The accuracy of trail cameras to aid manual identification and counts of items placed in separate collection bins of recyclables.

Checking each item placed in a separate collection bin of recyclables to examine contamination is often difficult for a researcher relying on such data. This is because of the time and inconvenience involved to manually identify items. We test a proof-of-concept experiment on the ability of trail cameras to identify items placed within separate collection bins. After a pre-test of seven camera models, we selected one with the best image quality. We use this camera for lab and field trials to count the number of identifiable items based on photos compared to manual hand-counts of the items. Three lab trials of this camera resulted in an average of 82% accuracy in item identification. We then conducted a field experiment, testing photo quality to identify items in six separate collection bins across a university campus over a one-month period with a total of over 9,700 photos. Of the 1343 items placed in the separate collection bins, the trail cameras provided photographs of high enough quality such that successful identification occurred for 68.5% of the items, with poor identification for paper items and small items. We conclude that trail cameras can be useful for data collection in separate collection behavior, especially for items with the largest surface size greater than a credit card.