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UpSens is the competent and reliable partner to support you in the development of solutions based on IoT sensors, to make your product increasingly sustainable and efficient, also from the point of view of energy savings.
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Optoi is one of the seven companies selected at national level for the Chips Act: the European legislative package on semiconductors, to strengthen technological and production leadership.
Do you want a healthy environment in the spaces where you spend up to 90% of your time?
QuAir is the solution!
What is QuAir?
QuAir is a modular and customizable indoor air quality monitoring device that combines advanced sensors and IoT technologies.
- Measurement of environmental parameters, consistently, reliably, and in real time
- Connected: makes it possible to send measurement data to a cloud space with customisable frequency
- Does not require installation but only a simple initial configuration
- Modular: customisable according to the specific needs of the environment or application in which it is placed
Fundamental parameters for the healthiness of indor environments
Index Air Quality global parameter
All data is always available to the user!
QuAir has its own my.quair platform for visualization in a graphical and intuitive format.
Visualization is in real time or it is possible to access the history of measurements taken, a key function for setting up energy efficiency for buildings.
All data collected from individual sensors can be downloaded in csv format.
"QuAir is the UpSens “turnkey solution" for monitoring environmental quality in indoor spaces.”
Frequently Asked Questions
Measuring indoor air quality is important because indoor and outdoor air pollution are the main environmental risk factor for people’s health. Since people spend up to 90% of their time indoors, breathing clean air means living healthier lives.
UpSens develops and manufactures standard and customised IoT sensors for monitoring physical and chemical parameters. Our must is the correctness of the data measured, because any complex system that relies on data to create intelligent systems, algorithms, artificial intelligence, risks being a “sandcastle” if they are not correct.
Our sensors collect a significant amount of data that, when correlated with each other, are a valuable source of information. The analysis of these data and the subsequent creation of AI-based algorithms allow us to obtain benefits ranging from the interpretation of complex situations and the possibility of obtaining information indirectly all the way to the efficiency of the systems if the final application involves the connection to these, as well as savings in terms of energy and therefore sustainability.
There is no single cause to blame for poor indoor air quality. There are chemical, physical, and biological agents. The main sources of indoor air pollution are linked to various factors, such as the occupants themselves, for example, as well as dust, building materials, furnishings, fixtures, and the outdoor air itself.
For this reason, it is important to measure indoor air quality in a scientific way, before activating any solution to implement corrective measures that may be suitable for the specific environment. It is equally important to keep measuring air quality by means of sensors, to verify that the implemented solution remains effective and performing over time.
Sensors that collect indoor air quality data are the starting point, for example in an air handling system, to be able to understand how to optimise the system’s operation. Thanks to the integration of environmental sensors in the areas where the system is in operation, it is possible to understand when it needs to be turned on, off or adjust its speed according to the actual need. This means that now the systems work not only by taking into account the size of a room or the time slots, but also considering the actual use and therefore the specific need to avoid wasting energy and money. The implementation of AI-related data analysis logics also makes it possible to implement intelligent efficiency that self-learns according to changes in the occupancy of a given environment that may vary over time.
The sensors can also be implemented in systems already present in the building; in this case, a preliminary stage is necessary before installation to understand in which mode they can be connected.
The main parameters to be measured in an office to determine air quality are: carbon dioxide (C02), since it helps understand if a room is properly ventilated, volatile organic compounds (VOCs), and fine particles (PM). In addition, we recommend also measuring temperature and relative humidity values as they are useful data for any correlations, of help in the development of efficiency algorithms.
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