UH student proposes low-cost camera and open-source AI to map plastic flows in Houston bayous
A University of Houston student proposed using computer vision and cameras mounted on bridges to collect systematic data on plastic flows through Houston bayous, arguing bridge-based human counts are impractical on tall Houston spans and citing high detection rates in small creeks as evidence of feasibility.
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Josh Brown, a mechanical engineering student and ROTC member, told the Resilience Committee that long bridges and wide bayous make traditional human bridge-count methods impractical, and proposed piloting computer-vision monitoring to locate plastic sources and track debris movement. He described adapting open-source tools and mounting inexpensive cameras on bridges near campus and on routes such as MLK Boulevard to train models to local conditions.
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