A model for implementing vibration and sound heatmaps in smart cities based on crowdsensing data

Abstract

This paper aims to establish a model that can utilize vibration and sound heatmaps in smart traffic using Internet of things, mobile and web technologies. The developed system should be able to monitor and collect information using crowdsensing technology, as well as provide the current status of the environment. The final objective of the model is to generate visual heat maps related to perceptual attributes (e.g. ‘calm’, ‘pleasant’, ‘unbearable‘) with collected vibrations and sounds as a starting point. The proposed system is developed through these main stages: (1) Vibration and sound sources recognition (2) Profiling of the sources (3) Prediction of perceptual measures divided by the area (4) Implementation of vibration and sound heatmaps. This research is specifically focusing on the last two stages (predictions and implementation). These stages are broken down into smaller phases with methodology and processes described in detail. The model of the developed system was realized through measured vibrations and sound data in urban transportation in Novi Sad city. Finally, we present the research results from the analysis paradigm and provide suggestions for its implementation.