Research and Innovation: Project SPIRI: continuous monitoring of indoor air quality for controlling heating, ventilation, air conditioning and Regrigeration systems (HVAC-R) with artificial intelligence techniques
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Project SPIRI: continuous monitoring of indoor air quality for controlling heating, ventilation, air conditioning and Regrigeration systems (HVAC-R) with artificial intelligence techniques

Abstract

The quality of the air we breathe has a great impact on our lives in the short, medium and long term (daily stress, seasonal diseases, cancer development or chronic lung diseases). According to the World Health Organization (WHO), 7 million people die prematurely every year because of air pollution. 4.3 of these specifically because of air pollution indoors. The WHO also attributes this to the fact that the indoor air quality (IAQ) is up to 40 times worse than outside air due to factors such as inadequate ventilation, internal source of pollutants, among others. Strategies for mitigation of this phenomenon involve: choice of materials with low emissions of Volatile Organic Compounds (VOCs), over dimension the ventilation system or modulate variable ventilation rate by the concentration of CO2 (simple control loop). Although the latter presenting a degree of sophistication, only a low concentration of CO2 is not sufficient to ensure optimum IAQ by ignoring other pollutants, such as VOCs or particulate matter (PM). The aim of the SIPRI Project is examining the feasibility of a new approach to maintaining IAQ, which involves holistic monitoring of environments to be controlled and application of artificial intelligence techniques for optimal and adaptive control of these. In this context holistic means: concentration of various greenhouse gases, particulate matter and other parameters that correlate with the environments occupancy level - sound pressure sensors, light and based photodiodes presence in the infrared spectrum - as well as other common parameters in HVAC-R systems controls - temperature, relative humidity and pressure. Regarding the artificial intelligence techniques, we seek to develop algorithms to identify profiles and modify autonomously control strategies for HVAC-R system. In other words, it the goal is to create a network of different sensors and an algorithm to interpret various data and recognize patterns to optimize the operation of HVAC-R systems, ensuring environmental quality for users and energy efficiency. This hardware set (network of sensors connected to the Internet) and software (artificial intelligence algorithm for interpreting data and intelligent performance) will be called SIPRI Technology, which is the product to be developed by researchers with the help of the PIPE program. With this, we intend to improve the air quality of indoor environments and reduce proliferation of diseases and energy expenses. In addition, the SIPRI project will be pioneering in the type sensor networks in building automation in Brazil and it is expected that he and his successors products may open doors for business with sensor networks and improve the quality of life, safety and well -being of the people. (AU)

Articles published in Agência FAPESP Newsletter about the research grant:
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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
ESQUIAGOLA, J.; MANINI, M.; AIKAWA, A.; YOSHIOKA, L.; ZUFFO, M.; IEEE. Monitoring Indoor Air Quality by using IoT Technology. PROCEEDINGS OF THE 2018 IEEE 25TH INTERNATIONAL CONFERENCE ON ELECTRONICS, ELECTRICAL ENGINEERING AND COMPUTING (INTERCON 2018), v. N/A, p. 4-pg., . (16/15514-8, 15/22209-4)

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