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Qualaria

Every day you breathe around 30,000 liters of air

Every day you breathe around 30,000 liters of air

Qualaria

by Samuele Gori
Qualaria
Qualaria
Qualaria

What is it about?

Every day you breathe around 30,000 liters of air. Do you ever ask yourself what they contain ?

Qualaria

App Details

Version
1.2.1
Rating
NA
Size
48Mb
Genre
Health & Fitness Lifestyle
Last updated
November 16, 2020
Release date
May 8, 2020
More info

App Screenshots

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App Store Description

Every day you breathe around 30,000 liters of air. Do you ever ask yourself what they contain ?

Identify Hazards:
Qualaria constantly checks the air that you and your dear ones breathe at home or at work, it can detect multiple toxic and irritating substances, it enables you to isolate and understand the sources of indoor pollution.
It succeeds also at reporting odourless chemicals, it shows you the variations that occur over time through charts and real-time readouts and it warns you when your attention is required(*).

Enhance comfort and prevent risks:
Besides chemical pollutants, having temperature and humidity under control is a major concern in order to avoid mould, dust mites and prevent situations of discomfort, irritation or allergy.
Pathogens like viruses and bacteria are sensitive to environmental conditions as well and adjusting temperature and humidity enables you to address their spread.

Improve productivity in studying and at work:
Excessive carbon dioxide may interfere with your ability to solve problems, it makes you difficult studying or working.
Qualaria advises you when it is time to open the window, an easy action that helps immediately(*).

Qualaria gets you up-to-date even when you are not at home and under certain conditions it can operate without an Internet connection.

Charts and data at your fingertips:
Qualaria delivers an advanced chart technology on iOS with fast loading time of daily, weekly and monthly figures and an easy finger-tracking feature that allows you to map pricisely the time of occurence of indoor air pollution with the human actions which eventually produced it.
Furthermore you can get the realtime readouts from sensors both at home and anywhere else.
You only need an iOS device and a home Wifi network.

Environmentally friendly enclosure designed in Italy, made of solid sycamore maple wood carved by local craftmen:
Qualaria detects pollution in the premises you commonly live in trying in turn not to be a cause of pollution itself.
70% of its weight is made up of biodegradable materials, realised from solid wood and plant-derived plastics.
Remainder 30% can be easily disassembled at product end of life for proper disposal.
Every enclosure is carved in Italy by the skilled hands of specialised craftmen and it is unique.
Even packaging ensures low environmental impact, being made of recycled and recyclable non-whitened cardboard, water-based plant-derived inks, hemp and cork agglomerated with food glue.
A product similar to Qualaria with an identical respect for our planet simply does not exist.

Additional features:
Data download in CSV format.
Home automation connection with Third Party sites.
Updates.
Multi-user and Multi-product App.
Luminous and chromatic indications on air quality.

REQUIREMENTS

2.4 GHz Wi-Fi connection 802.11 b/g/n WPA/WPA2
iOS 12.2 or later
Free Qualaria account

Specifications

Formaldehyde 0-5000 ppb ±15 ppb (1)
tVOC 0-1000 ppb (1)
CO2eq 400-2000 ppm
Temperature -40/+125 C ±0.3 °C (2)
Relative Humidity 0-100 % RH ± 2% (2)
WIFI 2.4 GHz 802.11 b/g/n WPA/WPA2
Power Supply 5 V DC (microUSB)
Consumption max 1 W (0,3 mW in low power mode)
Operating conditions 0/+50 °C 15-90% RH
Dimensions 163 x 130 x 50 mm
App Language English / Italian
Included accessories Mains adapter, user manual,power chords 1.80/3.00 mt, hemp bag


(1) App automatically converts the readouts from ppb to µg/m3
(2) Sensor reading range may differ from device actual operating conditions
(*) Some characteristics may require user registration to Third Party sites as described in the manual.
(**) remote users have priority over local ones for reading real-time sensor data.

Disclaimer:
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