Devavardhan Bajla
Pronouns: He/Him
Research Mentor(s): Branko Kerkez
Co-Presenter:
Research Mentor School/College/Department: Civil and Environmental Engineering / Engineering
Presentation Date: April 20
Presentation Type: Poster
Session: Session 1 – 10am – 10:50am
Room: League Ballroom
Authors: Devavardhan Bajla, Meagan Tobias
Presenter: 19
Abstract
The Digital Water Lab focuses on improving the way water resources are managed by collecting accurate data about them. This allows us to better understand waterways and make better decisions about their stewardship. Collecting data from a number of different sites and continuously sending them to the cloud allows for a more dynamic and higher-resolution understanding of waterways in real-time. This is done through depth and pressure sensor nodes that can remotely stream measurements, and the autosampler, which periodically collects water samples that are later analyzed for sediment content. This project focused on maintaining depth sensor nodes, carrying out total suspended solids (TSS) sampling in-lab, and upgrading the autosampler firmware. Maintaining depth sensor nodes involves deploying and retrieving sensors from the field, followed by repairing and reprogramming them in the lab. We set up the capability to run TSS samples in-lab to reduce the time and resources needed to process field measurements. This allows for more samples to be collected for use in future experiments. To collect more interesting samples at specific times, the autosampler firmware was upgraded to more easily wirelessly trigger when to collect a sample. Currently, the autosampler only follows its preset sampling frequency, which can only be changed while it is active. This has caused a large lag in the past and prevented samples from being collected during a storm event. Upgrading this system will allow the autosampler to be more adaptable to river conditions, and this can be expanded upon to automatically adjust the sampling rate based on real-world conditions and forecasts. As a whole, this project improves the quality of the current data collection system that has already been set up by making it more flexible and efficient.
Engineering, Interdisciplinary
