Abstract

IoT networks for data gathering in the buildings allow to control and manage the operational phase of the systems for ventilation and IAQ, optimizing the energy flows and the indoor comfort conditions. The concept of Cognitive Building steers the implementation of such networks in the assets considering the sensors as scattered systems to inform and actuate the adaptation strategies which are crucial when variables have to be included in the process management. Variables as weather, occupancy flows during the day, energy production by renewable energies, energy storage strategies, affect the indoor conditions, the rate of use of the HVAC systems and the energy management of the used/storage resources. The eLUX lab at the Smart Campus of the University of Brescia is a pilot building in the field and it has been monitoring since 2017. The indoor conditions monitoring could unveil critical situations defined by temperature, humidity and indoor air quality (IAQ) in the educational spaces and envisage strategies and scenarios related to energy demand defined by the occupancy stream. The IoT network collects data about indoor air quality in the different spaces and it is used to verify and increase the accuracy on occupancy estimation. The HVAC management referred to the effective occupancy can enable an energy management process based on user-centred approach empowering an increment of the comfort hours facing critical situations and it is possible to promote actuation strategies preserving energy efficiency and IAQ (e.g. increase ventilation to decrease the CO2 concentration, decrease temperature and control relative humidity in the indoor spaces by window opening or modulation of the fans and dehumidification systems activation). The educational spaces have been adopted as case studies to analyse the actual indoor conditions and come up with a detailed description of the profiles of use (i.e. occupancy, lighting, equipment, HVAC, CO2) supporting effective management policies. The paper describes the analyses on the data collected to understand when and how the indoor conditions can be improved to preserve the learning performance of the users. The research addresses one of the main topics of the eLUX living lab.

Highlights

  • Buildings are the places where activities are carried on and users that can adapt their indoor condition in the working spaces are most productive and with high levels of perceived wellbeing and comfort

  • The indoor conditions monitoring could unveil critical situations defined by temperature, humidity and indoor air quality (IAQ) in the educational spaces and envisage strategies and scenarios related to energy demand defined by the occupancy stream

  • The present study embraces a data driven approach and stating from the data gathered by sensors in different educational spaces analyzes three main parameters of comfort controllable in the indoor space to understand when, during the day, critical situation are reported and a prioritization of the indoor conditions related to the effective impact on learning performance is identified

Read more

Summary

Introduction

Buildings are the places where activities are carried on and users that can adapt their indoor condition in the working spaces are most productive and with high levels of perceived wellbeing and comfort. The IoT infrastructure provides the crucial layer of information about indoor conditions and occupancy needs that can enable the actuation of strategies to adapt and correct the building behavior and indoor conditions towards enhanced levels of comfort in the smart city [2]. In school buildings the problem of indoor air quality and comfort condition is crucial, researches proved that insufficient ventilation rate [3], and an increase of CO2 concentration [4], produces weaker results in the exam pass rate [5] which means a decreased cognitive performance in the accomplishment of learning task and knowledge restitution. Many studies reported that ventilation rates in schools are often substandard, and it is not rare to record CO2 concentration above 3000 ppm in classrooms [6][7]

Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call