A multi-layered energy consumption model for smart wireless acoustic sensor networks

12/17/2018
by   Gert Dekkers, et al.
0

Smart sensing is expected to become a pervasive technology in smart cities and environments of the near future. These services are improving their capabilities due to integrated devices shrinking in size while maintaining their computational power, which can run diverse Machine Learning algorithms and achieve high performance in various data-processing tasks. One attractive sensor modality to be used for smart sensing are acoustic sensors, which can convey highly informative data while keeping a moderate energy consumption. Unfortunately, the energy budget of current wireless sensor networks is usually not enough to support the requirements of standard microphones. Therefore, energy efficiency needs to be increased at all layers --- sensing, signal processing and communication --- in order to bring wireless smart acoustic sensors into the market. To help to attain this goal, this paper introduces WASN-EM: an energy consumption model for wireless acoustic sensors networks (WASN), whose aim is to aid in the development of novel techniques to increase the energy-efficient of smart wireless acoustic sensors. This model provides a first step of exploration prior to custom design of a smart wireless acoustic sensor, and also can be used to compare the energy consumption of different protocols.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
05/21/2021

Survey on Energy-Efficient Techniques for Wireless Sensor Networks

The concept of energy-efficient computing is not new but recently the fo...
research
05/07/2018

Energy Efficient Task Assignment in Virtualized Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are being used extensively today in vari...
research
12/21/2017

Rate-Distributed Spatial Filtering Based Noise Reduction in Wireless Acoustic Sensor Networks

In wireless acoustic sensor networks (WASNs), sensors typically have a l...
research
01/08/2021

FENet: A Frequency Extraction Network for Obstructive Sleep Apnea Detection

Obstructive Sleep Apnea (OSA) is a highly prevalent but inconspicuous di...
research
01/04/2021

Intelligent Routing to Enhance Energy Consumption in Wireless Sensor Network: A survey

Nowadays, the network and the Internet applications have gained a substa...
research
12/22/2016

Hardware for Machine Learning: Challenges and Opportunities

Machine learning plays a critical role in extracting meaningful informat...
research
10/19/2019

Smart Monitoring: remote-monitoring technology of power, gas, and water consumption in Smart Cities

This paper describes the remote-collection technology of detailed data (...

Please sign up or login with your details

Forgot password? Click here to reset