One of the main aspects affecting the quality of life of people living in urban and suburban areas is their continued exposure to high Road Traffic Noise (RTN) levels. Until now, noise measurements in cities have been performed by professionals, recording data in certain locations to build a noise map afterwards. However, the deployment of Wireless Acoustic Sensor Networks (WASN) has enabled automatic noise mapping in smart cities. In order to obtain a reliable picture of the RTN levels affecting citizens, Anomalous Noise Events (ANE) unrelated to road traffic should be removed from the noise map computation. To this aim, this paper introduces an Anomalous Noise Event Detector (ANED) designed to differentiate between RTN and ANE in real time within a predefined interval running on the distributed low-cost acoustic sensors of a WASN. The proposed ANED follows a two-class audio event detection and classification approach, instead of multi-class or one-class classification schemes, taking advantage of the collection of representative acoustic data in real-life environments. The experiments conducted within the DYNAMAP project, implemented on ARM-based acoustic sensors, show the feasibility of the proposal both in terms of computational cost and classification performance using standard Mel cepstral coefficients and Gaussian Mixture Models (GMM). The two-class GMM core classifier relatively improves the baseline universal GMM one-class classifier F1 measure by 18.7% and 31.8% for suburban and urban environments, respectively, within the 1-s integration interval. Nevertheless, according to the results, the classification performance of the current ANED implementation still has room for improvement.

The consistent growth in human life expectancy during the recent years has driven governments and private organizations to increase the efforts in caring for the eldest segment of the population. These institutions have built hospitals and retirement homes that have been rapidly overfilled, making their associated maintenance and operating costs prohibitive. The latest advances in technology and communications envisage new ways to monitor those people with special needs at their own home, increasing their quality of life in a cost-affordable way. The purpose of this paper is to present an Ambient Assisted Living (AAL) platform able to analyze, identify, and detect specific acoustic events happening in daily life environments, which enables the medic staff to remotely track the status of every patient in real-time. Additionally, this tele-care proposal is validated through a proof-of-concept experiment that takes benefit of the capabilities of the NVIDIA Graphical Processing Unit running on a Jetson TK1 board to locally detect acoustic events. Conducted experiments demonstrate the feasibility of this approach by reaching an overall accuracy of 82% when identifying a set of 14 indoor environment events related to the domestic surveillance and patients’ behaviour monitoring field. Obtained results encourage practitioners to keep working in this direction, and enable health care providers to remotely track the status of their patients in real-time with non-invasive methods.

This paper presents two digital transmission techniques for long haul ionospheric links. Since 2003 we have studied the HF link between the Antarctic Spanish Base, Juan Carlos I, and Spain; and we have described the link in terms of availability, signal-to-noise ratio, and delay and Doppler power profile. Based on these previous studies we have developed a test bed to investigate two digital transmission techniques, i.e., Direct-Sequence Spread Spectrum (DSSS) and Orthogonal Frequency Division Multiplexing (OFDM), which can provide a low power, low-rate ionospheric data link from Antarctica. Symbol length, bandwidth, and constellation are some of the features that are analyzed in this work. Data gathered from the link throughout the 2010/2011 and 2011/2012 Antarctic surveys show that the spread spectrum techniques can be used to transmit data at low rate when the channel forecast is poor, but when the channel forecast is good multicarrier techniques can be used to transmit sporadic bursts of data at higher rate.

La Salle and Ebro Observatory have been involved in remote sensing projects in Antarctica for the last 11 years (approximately one solar cycle). The Ebro Observatory has been monitoring and analyzing the geomagnetic and the ionospheric activity in the Antarctic Spanish station Juan Carlos I (ASJI) (62.7• S, 299.6• E) for more than eighteen and ten years, respectively. La Salle has two main goals in the project. The first one is the data transmission and reception from Antarctica to Spain to obtain a historical series of measurements of channel sounding of this 12,760-km ionospheric HF (high frequency) radio link. The second one is the establishment of a stable data low power communication system between the ASJI and Cambrils, Spain (41.0• N, 1.0 • E), to transmit the data from the remote sensors located on the island. In this paper, both narrowband and wideband soundings have been carried out to figure out the channel availability performed using a frequency range from 2 to 30 MHz with 0.5 MHz step during the 24 h of the day, encompassing wider channel measurements than previously done, in terms of hours and frequency. This paper presents the results obtained for the austral summer in 2014, using a monopole antenna at the transmitter and an inverted V on the receiver side. These results led us to the final physical layer design for the long Remote Sens. 2015, 7 11713 haul link, dividing the day into two parts: daytime, with low data throughput design, and nighttime, reaching high data throughput.

Nowadays, more than half of the world’s population lives in urban areas. Since this proportion is expected to keep rising, the sustainable development of cities is of paramount importance to guarantee the quality of life of their inhabitants. Environmental noise is one of the main concerns that has to be addressed, due to its negative impact on the health of people. Different national and international noise directives and legislations have been defined during the past decades, which local authorities must comply with involving noise mapping, action plans, policing, and public awareness, among others. To this aim, a recent change in the paradigm for environmental noise monitoring has been driven by the rise of Internet of Things technology within smart cities through the design and development of wireless acoustic sensor networks (WASNs). This work reviews the most relevant WASN-based approaches developed to date focused on environmental noise monitoring. The proposals have moved from networks composed of high-accuracy commercial devices to the those integrated by ad hoc low-cost acoustic sensors, sometimes designed as hybrid networks with low and high computational capacity nodes. After describing the main characteristics of recent WASN-based projects, the paper also discusses several open challenges, such as the development of acoustic signal processing techniques to identify noise events, to allow the reliable and pervasive deployment of WASNs in urban areas together with some potential future applications.