Geo-tagged environmental noise measurement with smartphones: Accuracy and perspectives of crowdsourced mapping

Abstract

Environmental noise affects life and health within urban environments through interfering with sleep, rest, study and personal communication. Noise mapping is an important issue of local authorities but due to its requirements (staff, costs and frequency), the available data are limited or outdated. Our aim was to involve people with smartphones in the mapping process and to determine the accuracy of the measurements performed with these devices in a natural environment. The main questions were whether the measured data were dependent on the type of applied software and smartphones. We tested three software (Noise Watch, Noise Meter and Sound Level Meter) and 12 different smartphones. We evaluated the measurements with hypothesis testing and correlation analysis. Although the accuracy of smartphones was below the professional equipment, measurements can be conducted easily due to their availability; thus, a reliability analysis is important. We found that comparison between professional devices and smartphones in a laboratory was misleading as it lacks the environmental factors biasing the measurements. The best method to compare the measurements carried out with smartphones and professional Noise Meters was to use large number of measuring points in a heterogenic outdoor environment where the noise ranged from the low to large values. We revealed that both the applied software and smartphones have relevant effect on the measurements, and, although it is possible to use these devices for noise mapping, one should consider not to apply different software and smartphones. Accordingly, crowdsourcing is not a reliable data collection method because: (1) measurements should be supervised, (2) smartphones’ accuracy should be tested and (3) measurement circumstances should be the same. If any of these requirements are violated, the quality of the resulting maps can be questioned.