We were looking to create a resource by which people can access information regarding their air quality, but found out that the standard metrics for this technology do not have enough reach for everyone to access the local data that is most important to their health and well-being. Community Air Quality Database creates a specialized space to gather this data via SMS surveys and reporting tools and load the collected data onto a publicly available window.

What it does

Community Air Quality Database conglomerates individual analyses of air quality from a broad range of qualitative and quantitative responses to illustrate the state of a neighborhood. After registering their phone number in the general database and answering a small set of questions on the relationship between individual lung health and environmental factors (asthma, smoking, allergies), individuals receive regularly scheduled surveys to gather information on their neighborhood set-up and related health experiences (frequency of asthma attacks). Along with the surveys, the application is equipped with additional tools that can be accessed via special keywords. These tools can be used to report sources of pollution as well as associated concerns.

The application can be accessed by texting EXPLORE to 716-342-0401. Registration for weekly surveys and occasional facts about the effects of air pollution can be done by texting AIR to the same number; additional tools include POLLUTANT to report clear sources of pollution and CONCERN to make note of and get information regarding possibly destructive sources of pollution in a community.

All of this is done using regular SMS messages, so that users can text in their responses regardless of whether they have a smart phone or want to access a data plan. Additionally, the number (716-342-0401) can be saved in a phone contact list for convenient access.

How I built it

Using a digital phone number from Nexmo and Telerivet's SMS gateway technology, we were able to design the surveys and problem reporting devices. Using Google Fusion Tables, we were able to geocode this information onto maps.

Challenges I ran into

At first, we wanted to create a service that allowed people to gather information about their air quality based by ZIP code; however, we soon learned that most cities do a poor job of adequately measuring air quality on such a confined area. In fact, all air quality attributed to Buffalo, Batavia, and Alden, three towns separated by several miles and zoning types, is all measured by a center in Getzville. Therefore, there really is no way of accurately telling an individual what his or her neighborhood is experiencing that day in terms of environmental health. That's when we decided to change course and begin focusing more broadly on creating a storing site for that information, rather than trying to find it elsewhere.

Accomplishments that I'm proud of

This was the first time I had really built an SMS-based system fully focused on one topic; I had done some different experiments from time to time with using the technology for organizational purposes, but this was the first fully dedicated project I've worked on.

What I learned

Air quality is a complicated issue. While I think we have set up a solid base for which to develop a usable set of mobile tools, I know that it would require much more input in order to refine the process of knowledge gathering and to really take this fledgling application to a higher level as a truly usable resource. To clarify: because of the many factors influencing air quality, the process by which this data is collected and visualized will evolve over time; however, I believe that creating an open platform to see different facets of this project will only enable the improvement of techniques and the creation of a healthier society.

What's next for Community Air Quality Database

We would like to build a strong base of over 1,000 people in the city of Buffalo upon whom we will develop the standard conversations for these types of measurements. Using their responses, we would like to create a publicly available map of responses, showing trends between neighborhoods and districts of the presence of certain environmental factors that might be adversely effecting community health. Although we have not had much success in visualizing this yet, I believe that given enough time, we will be able to merge the Data Tables currently storing information with Google Fusion Tables to create maps which can be easily embedded into web pages. Thus, citizens will be enabled with the knowledge to understand different is impacting their neighborhood and how they can improve overall quality of life. Eventually, I believe that this same process can be duplicated and applied to all cities as an alternative method of gathering and disseminating knowledge regarding the health and quality of air.

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