Assessment and Accuracy Improvement of Pyroelectric Sensors (Eco-Counter) Based on Visitors Count in National Park. The Case: Monitoring System of Tourist Traffic in Stołowe Mountains National Park, Poland

• Published in: Environmental and Climate Technologies Vol. 26; no. 1; pp. 182 - 198
• Main Authors: Rogowski, Mateusz, Piotrowski, Krzysztof
• Format: Journal Article
• Language: English
• Published: Riga Sciendo 01.01.2022; Riga Technical University
• Subjects: Calibration; Data collection; eco-counter; Error reduction; Intervals; Monitoring; Monitoring systems; Mountains; national park; National parks; Onsite; pyroelectric sensor; Sensors; Tourism; Tourists; Traffic management; Typology; visitor flow; Poland
• ISSN: 2255-8837; 1691-5208; 2255-8837
• DOI: 10.2478/rtuect-2022-0015

The monitoring of tourist traffic helps to manage tourism in national parks. Today park managers and researchers use many different devices and technologies that facilitate data collection. Among these often used devices is the pyroelectric sensor. Despite its high degree of usefulness, this type of sensor can miscalculate. Therefore, there is a need to assess the magnitude of errors and the circumstances in which they occur. The purpose of the study was to evaluate pyroelectric sensor counting errors in relation to different visitor flow levels and time intervals between visitors. The study was based on a field experiment and on-site observations using pyroelectric sensors, part of the Monitoring System of tourist traffic (MSTT) in Stołowe Mountains National Park in Poland. The outcome of the assessment was the errors sizes and types and calibration formula. Pyroelectric sensors more often overcount than undercount. Errors occur in larger than 6-visitor groups and time intervals between visitors shorter than 3 seconds. Finally, the analysis of the causes of errors gave the ground to generate the typology of error circumstances. The calibration formula was generated based on a field experiment and on-site observation. The average error size was reduced from ±13 % to ±6 %. The calibration formula provided in the study is simple and universal and can be applied to other data.