alle richieste degli enti di controllo e ridurre i rischi di criticità operative e reputazionali.

Immagine di città vista dall'alto con fabbrica che emette fumi nell'aria

Urban Applications

In urban areas, often characterized by multiple emission sources and complex environmental dynamics, DigitalPlant enables advanced air‑quality supervision at city and metropolitan scale. Key applications include:

Continuous monitoring of large urban areas through heterogeneous sensor networks integrated into a single information system.
Identification of predominant sources using air‑trajectory reconstruction models and advanced statistical analyses.
Support for technical and administrative planning through forecasting models that estimate the evolution of emission scenarios and help evaluate the potential effectiveness of mitigation measures (traffic restrictions, emission‑control policies, urban planning).
Early warning and public communication, with the ability to provide reliable information to citizens via dashboards, public portals or territorial alert systems.

DigitalPlant contributes to improving environmental information quality, supporting data‑driven decisions and increasing transparency toward the population.

Port Applications

Port areas are complex environments where maritime traffic, logistics, road transport and nearby urban settlements coexist. DigitalPlant serves as an integrated platform to:

Continuously monitor air quality within the port area, integrating data from dedicated sensors, existing stations and meteorological sources.
Assess the impact of port activities on surrounding territories, distinguishing contributions from maritime traffic versus urban or industrial sources.
Identify predominant sources through retrospective models, useful for determining the contribution of specific docks, operational phases, storage areas, construction sites or moving vehicles.
Support mitigation plans, shore‑power strategies, operational control and intervention planning based on continuously updated information recalibrated through machine‑learning algorithms.

For Port Authorities and management bodies, DigitalPlant is a concrete tool for improving operational sustainability, enhancing transparency toward citizens and reducing conflicts between port and territory.

Tourism and Hospitality Applications

In tourist areas and high‑value natural environments, environmental quality is essential for enhancing the visitor experience and the attractiveness of the site. DigitalPlant can be used to:

Assess and certify air quality in naturalistic or tourist‑oriented areas through continuous monitoring and easily accessible indicators.
Support sustainable‑management processes by helping administrations, park authorities and operators identify critical dynamics linked to tourism flows, transportation or local activities.
Provide transparent information to visitors through public dashboards, on‑site displays or app‑based notifications.

DigitalPlant becomes a tool for territorial promotion, improving service quality and enhancing sustainability, with positive impacts on reputation, image and economic competitiveness.