In Nature, fish have the ability to localize prey, school, navigate, etc., using the lateral-line organ. Artificial hair flow sensors arranged in a linear array shape (inspired by the lateral-line system (LSS) in fish) have been applied to measure airflow patterns at the sensor positions. Here, we take advantage of both biomimetic artificial hair-based flow sensors arranged as LSS and beamforming techniques to demonstrate dipole-source localization in air. Modelling and measurement results show the artificial lateral-line ability to image the position of dipole sources accurately with estimation error of less than 0.14 times the array length. This opens up possibilities for flow- based, near-field environment mapping that can be beneficial to, for example, biologists and robot guidance applications.

https://royalsocietypublishing.org/doi/pdf/10.1098/rsif.2013.0162

Imaging dipole flow sources using an artificial lateral-line system made of biomimetic hair flow sensors

The aim of this paper is to present a secure wireless sensor network-based infrastructure for fast and accurate detection of eventual leaks that might occur in multiphase pipelines (i.e., pipelines which carry simultaneously more than one fluid). The system is scalable to monitor long distances of pipelines. It consists of a newly designed low-cost pipeline set which is composed of an inner pipe that carries the multiphase fluid, surrounded by a second outer pipe that holds the leak detection unit. This latest comprises an air-ultrasonic sensor which continuously senses the presence of the leak. The location of the leak is determined by a bidirectional microphone. Both these sensors are interfaced to a wireless sensor module which performs control, signal processing, and transmission tasks. Hence, the second contribution of this paper is to provide a new secure and reliable communication protocol that takes into consideration the nature of the network in terms of packets patterns and hardware constraints of the communicating nodes. Online tests in a laboratory scale flow loop indicate that the system is capable to accurately determine the location of the leak and its rate (in 1/min) in fast response time for different scenarios of leaks.

A Wireless Sensor Network-Based Infrastructure for Real-Time and Online Pipeline Inspection

The fast development of networked smart devices equipped with sensors and radio-frequency identification, connected to the Internet, is enabling the emergence of many new applications and the redesign of traditional systems towards more effective operation. Raising awareness among engineering PhD students for the potential of this new wave in their research work is a crucial element in their education. With this aim, the doctoral conference DoCEIS'13 focused on technological innovation for the Internet of Things, challenging the contributors to analyze in which ways their technical and scientific work could contribute to or benefit from this paradigm. The results of this initiative, which was reasonably successful, are briefly analyzed.

/pdf/technological-innovation-for-the-internet-of-things-j62k5emalh.pdf

Technological Innovation for the Internet of Things

Investigation of sampling frequency requirements for acoustic source localisation using wireless sensor networks

This paper investigates the use of an Acoustic Vector Sensor (AVS) for tracking a moving speaker in real time through estimation of the Direction of Arrival (DOA). This estimation is obtained using the MUltiple SIgnal Classification (MUSIC) [1] algorithm applied on a time-frame basis. The performance of the AVS is compared with a SoundField Microphone which has similar polar responses to the AVS using time-frames ranging from 20 ms to 1 s. Results show that for 20 ms frames, the AVS is capable of estimating the DOA for both mono-tone and speech signals, which are both stationary and moving, with an accuracy of approximately 1.6° and less than 5° in azimuth, for stationary and moving speech sources, respectively. The results also show that the DOA estimates using the SoundField microphone are significantly less accurate than those obtained from the AVS. Furthermore, the results suggest that for estimating the DOA for speech sources, a Voice Activity Detector (VAD) is critical to ensure accurate azimuth estimation.

/pdf/using-in-air-acoustic-vector-sensors-for-tracking-moving-3gyct4jd0v.pdf

Using in-air Acoustic Vector Sensors for tracking moving speakers

This paper introduces a new method for the estimation of sound source distance and direction using at least three microphone sensors in indoor environments. Unlike the other methods that normally use approximations in obtaining the time difference between sensors, this method exploits the existed geometrical relationships of the sensors to form an exact solution to estimating the source position. To overcome reverberation, an enhancing pre-process has been used for different sound sources with different spectra, e.g., single frequency, multiple frequencies and different noise shapes. Source direction and distances are estimated from time of sound wave travel and distances of acoustic sensors. Using the method described in this paper a level of 1° accuracy is obtained. Several experimental tests have been undertaken that verify the results. Conclusions and future work are also described.

https://iopscience.iop.org/article/10.1088/0957-0233/19/2/024003/pdf

D C Tan

Papers

Accurate sound source localization in a reverberant environment using multiple acoustic sensors