Alvaro Ortiz Pérez

Alvaro Ortiz Pérez


Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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9 December 2018 in Sensors
Verified
Journal Article
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APAlvaro Ortiz Pérez
Alvaro Ortiz Pérez
BBBenedikt Bierer
Benedikt Bierer
LLouisa Scholz
Louisa Scholz
JWJürgen Wöllenstein
Jürgen Wöllenstein
Stefan PalzerStefan Palzer
Stefan Palzer
Schools are amongst the most densely occupied indoor areas and at the same time children and young adults are the most vulnerable group with respect to adverse health effects as a result of poor environmental conditions. Health, performance and well-being of pupils crucially depend on indoor environmental quality (IEQ) of which air quality and thermal comfort are central pillars. This makes the monitoring and control of environmental parameters in classes important. At the same time most school buildings do neither feature automated, intelligent heating, ventilation, and air conditioning (HVAC) systems nor suitable IEQ monitoring systems. In this contribution, we therefore investigate the capabilities of a novel wireless gas sensor network to determine carbon dioxide concentrations, along with temperature and humidity. The use of a photoacoustic detector enables the construction of long-term stable, miniaturized, LED-based non-dispersive infrared absorption spectrometers without the use of a reference channel. The data of the sensor nodes is transmitted via a Z-Wave protocol to a central gateway, which in turn sends the data to a web-based platform for online analysis. The results show that it is difficult to maintain adequate IEQ levels in class rooms even when ventilating frequently and that individual monitoring and control of rooms is necessary to combine energy savings and good IEQ.

29 December 2016 in Sensors
Verified
Journal Article
Open access
PDF file
APAlvaro Ortiz Pérez
Alvaro Ortiz Pérez
VFVera Kallfaß-De Frenes
Vera Kallfaß-De Frenes
AFAlexander Filbert
Alexander Filbert
JKJanosch Kneer
Janosch Kneer
BBBenedikt Bierer
Benedikt Bierer
Stefan PalzerStefan Palzer
Stefan Palzer
This manuscript describes the design considerations, implementation, and laboratory validation of an odor sensing module whose purpose is to support people that suffer from incontinence. Because of the requirements expressed by the affected end-users the odor sensing unit is realized as a portable accessory that may be connected to any pre-existing smart device. We have opted for a low-cost, low-power consuming metal oxide based gas detection approach to highlight the viability of developing an inexpensive yet helpful odor recognition technology. The system consists of a hotplate employing, inkjet-printed p-type semiconducting layers of copper(II) oxide, and chromium titanium oxide. Both functional layers are characterized with respect to their gas-sensitive behavior towards humidity, ammonia, methylmercaptan, and dimethylsulfide and we demonstrate detection limits in the parts-per-billion range for the two latter gases. Employing a temperature variation scheme that reads out the layer’s resistivity in a steady-state, we use each sensor chip as a virtual array. With this setup, we demonstrate the feasibility of detecting odors associated with incontinence.

25 August 2017 in Proceedings
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Conference Paper
Open access
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APAlvaro Ortiz Pérez
Alvaro Ortiz Pérez
BBBenedikt Bierer
Benedikt Bierer
CDCem Dinc
Cem Dinc
JWJürgen Wöllenstein
Jürgen Wöllenstein
Stefan PalzerStefan Palzer
Stefan Palzer
The localization of bad odors is a long standing issue with high relevance for affected people because of the health and safety implications. In order to enable the detection and localization of bad odors we propose a wireless, low-power consuming sensor network. The sensor nodes are designed to wake-up upon initial detection of a bad odor to then start to measure the strength of the odor. Taking into account the spatial variation of the bad odor as well as environmental parameters the odor source may be identified. After the odor vanishes the sensor nodes return to sleep mode.