Energy savings and a better environment for children with attendance analysis

Project facts

Project promoter:
Zachráň včely s.r.o.(SK)
Project Number:
SK-INNOVATION-0001
Status:
Completed
Final project cost:
€160,737

Description

The project is focused on saving energy and improving the interiors of buildings. Device established in public buildings such as schools or offices, measures and collects data on ventilation, air quality, humidity, temperature, noise, dust, CO2 levels etc. in the rooms. Based on the analyses of the collected data, it is possible to set up the environment of the building to become healthy for its inhabitants, saved energy consumption and reduce pollution.

Summary of project results

The quality of the environment; Influence of air humidity and temperature on the probability of infection of the exposed subject; the quality of the school / the office environment, especially the level of CO2; management of heating, ventilation and other aspects of building management; the environmental impacts of energy waste.

Design, programming,  testing - HW device design, cloud server programming, mobile application programming for iOS phones, programming a mobile application for Android phones, programming application for computers, testing.

Design and engineering of a plastic box - Plastic packaging for sensors were designed and tested. 

Product certification - The certification and calibration of the product was carried out in such a way that the sensors meet the relevant legislative regulations. 

Creation of educational materials - Educational and informational materials were created.

Saving energy and improving the quality of the environment: Continuous measurement of data inform the operator or automated recuperation / air conditioning system about the need to ventilate or heat the building. This prevents energy losses due to incorrect ventilation. At the same time, potential damage to the health of the child is avoided.

Improving attendance and health: Each school involved in the project can enter data on pupils'' attendance and missed lessons into the system. Machine learning can analyze these data and then classify the school into the appropriate statistical percentiles correlated with the measured values. 

Information on the projects funded by the EEA and Norway Grants is provided by the Programme and Fund Operators in the Beneficiary States, who are responsible for the completeness and accuracy of this information.