Field Test of a Passive Infrared Camera for Measuring Trail-Based Physical Activity

Abstract

Introduction: Trails are ubiquitous and far-reaching, but research on the impact trails have on physical activity is limited by the lack of resource-efficient, accurate, and practical systematic observation tools. Commonly used infrared trail sensors count trail use and may broadly differentiate activity (i.e., bicyclist vs. pedestrian), but cannot detect nuances needed for outcomes research such as frequency, intensity, time, and type of activity. Motion-activated passive infrared cameras (PICs), used in ecological research and visitor management in wildlife areas, have potential applicability as a systematic observation data collection tool.Materials and Methods: We conducted a 7-month field test of a PIC as a systematic observation data collection tool on a hiking trail, using photos to identify each trail user's physical activity type, age, sex, and other characteristics. We also tallied hourly trail use counts from the photos, using Bland–Altman plots, paired t-tests, Concordance Correlation Coefficient, Kendall's Tau-b, and a novel inter-counter reliability measure to test concordance against concurrent hourly counts from an infrared sensor.Results: The field test proved informative, providing photos of 2,447 human users of the trail over 4,974 h of data collection. Nearly all of the users were walkers (94.0%) and most were male (69.2%). More of the males used the trail alone (44.8%) than did females (29.8%). Concordance was strong between instruments (p < 0.01), though biased (p < 0.01). Inter-counter reliability was 91.1% during the field study, but only 36.2% when excluding the hours with no detectable trail use on either device. Bland–Altman plots highlighted the tendency for the infrared sensor to provide higher counts, especially for the subsample of hours that had counts >0 on either device (14.0%; 694 h).Discussion: The study's findings highlight the benefits of using PICs to track trail user characteristics despite the needs to further refine best practices for image coding, camera location, and settings. More widespread field use is limited by the extensive amount of time required to code photos and the need to validate the PICs as a trail use counter. The future potential of PICs as a trail-specific PA research and management tool is discussed.

Trail Conditions and Community Use: Utilizing Geospatial Video to Guide the Adoption of a Spatial-Temporal Trail Audit Tool (STAT)

“…Trail audits can be particularly difficult to collect in rural communities challenged with vast space and limited resources [11]. Currently, trail use data collection methods include manually counting trail users with clickers or infrared video counters [20]. The former is time-intensive, and the latter has inaccuracies due to weather and wildlife interferences and cannot distinguish unique users [20].…”

“…Currently, trail use data collection methods include manually counting trail users with clickers or infrared video counters [20]. The former is time-intensive, and the latter has inaccuracies due to weather and wildlife interferences and cannot distinguish unique users [20]. Therefore, more efficient and accurate trail quality and use data collection methods are needed for practitioners and researchers focused on improving the current trail conditions and use.…”

Pre-Symptomatic Disease Detection in the Vine, Chrysanthemum, and Rose Leaves with a Low-Cost Infrared Sensor

“…In addition to the high cost of the hyperspectral and multispectral cameras, errors or incorrect information may result from hyperspectral, multispectral, and RGB digital images about plants' health, due to lighting conditions [19]. This sets important barriers for the commercial use of the above techniques in the open field and greenhouse crops, suggesting that hyperspectral sensors may be a viable solution to overcome many of these measurement limitations listed above [20].…”