Sound source localization is a well-researched subject with applications ranging from localizing sniper fire in urban battlefields to cataloging wildlife in rural areas. One critical application is the localization of noise pollution sources in urban environments, due to an increasing body of evidence linking noise pollution to adverse effects on human health. Current noise mapping techniques often fail to accurately identify noise pollution sources, because they rely on the interpolation of a limited number of scattered sound sensors. Aiming to produce accurate noise pollution maps, we developed the SoundCompass, a low-cost sound sensor capable of measuring local noise levels and sound field directionality. Our first prototype is composed of a sensor array of 52 Microelectromechanical systems (MEMS) microphones, an inertial measuring unit and a low-power field-programmable gate array (FPGA). This article presents the SoundCompass’s hardware and firmware design together with a data fusion technique that exploits the sensing capabilities of the SoundCompass in a wireless sensor network to localize noise pollution sources. Live tests produced a sound source localization accuracy of a few centimeters in a 25-m2 anechoic chamber, while simulation results accurately located up to five broadband sound sources in a 10,000-m2 open field.

The massive production of microphones for consumer electronics, and the shift from dedicated processing hardware to PC-based systems, opens the way to build affordable, extensive noise measurement networks. Applications include e.g. noise limit and urban soundscape monitoring, and validation of calculated noise maps. Microphones are the critical components of such a network. Therefore, in a first step, some basic characteristics of 8 microphones, distributed over a wide range of price classes, were measured in a standardized way in an anechoic chamber. In a next step, a thorough evaluation was made of the ability of these microphones to be used for environmental noise monitoring. This was done during a continuous, half-year lasting outdoor experiment, characterized by a wide variety of meteorological conditions. While some microphones failed during the course of this test, it was shown that it is possible to identify cheap microphones that highly correlate to the reference microphone during the full test period. When the deviations are expressed in total A-weighted (road traffic) noise levels, values of less than 1 dBA are obtained, in excess to the deviation amongst reference microphones themselves.

Wireless Sensor Networks (WSNs) have permeated the entire fabric of academic disciplines that greatly rely on control and decision-making processes such as medical health care, agriculture, ecology and industrial automation. In ecology, an infrastructure consisting of networks of interconnected sensors can provide in-situ high-precision monitoring of natural phenomena at a large-scale. Moreover, WSNs provide a number of advantages to ecoinformatics such as the possibility of constructing quality datasets that coupled to machine learning-based prediction systems, can be used for ecological and process modelling. In this manuscript, we present a survey on recent WSNs based on several fields related to environmental research e.g. ecoinformatics, precision agriculture and wildlife observation. Finally, we have focused on the identification of limitations and open problems therein.

Bluetooth Mesh is a new communications protocol for connecting Bluetooth Low Energy devices in a mesh network; it originates as an alternative solution for home and office automation applications. Being a relatively new technology, there is a need to test Bluetooth Mesh in a realistic working environment to asses its strengths and weaknesses. We implemented a basic proof-of-concept Bluetooth Mesh network in our office building for a well-known office automation application: a smart doorbell. The smart doorbell uses Bluetooth Mesh technology to send and receive event messages inside a building and expand its reach with relay nodes. The network nodes were designed in-house according to the requirements of the application. This paper explores the design in hardware and software of a Bluetooth Mesh network in a real environment considering some evaluation metrics, such as package loss across distance and power consumption. It reports some issues regarding energy consumption and relay features. Results show that this technology performed well in our building automation application when considering factors such as radio transmission power and environment settings to achieve optimal functioning.