VrauuRalla| A One Health Approach
A One Health Approach
AR.SAVE
Summary
AR.SAVE is a device that measures the presence of pollutants in indoor and outdoor air using a Raspberry Pi Zero with an exhaust fan attached and connected to electrochemical sensors in order to detect toxic gases in the air mixture, along with a GPS tracking system and biochemical sensors for harmful organisms. The data will be processed by the sensors and be sent in communication with a standard ZigBee Mesh network with extension with the Ethernet Shield, allowing the information to be stored in a database and the network to be accessed by a website with an informative graphic interface.
How We Addressed This Challenge
The Air is analyzed by the electrochemical and chemical sensors present in the Raspberry Pi Zero capturing polluting gases and air particles containing microorganisms such as bacteria and fungi and the data stored in a proprietary database will be transmitted both to a website in order to educate the citizen about air quality in its proximity, as well as to be related to NASA satellite data in order to study the relationship between air pollution and the presence of pathogens.
The importance of this device is to improve the study on air pollution in the terrestrial globe and its effects, making the information obtained a form of pollution index for research, so that they can articulate a more objective and effective solution to study cause and effect relationships between pollutants, and inform the population about the quality of the air around them.
How We Developed This Project
Inspired by data available by NASA (Air quality from space) on air quality, reporting on the increase in pollution and the high mortality rate, reaching 1 in 9 deaths across the globe, in addition to which components of our team also have problems related to airways (asthma), we seek to use our interdisciplinary knowledge to cause a positive and highly relevant impact in the research community and in the popularization of knowledge of air pollution indexes.
In this project, we decided to add the knowledge of everyone in the group and produce a device that could help people and mainly scientists so that they can study more quickly and objectively the effects of air pollution in a given location.
To structure our prototype, both physical and virtual, for our device and graphical website interface, we use 3 main software:
First, we used AutoCad to model the device box with the filaments for the air passage, coupled exhaust fan and compartment for the Raspberry Pi Zero and the electrochemical biosensors with future simulation of the passage of air fluids through the device. We also use Marvel and Photoshop to create the prototype of the visual interface of our website with screens that expose our proposal for UX / UI design and some examples of data displayed graphically.
One of the challenges we face most was how to network the data collected by the device for use on the website and in research with NASA databases, especially in areas where there is no internet signal, which threatens portability of the device in different environments.To solve this problem we proposed to adopt a Mesh network communication, using the ZigBee standard with an Ethernet Shield extension that allows the Raspberry Pi Zero to store the information obtained in the database on a local network, there is a connection between the internet nodes, the network will be accessed remotely through our website
How We Used Space Agency Data in This Project
NASA data on the use of GPS, making it possible to obtain information from different regions.
Data from NASA in the article (Air quality from space) regarding the increase of pollutants in the air, a great motivator for us to carry out the challenge and study the progression, relationships and consequences of this phenomenon.
NASA data via EOSDIS Worldview satellite on the concentration of pollutants in certain regions that will be used in conjunction with the data collected by our device (AR.SAVE) in order to specify the concentrations of pollutants in more specific areas within the regions covered by satellites and the specific and comprehensive relationships of air pollution data addressed with pathogen detection data in the bank of our device.
Project Demo
SLIDES:
https://docs.google.com/presentation/d/1HbsuZmU8s0LCw5wQO69qurlfP7MDy3G5ndDW6Bq2j6Q/edit?usp=sharing
30s video EN:
https://youtu.be/Nyljer-qEaI
3min video PT/BR:
https://www.youtube.com/watch?v=U-ts1lRhju4&feature=youtu.be
Data & Resources
http://www.ibram.df.gov.br/wp-content/uploads/2018/03/IQAR-utilizado-pelo-IBRAM.pdf
https://periodicos.unifor.br/tec/article/viewFile/5275/4125
https://www.arca.fiocruz.br/bitstream/icict/8254/2/148.pdf
https://revistapesquisa.fapesp.br/sensor-detecta-microorganismos/
https://airquality.gsfc.nasa.gov/
https://worldview.earthdata.nasa.gov/
https://www.nasa.gov/directorates/heo/scan/communications/policy/what_is_gps
https://qastack.com.br/iot/286/why-are-mesh-networks-used-more-frequently-for-iot-networks
http://www.eng-automacao.araxa.cefetmg.br/wp-content/uploads/sites/152/2018/12/TCC-ARIF-Vers%C3%A3o-FinalCefetMG.pdf
https://apps.who.int/iris/bitstream/handle/10665/164348/E92645.pdf;jsessionid=F443335EA6F6F82880E014693D33E929?sequence=1