Wireless Sensor Networks for Noise Measurement and Acoustic Event Recognitions in Urban Environments

Abstract

Nowadays, urban noise emerges as a distinct threat to people’s physiological and psychological health. Previous works mainly focus on the measurement and mapping of the noise by using Wireless Acoustic Sensor Networks (WASNs) and further propose some methods that can effectively reduce the noise pollution in urban environments. In addition, the research on the combination of environmental noise measurement and acoustic events recognition are rapidly progressing. In a real-life application, there still exists the challenges on the hardware design with enough computational capacity, the reduction of data amount with a reasonable method, the acoustic recognition with CNNs, and the deployment for the long-term outdoor monitoring. In this paper, we develop a novel system that utilizes the WASNs to monitor the urban noise and recognize acoustic events with a high performance. Specifically, the proposed system mainly includes the following three stages: (1) We used multiple sensor nodes that are equipped with various hardware devices and performed with assorted signal processing methods to capture noise levels and audio data; (2) the Convolutional Neural Networks (CNNs) take such captured data as inputs and classify them into different labels such as car horn, shout, crash, explosion; (3) we design a monitoring platform to visualize noise maps, acoustic event information, and noise statistics. Most importantly, we consider how to design effective sensor nodes in terms of cost, data transmission, and outdoor deployment. Experimental results demonstrate that the proposed system can measure the urban noise and recognize acoustic events with a high performance in real-life scenarios.

Challenges, Applications, and Future of Wireless Sensors in Internet of Things: A Review

“…To prevent human health from these adverse effects, the environmental monitoring is becoming a fundamental thing and is being made possible because of WSs [87]. In an urban environment, a study have been proposed in [72] for measuring the different noise levels in real time using the WS nodes.…”

Advances in the Development of Innovative Sensor Platforms for Field Analysis

“…For example, in 2018, Risojević et al [80] optimized the performances of limited computational resources and cheap devices (any node costs about 41 €) to obtain a system able to monitor the environmental noise for several days with a precision similar to that reachable with professional sound meter devices. Recent advances have led to the implementation of this approach not only to map the noise pollution in outdoor environment, but also to gather sound data that can be analyzed by a server through convolutional neural networks in order to classify them by individuating their source, as well as allowing the user able to receive and visualize noise maps, acoustic events information, and noise statistics in a defined area [81].…”

Passive Extraction of Signal Feature Using a Rectifier with a Mechanically Switched Inductor for Low Power Acoustic Event Detection

“…The recognition of infrequent events is of interest in many fields (environmental monitoring [ 1 , 2 , 3 , 4 , 5 ], safety and security [ 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 ], communication [ 14 , 15 , 16 ], agriculture, health monitoring [ 17 ]). It requires continuous operation of an electronic system comprising sensing, detection and recognition functions, which are power-hungry tasks [ 7 , 18 ].…”