BCALL PRIN 2022D. D. N. 104 DEL 2 FEBRUARY 2022

TITOLO DEL PROGETTO “VIRIDIIS – VertIcal gaRdens wIth DIgital twIn of plantS”

CODICE CUP D53D23001420006

Budget: € 90.646

Other Research Units:

- University of Basilicata, Head: Prof. Paola D’Antonio

- CNR-ITC, Head: Dr Paola Lassandro

Prof. Gregorio ANDRIA – Poliba

Brief project description:

VIRIDIIS is a research project that integrates IoT technologies, advanced sensors and artificial intelligence to improve the ecological quality of urban greenery. Based on the concept of the digital twin of plants, the system collects and analyses heterogeneous data from soil, atmosphere and vegetation, enabling continuous monitoring and proactive assessment of environmental conditions. This technological infrastructure makes it possible to identify critical situations promptly and support informed decision-making in the management of green spaces.

In addition to monitoring, the project introduces a conversational agent that makes information on the health of plants accessible to users, facilitating understanding of their needs and suggesting any corrective measures. In this way, technology becomes a means of bringing citizens and the environment closer together, promoting greater ecological awareness.

The approach is strongly multidisciplinary and combines expertise in sensor technology, IoT infrastructures, data analysis, artificial intelligence, human–machine interaction and botany. The ability to model interactions between soil, plants and the atmosphere contributes not only to the protection of urban greenery, but also to the overall well-being of the urban ecosystem. Furthermore, the proactive approach adopted by VIRIDIIS strengthens urban resilience, improving the ability of green infrastructures to mitigate the effects of climate change.

Overall, the project demonstrates how technology can play a strategic role in building more sustainable and intelligent cities that are capable of addressing contemporary environmental challenges.

General objectives:

• Improve the ecological quality of urban greenery through the integrated use of advanced technologies.
• Continuously and proactively monitor the environmental and physiological conditions of plants.
• Support more informed and sustainable management of urban green spaces.

Specific objectives:

• Create a digital twin of plants, capable of collecting, storing and analysing multimodal data (soil, atmosphere, vegetation).
• Identify critical issues promptly, anomalies and deviations from optimal growth parameters.
• Make information on the condition of plants accessible through a conversational agent using natural language.
• Facilitate understanding of the needs of plants and suggest any corrective measures.
• Integrate multidisciplinary expertise (sensor technology, IoT, AI, HMI, botany) to model interactions between soil, plants and the atmosphere.

Expected results:

The main objective of the project was to create an integrated framework for the continuous monitoring of plant conditions, capable of transforming raw data from sensors into useful information about their health status. A second objective was to develop a digital twin for each monitored plant, in order to obtain a dynamic and up-to-date representation of its physiological and environmental conditions. Finally, the project aimed to make this information easily accessible through a conversational natural-language interface.

Results achieved:

All objectives have been achieved: a system combining sensors and machine learning techniques was developed to produce reliable indicators of plant health; a digital twin capable of analysing trends, anomalies and deviations from optimal parameters was implemented; and a conversational interface was developed to correctly interpret user requests, identify intents and extract relevant entities. Overall, the project enabled intuitive interaction with complex data, improving access to and understanding of information about the monitored green spaces.