scholarly journals Speech Intelligibility Analysis and Approximation to Room Parameters through the Internet of Things

2021 ◽  
Vol 11 (4) ◽  
pp. 1430
Author(s):  
Jesus Lopez-Ballester ◽  
Jose M. Alcaraz Calero ◽  
Jaume Segura-Garcia ◽  
Santiago Felici-Castell ◽  
Miguel Garcia-Pineda ◽  
...  
Keyword(s):  
Speech Intelligibility ◽  
Raspberry Pi ◽  
Indoor Environments ◽  
Acoustic Sensor ◽  
Acoustic Measurements ◽  
Acoustic Parameters ◽  
Acoustic Characteristics ◽  
Acoustic Sensor Networks ◽  
Speech Intelligibility Index ◽  
The Internet Of Things

In recent years, Wireless Acoustic Sensor Networks (WASN) have been widely applied to different acoustic fields in outdoor and indoor environments. Most of these applications are oriented to locate or identify sources and measure specific features of the environment involved. In this paper, we study the application of a WASN for room acoustic measurements. To evaluate the acoustic characteristics, a set of Raspberry Pi 3 (RPi) has been used. One is used to play different acoustic signals and four are used to record at different points in the room simultaneously. The signals are sent wirelessly to a computer connected to a server, where using MATLAB we calculate both the impulse response (IR), and different acoustic parameters, such as the Speech Intelligibility Index (SII). In this way, the evaluation of room acoustic parameters with asynchronous IR measurements two different applications has been explored. Finally, the network features have been evaluated to assess the effectiveness of this system.

Acoustic sensor networks in the Internet of Things applications

2018 ◽  
Vol 86 ◽  
pp. 1167-1169 ◽  
Author(s):  
Joarder Kamruzzaman ◽  
Guojun Wang ◽  
Gour Karmakar ◽  
Iftekhar Ahmad ◽  
Md Zakirul Alam Bhuiyan
Keyword(s):  
Sensor Networks ◽  
Internet Of Things ◽  
The Internet ◽  
Acoustic Sensor ◽  
Acoustic Sensor Networks ◽  
The Internet Of Things

scholarly journals Packet Flow Based Reinforcement Learning MAC Protocol for Underwater Acoustic Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2284
Author(s):  
Ibrahim B. Alhassan ◽  
Paul D. Mitchell
Keyword(s):  
Sensor Networks ◽  
Mac Protocol ◽  
Propagation Delay ◽  
Basic Function ◽  
Acoustic Sensor ◽  
Underwater Acoustic Sensor Networks ◽  
Medium Access ◽  
Underwater Acoustic ◽  
Q Learning ◽  
Acoustic Sensor Networks

Medium access control (MAC) is one of the key requirements in underwater acoustic sensor networks (UASNs). For a MAC protocol to provide its basic function of efficient sharing of channel access, the highly dynamic underwater environment demands MAC protocols to be adaptive as well. Q-learning is one of the promising techniques employed in intelligent MAC protocol solutions, however, due to the long propagation delay, the performance of this approach is severely limited by reliance on an explicit reward signal to function. In this paper, we propose a restructured and a modified two stage Q-learning process to extract an implicit reward signal for a novel MAC protocol: Packet flow ALOHA with Q-learning (ALOHA-QUPAF). Based on a simulated pipeline monitoring chain network, results show that the protocol outperforms both ALOHA-Q and framed ALOHA by at least 13% and 148% in all simulated scenarios, respectively.

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