| Summary: | The miniSASS was developed as a citizen science tool for monitoring the health of river systems and reflecting the water quality through assessing macroinvertebrates communities. The miniSASS samples the macroinvertebrate community in a river reach and compares the community present to the expected community under ideal natural conditions. The information garnered during a survey relies heavily on the accurate identification of macroinvertebrates by lows killed citizen scientists. This leaves a potential for errors in identification which may impact the accuracy of results and, ultimately, of the river health assessment. In response, we initiated the development of a smartphone application with built-in machine-learning algorithms for the automatic, real-time identification of macroinvertebrates. This report presents our data, methodology, and preliminary results from the automated identification algorithms.
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