A Low Cost Wireless Acoustic Sensor for Ambient Assisted Living Systems

Abstract

Ambient Assisted Living (AAL) has become an attractive research topic due to growing interest in remote monitoring of older people. Development in sensor technologies and advances in wireless communications allows to remotely offer smart assistance and monitor those people at their own home, increasing their quality of life. In this context, Wireless Acoustic Sensor Networks (WASN) provide a suitable way for implementing AAL systems which can be used to infer hazardous situations via environmental sounds identification. Nevertheless, satisfying sensor solutions have not been found with the considerations of both low cost and high performance. In this paper, we report the design and implementation of a wireless acoustic sensor to be located at the edge of a WASN for recording and processing environmental sounds which can be applied to AAL systems for personal healthcare because it has the following significant advantages: low cost, small size, audio sampling and computation capabilities for audio processing. The proposed wireless acoustic sensor is able to record audio samples at least to 10 kHz sampling frequency and 12-bit resolution. Also, it is capable of doing audio signal processing without compromising the sample rate and the energy consumption by using a new microcontroller released at the last quarter of 2016. The proposed low cost wireless acoustic sensor has been verified using four randomness tests for doing statistical analysis and a classification system of the recorded sounds based on audio fingerprints.

A Distributed Computing Solution Based on Distributed Kalman Filter for Leak Detection in WSN-Based Water Pipeline Monitoring

“…From a technical point of view, the ESP32 offers: for computation: an Xtensa Dual-Core 32-bit LX6 microprocessor operating at up to 240 MHz, a 520-kB Static Random-Access Memory (SRAM), a 4-MB flash memory. for interfacing: a 12-bit Analog-to-Digital Converter (ADC) with up to 18 channels and 40 physical General Purpose Input Output (GPIO) pads, which can be used as general purpose I/O to connect new sensors, or can be connected to an internal peripheral signal [ 10 ]. for communication: a built-in Wi-Fi card supporting IEEE 802.11 b/g/n standards, Bluetooth version 4.2 and 486 Bluetooth Low Energy (BLE).…”

“…for interfacing: a 12-bit Analog-to-Digital Converter (ADC) with up to 18 channels and 40 physical General Purpose Input Output (GPIO) pads, which can be used as general purpose I/O to connect new sensors, or can be connected to an internal peripheral signal [ 10 ].…”

“…In addition, in large-scale monitoring applications, most of the sensor nodes are geographically far away from the base station and are usually battery powered [ 8 ]. Therefore, the drawbacks of WSNs with centralized architectures deployed in large-scale monitoring applications are enormous bandwidth requirement and huge energy consumption as periodic transmission of raw data over long distances, via multiple hops to the base station leads to fast depletion of sensor node’s battery and shortens the lifespan of a WSN [ 7 , 9 , 10 ]. Other drawbacks include low reliability, longer response time, high bandwidth cost, low level data security and privacy [ 7 , 9 , 10 , 11 , 12 ].…”

“…Therefore, the drawbacks of WSNs with centralized architectures deployed in large-scale monitoring applications are enormous bandwidth requirement and huge energy consumption as periodic transmission of raw data over long distances, via multiple hops to the base station leads to fast depletion of sensor node’s battery and shortens the lifespan of a WSN [ 7 , 9 , 10 ]. Other drawbacks include low reliability, longer response time, high bandwidth cost, low level data security and privacy [ 7 , 9 , 10 , 11 , 12 ]. Some works in the literature have demonstrated the feasibility of distributed computing in WSN and its promises of gain in performance and lower power consumption [ 5 , 7 , 11 , 12 , 13 ].…”

Special Issue on “Sound and Music Computing”

“…Quintana-Suárez et al [29] authored an article on a sensor device that enables to remotely monitor the activity and health of elderly people. Such technology is generally called Ambient Assisted Living, and this article in particular presents a low-cost acoustic sensor.…”