BL.Predict, the clairvoyant of maintenance for Le Havre city

Stadium Océane du Havre.

Imagine you won the lottery (yes, we all dream about it) and bought Versailles castle. You can not remember if you closed the bathroom tap on the other wing of the castle. Do not worry, you do not have to walk ten minutes long, you just have to check your phone app which will let you know if the water is still running thanks to BL.Predict sensors. If you don’t think about it, the solution will alert you after an unusual consumption.

This short story was to let you picture what BL.Predict is about. In this article we’ll tell you about the project we are leading in collaboration with Le Havre City.

Le Havre Seine Métropole (LHSM) is a French conurbation composed of 275 000 peoples in 54 municipalities. LHSM manages numerous services for its citizens, such as water management and sanitation, waste and recycling management, mobility and transports solutions, schools and health services, sports and leisure facilities, especially the swimming pools and the stadium of the local football team, Le Havre AC.

So Le Havre Seine Metropolis, it’s over 200 buildings to maintain every day for the need of the community. To do so, it uses the Carl Source CMMS solutionCarl Touch since 2016 and is now developing it on all its facilities managed by M. Thibault Siefridt, in charge of the Smart Building project, in collaboration with a digital transformation consulting company Integrativ, under the responsibility of M. Alaric Defrances et Paul Lefrançois, and with Carl Berger-Levrault.
The city wants now to go further with this solution to ease the maintenance management of its facilities by implementing one of our last innovative solution: BL.Predict. We are working together to establish BL.Predict, an innovative interoperability platform dedicated to the intelligent management of technical equipment linked to the Carl Source CMMS solution. Thanks to IoT (Internet of Things) technologies, the platform collects, stocks, analyses and transforms the data to enhance them and provide constant information for maintenance purpose. With these data the platform can let the persons in charge know in case of dysfunction, automatically alert in case of technical symptoms, helps to apply conditional maintenance, to prevent some technical operations and optimize equipment energy performances.

BL.Predict illustration

Proof of concept on Océane Stadium

The Océane Stadium, with a capacity up to 28 000 peoples is the biggest facility to welcome all kind of event in Normandie. It is use for special events and must be ready to use the D-day. So in one hand, its numerous equipment need to be monitor in terms of temperature and humidity rate (for electronic equipment), to make sure air handling units are perfectly working and verify sanitary hot water temperatures to avoid any risk linked to legionellosis. On the other hand, the stadium has been build on a groundwater table which involves a pumping system in constant work to insure the stadium grass not to be flooded. The conurbation set up ambitious energies reductions objectives, so they monitor electricity, gas and water consumption to reach them.
Thanks to the numerous IoT sensors installed by our partners, Adeunis and WattSense , different kind of physical data are collected on our platform.
To let you imagine the importance of these collected data, the stadium is about 19 hectares and there is only one technician, height hours a day to take care of all its equipment. Just to go checking the state of all equipment, it would take him days without even intervening on the systems. That’s why the about 150 data collected by day on each of the more than thirty devices are precious. It saves time by doing targeted intervention classified by priority and by indicating the equipment states evolution (when changing the air handling unit filter for instance). Finally, they provide concrete long term information to the site manager such as the dysfunction rate, possibles improvements, equipment maintains conditions knowledge and the insurance to respect security rules.
In the context of the tertiary decree, we also collect gas and electricity consumption directly from Enedis and GRDF API’s for several facilities.

BL.Predict premises management
Figure 1: Premises data collected dashboardBL.Predict, meters managementFigure 2: Meters data collected dashboardBL.Predict, sanitary facilities managementFigure 3: Sanitary facilities data collected dashboard

At the moment, the POC (Proof Of Concept) is satisfying. LHSM plans to collect data from all the facilities present on the conurbation using BL.Predict.
As soon as LHSM is ready to extend our solution on all the city, it will help them to manage over 200 facilities on a same software.

Once this project will be well set up, LHSM plans to implement BL.Visualize , a Carl Berger-Levrault solution which provides 3D representation of facilities and networks.

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