Smart and sustainable buildings in the dairy industry

Nounou Idea Challenge 2019 competition

  • In 2019 Siba IoT won a special prize in “Nounou Idea Challenge 2019 competition” . The idea consisted of real time monitoring of air quality in process rooms of a dairy industry in order to protect the health of personnel and employees as well as the quality of products from airborn contamination such as particulate matter, aerosols, microorganisms, moulds and yeasts.
  • Air quality  parameters that are monitored include particulate matter expressed as PM1.0, PM2.5 and PM10, temperature and humidity. Additionally, differential pressure is measured at selected locations in order to maintain negative pressure in a room or to assess the efficacy of air exchange between external and internal ambients. Another type of sensor box detects hydrogen peroxide concentration, a chemical used as a disinfectant in filling operations, and is regulated in the ambient air for the safety of human health.
Fig. 1 - Particle, temperature and humidity dashboard in the incubator room
Siba sensor boxes
  • In total 15 type PM Siba IoT sensor boxes were installed, 12 in the different process rooms and 3 in the outside area around the factory.
  • Another 3 type DP sensor boxes were installed in 3 process rooms to check the differential pressure between two adjacent rooms or between a room and the external air.
  • Finally 2 type HPO Siba sensor boxes measuring hydrogen peroxide concentrations were installed in the yoghurt filling room to detect excess H2O2 concentrations in the air.
  • The measurements generated from the above devices are stored in a web platform where they are visualised in real-time both as tables and timeseries, while it is possible to explore historial data using a user-friendly interface.


  • Analysis of the results can yield useful information, i.e daily, weekly, or seasonal patterns of contamination, adherence to legal limits, detection of sources of pollution, or activities that may cause particle or microbe generation. It can be used to estimate the origin of particles indoors by calulating the indoor-to-outdoor ratio. Ideally it can lead to correlation between microbial counts and particle concentration and thus provide a tool for alerts, prediction and prevention.
  • It is very esady to explore historial data using a user-friendly interface. Thus, each graph is associated (via the location of the device that generated the data) with a specific microclimate. Data sets can be downloaded, and users can set thresholds for alerts using a query language.
  • Figures 3 and 4 show PM2.5 concentrations in two adjacent rooms that communicate through a door that should be kept closed. Similar peaks were found in the two graphs at the same time interval, although of a different magnitude, that may indicate that the door betweeen the rooms was left accidentally open.

Figs. 3 and 4 - PM2.5 particles variation in the drainage and incubation rooms

We were given a unique opportunity to apply our innovative devices to a modern high technology industrial environment, with very high quality standards. Our collaboration with the skilled and highly trained personel led to fruitful discussions and evaluations.