Project Description

Introduction

Global climate change is an issue that will affect every person on the planet. It is widely acknowledged that climate change is driven by rising levels of atmospheric carbon dioxide (CO2) resulting from fossil fuel burning.  The importance of research into climate change cannot be understated, but when people think of data associated with climate change they typically think of the carbon footprint of our cities. They often forget that the environment and its carbon cycle hold data that is just as, if not more, valuable. Our goal is to ensure that ecologists can collect data as quickly, efficiently, and as easily as possible from the environment.

Our team, CO2 Software, has been asked to design an application for Northern Arizona University, with the guidance of our sponsors Doctor Andrew Richardson and Doctor Mariah Carbone.  The Richardson-Carbone Lab studies carbon cycling in forest ecosystems. The research is used to understand the balance between carbon uptake (photosynthesis by plants) and release (respiration both by living and growing plants, as well as by microorganisms decomposing dead organic matter in the soil).

The Problem

Currently, the Richardson-Carbone Lab has to use a cumbersome set of equipment to conduct their research. Unfortunately, the technology required for his research, a laptop and the LI-840A Gas Analyzer, is not very mobile and can provide a good deal of inconvenience and time loss. The data cannot be viewed easily out in the field. In the original method, the data was just a text file filled with unreadable raw data. Furthermore, the current method offers no way to analyze the data. There was no mobile alternative to the software being used, until now.

The Solution

Our Solution involves designing a mobile application that can replicate and improve the functionality of the software being used on Richardson’s laptop. The application they have asked us to design reads in data from the LI-840A gas analyzer. This allows for research to be conducted much faster, saving both time and energy. It does this by allowing metadata input for datasets, letting the user easily view the datasets, computing statistical analysis on the datasets, and letting the user get the datasets out of the application. The data displayed is updated in real time so one can easily monitor the output of a particular organism.

High Level Requirements

In order to solve these issues for our client, we have developed an application for mobile Android devices that can be used to measure and record data in conjunction with their LI-840A gas analyzer. The application’s interface is designed with a tablet in mind, as the large screen real estate allows for a higher level of detail. The application uses data visualization tools to render a series of graphs that displays the gas analyzer’s reported data in real time. The software also provides several means of statistical analysis so the user can generate the information as needed with the convenience of staying within a single application. Finally the application can transfer data out via email with convenient naming conventions of the files. With all of the tools being readily available on a tablet device, any researcher out in the field will no longer be burdened with having to carry a laptop or any other peripheral devices in order to collect and analyze data.

The data our application uses is collected from the gas analyzer itself. The LI-840A can communicate with the Android device by utilizing a direct usb-to-serial connection, and the data is transferred directly to it. The data is delivered in a simple, XML style format, with clear name labels for every measurement the analyzer provides. Originally, the project was envisioned as using a Raspberry Pi as a middleman between the LI-840A and the Android device. However, we decided that the ultimate goal of this project was to make a product that was as compact and mobile as possible, and omitting an additional data transfer point was an obvious decision. The application have developed replaces the need for such a setup by providing a mobile alternative, while preserving all of the benefits offered by the originally used software.

The interface of the app has involve multiple windows, the primary one being the Graph Screen screen. Using the GraphView library, we read in the data stream and graph it onto the screen in real time. There is a built-in functionality in GraphView to allow the graphs that are displayed in the app to be manipulated in size and visibility by the user using simple touch commands. This fulfills the requirements of both having real time data display as well as having that display be adjustable by the user.

Any subset data that is logged in the application is immediately saved after the the user stops the logging. The user can access these data logs in a window accessible from the File Directory Screen, choosing them from a list. In order to avoid visual clutter and confusion for the user, there are metadata elements associated with every subset of data. The initial values for metadata include things such as a name, the Sample ID, an image, and GPS coordinates. This allows for the user to save all of the data they record with our app, and then be able to easily identify and access it later.

It should be noted that this software is not exclusive to just researchers aiming to shrink the size of their research kit. Any researcher that finds our application’s interface accessible or its statical analysis tools to be of use can employ our product in their work. It could potentially increase the productivity of countless researchers across the entire field.