Projects 2011-2012

(UNT RET Site: NSF Grant #1132585)
Aquatic Sensor Aquatic Sensor Setup
Group Members:
  • Blaine Chamberlain, Newman Smith High School
  • Barbara Lightfoot, Krum High School
  • Sharon Wood, Marcus High School
  • Dr. Shengli Fu, UNT (Faculty Mentor)
  • Water quality variables, such as pH and temperature, affect the wellbeing of aquatic organisms. It is critical to monitor the water quality for both natural and artificial systems to ensure the survival of resident organisms. The goal of this project was to incorporate a Wireless Sensor Networks (WSN) in an aquatic system to establish a method of collecting temperature and pH data. The RET program allowed the team to explore various environmental conditions using WSN.

    Additionally, researching the literature was instrumental in establishing the parameters for testing the environment and conducting experiments. This program provided valuable experiences which will be shared with both district teachers and students. This technology is widely applicable in real life for management of moderate to large-size aquaria, ponds, rivers and streams.

(TEO) Data Analysis and Modeling: Neches River Data Analysis and Modelling Setup
Group Members:
  • Dawn Chegwidden, Lewisville High School
  • Kim Garrett, Northwest High School
  • Dr. Miguel Acevedo, UNT (Faculty Mentor)

The focus of this project was the creation of a hydrological balance model of the Neches River from the big Thicket National Preserve. The Big Thicket is a uniquely diverse ecosystem in the Neches River watershed, listed as an international Biosphere Reserve and as a Globally Important Bird Area. A general concern is that we must try to conserve our hydrological resources that sustain our very diverse ecosystems.

This RET group used existing and archived data to produce a robust environmental model that can be used to determine the hydrological balance of the lower Neches River Watershed. Stream flow and precipitation data were used for this model. The integration of long-term data takes into account trends and anomalies for the river providing great pictorial information on historical flows and changes over the years.

Sensor Data Processing: Soil Moisture Sensor Data Processing: Soil Moisture Experimental Setup
Group Members:
  • Randall Dupree, John H. Guyer High School
  • Laura De Lemos, Newman Smith High School
  • Dr. Xinrong Li, UNT (Faculty Mentor)

This three-part project focused on using Wireless Sensor Networks (WSN) to collect data on soil moisture using a probe. The three aspects included a demonstration, experiment, and a wireless automatic irrigation system.

For the demonstration portion, the WSN was used to define volumetric water content and to illustrate the power of the graphical programming environment in LabVIEW. For the experiment, the variation in soil moisture among four soil types (sand, silt, clay and potting soil) were monitored. Lastly, the group used the WSN and LabVIEW to create a wireless automatic irrigation system calibrated from the data of the experiment. The concepts and designs developed in this RET project can be used in the real world for automatically watering plants.