**Mission Statement/Research Question:** How can we monitor water health data in a low-cost, accessible, and reliable way? **Project Brief:** Currently, there is a high cost and low frequency at which data is being collected on the Red Cedar watershed. From a political lens, perhaps more grants can be allocated to establish a steady flow of money towards monitoring. But even with political support and economic means, the hardware and processes involved with monitoring put volunteer health at risk. Nevertheless, this data is important to collect because it can help us pinpoint sources of nitrogen and phosphorus pollution as well as areas that are at most risk to have unsafe levels of nitrates in drinking water. Thus, our key motivation for this summer’s research was to find a remote, wireless method to collect lake data, and prove that it worked for a couple of different data types. We made a prototype that we call the MenomiNet. Using the Lake Erie project as our key precedent, we made a water quality buoy to monitor lake health metrics such as temperature, turbidity, pH, and dissolved oxygen(DO). In We also made a framework for a dashboard that could be updated to include more nodes in more locations. In the future, we hope chlorophyll, special conductivity, and water depth can be monitored by this sensor network. We also hope the pipeline between the LoRA network and a website or app is more thoroughly explored. Communicating the MenomiNet data publicly may help connect more people to the watershed issue. The MenomiNet in its complete version will consist of a chain link of LoRA nodes, each outfitted with an Arduino network of sensors. The LoRA's will communicate the data back to home base in a relatively frequent time interval, for instance, hourly. The photo below depicts one of many possible layouts for the network. **Project Team** - Sahi Chundu - Cody Lundquist - Devin R. Berg (advisor) **Links** - Poster: [10.5281/zenodo.6977169](https://doi.org/10.5281/zenodo.6977169) *This work is supported by the National Science Foundation under Grant No. SMA-1950289. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. Additional support was provided by the Fresh Water Collaborative of Wisconsin.*
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