Marcos Hervás

Narrowband and Wideband Channel Sounding of an Antarctica to Spain Ionospheric Radio Link

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.

Physical Layer Definition for a Long-Haul HF Antarctica to Spain Radio Link

La Salle and the Observatori de l’Ebre (OE) have been involved in a remote sensing project in Antarctica for the last 11 years. The OE has been monitoring the geomagnetic activity for more than twenty years and also the ionospheric activity of the last ten years in the Spanish Antarctic Station Juan Carlos I (ASJI) (62.7 ° S, 299.6 ° E). La Salle is finishing the design and testing of a low-power communication system between the ASJI and Cambrils (41.0 ° N, 1.0 ° E) with a double goal: (i) the transmission of data from the sensors located at the ASJI and (ii) the performance of an oblique ionospheric sounding of a 12,760 km HF link. Previously, La Salle has already performed sounding and modulation tests to describe the channel performance in terms of availability, Signal-to-Noise Ratio (SNR), Doppler spread and delay spread. This paper closes the design of the physical layer, by means of the channel error study and the synchronization performance, and concludes with a new physical layer proposal for the Oblique Ionosphere Sounder. Narrowband and wideband frames have been defined to be used when the oblique sounder performs as an ionospheric sensor. Finally, two transmission modes have been defined for the modem performance: the High Robustness Mode (HRM) for low SNR hours and the High Throughput Mode (HTM) for the high SNR hours.

homeSound: Real-Time Audio Event Detection Based on High Performance Computing for Behaviour and Surveillance Remote Monitoring

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.

Flexible Low-Cost SDR Platform for HF Communications: Near vertical incidence skywave preliminary results.

A new low-cost reconfigurable software-defined radio (SDR) platform for high-frequency (HF) applications is presented in this article. The platform can work in the entire HF band (3-30 MHz), with bandwidths up to 36 kHz. We present the preliminary results working in a near vertical incidence skywave (NVIS) communication, where only the frequency range 3- 12 MHz is needed. The modem has been designed so that the modulations to be used, time frames, and scheduling can be completely reprogrammable in both narrow-band and wide-band modes. This is a strong advantage, because tests can be redesigned and reprogrammed to evaluate channel performance, which is not only important for research purposes but also for its final application in emergency communications in the NVIS propagation case of study. The transmission can be adapted to the best propagation frequency at every moment by means of a previous sounding analysis.

An FPGA-Based WASN for Remote Real-Time Monitoring of Endangered Species: A Case Study on the Birdsong Recognition of Botaurus stellaris

Fast environmental variations due to climate change can cause mass decline or even extinctions of species, having a dramatic impact on the future of biodiversity. During the last decade, different approaches have been proposed to track and monitor endangered species, generally based on costly semi-automatic systems that require human supervision adding limitations in coverage and time. However, the recent emergence of Wireless Acoustic Sensor Networks (WASN) has allowed non-intrusive remote monitoring of endangered species in real time through the automatic identification of the sound they emit. In this work, an FPGA-based WASN centralized architecture is proposed and validated on a simulated operation environment. The feasibility of the architecture is evaluated in a case study designed to detect the threatened Botaurus stellaris among other 19 cohabiting birds species in The Parc Natural dels Aiguamolls de l’Empordà, showing an averaged recognition accuracy of 91% over 2h 55’ of representative data. The FPGA-based feature extraction implementation allows the system to process data from 30 acoustic sensors in real time with an affordable cost. Finally, several open questions derived from this research are discussed to be considered for future works.

Real-Time Distributed Architecture for Remote Acoustic Elderly Monitoring in Residential-Scale Ambient Assisted Living Scenarios

Ambient Assisted Living (AAL) has become a powerful alternative to improving the life quality of elderly and partially dependent people in their own living environments. In this regard, tele-care and remote surveillance AAL applications have emerged as a hot research topic in this domain. These services aim to infer the patients’ status by means of centralized architectures that collect data from a set of sensors deployed in their living environment. However, when the size of the scenario and number of patients to be monitored increase (e.g., residential areas, retirement homes), these systems typically struggle at processing all associated data and providing a reasonable output in real time. The purpose of this paper is to present a fog-inspired distributed architecture to collect, analyze and identify up to nine acoustic events that represent abnormal behavior or dangerous health conditions in large-scale scenarios. Specifically, the proposed platform collects data from a set of wireless acoustic sensors and runs an automatic two-stage audio event classification process to decide whether or not to trigger an alarm. Conducted experiments over a labeled dataset of 7116 s based on the priorities of the Fundació Ave Maria health experts have obtained an overall accuracy of 94.6%.

homeSound: A High Performance Platform for Massive Data Acquisition and Processing in Ambient Assisted Living Environments.

Human life expectancy has steadily grown over the last century, which has driven governments and institutions to increase the efforts on caring about the eldest segment of the population. The first answer to that increasing need was the building of hospitals and retirement homes, but these facilities have been rapidly overfilled and their associated maintenance costs are becoming far prohibitive. Therefore, modern trends attempt to take advantage of latest advances in technology and communications to remotely monitor those people with special needs at their own home, increasing their life quality and with much less impact on their social lives. Nonetheless, this approach still requires a considerable amount of qualified medical personnel to track every patient at any time. The purpose of this paper is to present an acoustic event detection platform for assisted living that tracks patients status by automatically identifying and analyzing the acoustic events happening in a house. Specifically, we have taken benefit of the amazing capabilities of a Jetson TK1, with its NVIDIA Graphical Processing Unit, to collect the data in the house and process it to identify a closed number of events, which could led doctors or care assistants in real-time by tracking the patient at home. This is a proof of concept conducted with data of only one acoustic sensor, but in the future we have planned to extract information of the sensor network placed in several places in the house.

QPSK demodulation using cellular neural networks

We show how QPSK signals can be demodulated using a simple discrete time two neuron CNN, on real data of a long haul radio link to Antarctica.