Field test of the Smart Delta P solution on the Atelier Numérique building
Monitoring of ventilation systems
Monitoring of ventilation systems
The design of a new product involves several stages: analysis of the field requirement, technical specification, hardware/software development, prototyping, industrialisation, etc. It can take several weeks or months to reach the marketing stage. In order to finalise the development, one stage consists of testing the product on pilot sites. The objective is to deploy the solution under real test conditions by target users in order to obtain concrete feedback and quickly remove any blockages.
Announced a few months ago, our offer combining Artificial Intelligence and Edge Computing, developed in collaboration with Carl Software, has now reached the field test phase. The “Smart Delta P” has indeed been tested for several weeks on the ventilation systems of the Atelier Numérique building in Inovallée (38). This first full-scale implementation was made possible with the collaboration of INRIA (National Institute for Research in Digital Science and Technology) and the Le Grésivaudan Community of Communes (owner of the building).
The Montbonnot digital workshop is located in the heart of the Inovallée technology park (38).
This building is dedicated to companies and research in the digital and software field.
It houses several companies from the digital world in its many offices.
1 building dedicated to innovation
1600 m2 of floor space
38 offices on two floors
After having been deployed in the Adeunis and Carl Software buildings, the Smart Delta P solution is now deployed on other ventilation systems in order to validate more installation cases.
INRIA, also working on the digitalization of buildings, allowed us, with the agreement of the CCLG, to deploy Smart Delta P sensors on two elements of the ventilation system of the Atelier Numérique André Emery:
On the Air Handling Unit
The objective is to monitor the clogging of the filter and anticipate its maintenance.
Outside, on the roof of the building
At the level of the extract unit of the CMV
The objective: to monitor the proper functioning of the ventilation box and to anticipate its breakdowns.
This solution operates on a private LoRaWAN network. After a radio-mapping phase carried out by our experts, a Multitech Conduit gateway was installed to cover the entire building, from the ground floor where the AHU is located to the roof.
The installation was carried out at the beginning of January and the first phase, known as the “learning phase”, is now complete. For several weeks, the solution recorded data relating to a so-called “normal” operating mode for each of the ventilation systems and deduced an initial operating model. Each model was then fed back to the corresponding Smart Delta P.
The second phase will now begin, during which the building operators will be able to observe and validate or invalidate the anomalies reported by the model in order to complete its learning process and thus increase its robustness.
Other deployments are already planned with new pilot buildings, which will allow us to diversify our tests and the type of building observed.
The solution will eventually be completely autonomous, based on all the feedback from the field.
Adeunis and Carl Software have designed a turnkey solution that combines IoT, Artificial Intelligence and Edge Computing to easily supervise ventilation equipment in real estate structures and anticipate the maintenance required.
The intelligence provided will allow, through cycle analyses, to prevent and anticipate the technical maintenance of equipment thanks to the generation of predictive models. The role of these models is to detect equipment malfunctions or drifts over time.
Thanks to the relevance of the information transmitted, the maintainer can anticipate his needs and improve his reactivity. The solution enables him to better target his maintenance actions, reduce intervention costs, and act on the energy performance and durability of equipment.
Read our articles on Smart Delta P and intelligent monitoring of ventilation systems