Developing a User-Driven Framework for Generating Field Data Collection Applications
Format
SOECS Senior Project Demonstration
Faculty Mentor Name
Michael Doherty
Faculty Mentor Department
Computer Science
Additional Faculty Mentor Name
Jinzhu Gao
Abstract/Artist Statement
The Environmental Restoration Department at Lawrence Livermore National Laboratory (LLNL) collects field data in and around LLNL’s sites in their effort to remove contaminants (from historical operations) from the underground water supply to keep it clean and compliant with drinking water standards. ERD began this project to decontaminate the water supply over 35 years ago, and their efforts so far have exceeded expectations. However, when samplers go out to the wells around the sites to draw water for testing, they must bring handwritten forms that they print out before they leave their office and write their data down on them. I have developed a framework in which samplers can design their data collection form on a mobile device, and then take that mobile device out into the field and use that to record measurements. The application is designed to be able to be deployed offline, so it may be used in places without an Internet connection. This framework addresses two key concerns for data collection – it completely eliminates the use of handwritten forms in data collection, and also gets rid of paper-to-database transcription errors. Using their mobile application, samplers can upload their data from their device straight to the database when they have returned to an area with Internet access, using a pre-existing tool. This framework will save a considerable amount of money for the lab by halving the average total amount of time taken to collect data and eliminating printing costs.
Location
School of Engineering & Computer Science
Start Date
2-5-2015 2:30 PM
End Date
2-5-2015 4:30 PM
Developing a User-Driven Framework for Generating Field Data Collection Applications
School of Engineering & Computer Science
The Environmental Restoration Department at Lawrence Livermore National Laboratory (LLNL) collects field data in and around LLNL’s sites in their effort to remove contaminants (from historical operations) from the underground water supply to keep it clean and compliant with drinking water standards. ERD began this project to decontaminate the water supply over 35 years ago, and their efforts so far have exceeded expectations. However, when samplers go out to the wells around the sites to draw water for testing, they must bring handwritten forms that they print out before they leave their office and write their data down on them. I have developed a framework in which samplers can design their data collection form on a mobile device, and then take that mobile device out into the field and use that to record measurements. The application is designed to be able to be deployed offline, so it may be used in places without an Internet connection. This framework addresses two key concerns for data collection – it completely eliminates the use of handwritten forms in data collection, and also gets rid of paper-to-database transcription errors. Using their mobile application, samplers can upload their data from their device straight to the database when they have returned to an area with Internet access, using a pre-existing tool. This framework will save a considerable amount of money for the lab by halving the average total amount of time taken to collect data and eliminating printing costs.