# Edge-Computing Meshed Wireless Acoustic Sensor Network for Indoor Sound Monitoring
## 1 Introduction
Specifically, the paper covers the conception of the network since selection and set-up of the hardware of the sensing nodes (including the selection and the calibration of the microphones) and the wireless communication protocol between them, to the comparison of different models of 3D printed boxes to protect the computing units of each node while preventing overheating. The proposed system should fit any indoor environment that aims to measure noise levels or detect acoustic events. One can find several contributions in the literature focused on the design of low-cost acoustic sensor networks to solve several different requirements, depending on their application. Those contributions can range from a simple WASN design [8], to a system already capable of executing, in real-time, several algorithms and uploading the results in the cloud [9]. The goal of the proposal presented in this paper, which clearly differs from other proposals in the literature, is to obtain the most precise acoustic sensor network with the lowest possible cost, assuming that precision, in this stage, stands for both the precision of acoustic measurements and future acoustic event detection algorithms. For this purpose, the requirements of both data collection hardware design and computational capabilities to develop signal processing algorithms have been considered. The precise comparison of our approach with regards to other proposals in the literature is widely discussed and detailed in the Discussion section of this paper (Section 6). Focusing more on the details and the proper contributions of this work, the most relevant issues presented in this paper are:  
1. The design of a general-purpose Wireless Acoustic Sensor Network, focusing on the design of the sensing nodes using a commercial computing unit and microphone. Different commercial computing units have been evaluated in terms of cost and capabilities. The selected computing unit is capable of performing edge-computing calculations, which enables acoustic signal processing to be carried out in the sensor without the need to send raw acoustic data to the cloud. Regarding the microphone, three different options have been evaluated in terms of cost, linearity and calibration capabilities. The plug-and-play selected option enables omnidirectional data to be obtained without the need for an external Analogue to Digital Converter. 2. The conception of a wireless meshed network topology to communicate the sensing devices in a Local Area Network (LAN), maximizing the coverage area of the network without using external hardware such as a router or a range extender. For this purpose, a real-world test has been carried out in a scenario composed of three rooms and one terrace, with a long distance among nodes. A comparison between using a direct connection from nodes to a central unit or a meshed topology has shown that the latter option enables us to drastically reducing the number of frames lost during the experiments. 3. The design of a coverage (i.e., a protecting 3D-printed box) to protect the hardware and also ensure that such hardware does not overheat, causing the computer unit to stop working in the worst situation. For this purpose, different models of custom 3D-printed boxes of different shapes and materials have been compared. In the experimental evaluation, identical stress tests have been carried out using different models of boxes. The results show that the physical design of the box greatly affects the temperature value reached in the sensor. The remainder of this paper is organized as follows: first, Section 2 explores the main relevant related works in the field; then, Section 3 explains how the hardware of the WASN has been conceived, including: (i) the design and assembly of different commercial elements for each sensing node, (ii) the acoustic calibration process carried out to guarantee heterogeneity among nodes and (iii) the design process of 3-D printed boxes to protect the hardware.