COLLABORATIVE NOISE MAPPING USING SMARTPHONE

11 citations as recorded by crossref.

1. Reducing Data Requirements for Simple and Effective Noise Mapping: A Case Study of Noise Mapping Using Computational Methods and GIS for the Raebareli City Intersection M. Zafar et al. https://doi.org/10.3390/acoustics5040061
2. Smartphones, a tool for noise monitoring and noise mapping: an overview A. Padilla-Ortiz et al. https://doi.org/10.1007/s13762-022-04240-6
3. Investigating Noise Mapping in Cities to Associate Noise Levels with Sources of Noise Using Crowdsourcing Applications E. Othman et al. https://doi.org/10.3390/urbansci8010013
4. Spatial modeling of ambient traffic noise using open data S. Popović https://doi.org/10.5937/tehnika2501031P
5. Use of noise prediction models for road noise mapping in locations that do not have a standardized model: a short systematic review G. Meller et al. https://doi.org/10.1007/s10661-023-11268-9
6. Using a Clustering Method to Detect Spatial Events in a Smartphone-Based Crowd-Sourced Database for Environmental Noise Assessment A. Boumchich et al. https://doi.org/10.3390/s22228832
7. Sequential Clustering Phases for Environmental Noise Level Monitoring on a Mobile Crowd Sourcing/Sensing Platform F. Alhazemi https://doi.org/10.3390/s25051601
8. GIS Based Road Traffic Noise Mapping and Assessment of Health Hazards for a Developing Urban Intersection M. Zafar et al. https://doi.org/10.3390/acoustics5010006
9. General Review of Smartphone Usability in Noise Mapping F. Omar & B. Bostancı https://doi.org/10.34248/bsengineering.1425362
10. Determination of Point-to-Point 3D Routing Algorithm Using LiDAR Data for Noise Prediction S. Bharadwaj et al. https://doi.org/10.3390/asi5030058
11. Spatial attenuation characteristics and influencing factors of traffic noise in high-density cities: A case study of Tianjin, China Z. Zhou et al. https://doi.org/10.1051/aacus/2025034