Indoor-noise

In residential buildings, noise generated by residents or home appliances propagates through building structure and annoys residents on other floors. It is difficult for human to precisely identify the type/position of inter-floor noise, and some conflicts between residents have originated from this incorrect estimation of type/position. Correctly identifying the noise type/position is considered to be the first step in solving noise problem.

We built three different inter-floor noise datasets to study this problem.

Name	Building type
SNU-B36-50E	Office building
BDML-APT	Apartment building 1 (APT1)
CS-APT	Apartment building 2 (APT2)

Single acoustical sensor

A noise signal over a single microphone with a sufficient time duration might contain the dispersive nature of the plate wave or unidentified features. We used data-driven approach to catch these features and identify the noise signal.

Study

IWAENC 2018 (repo.)
- In this work, an method for inter-floor noise type/position classification was proposed and validated against an inter-floor noise dataset.
- We built an inter-floor noise dataset SNU-B36-50 in an office building.
Appl. Sci. (repo.)
- This paper is expanded version of IWAENC 2018.
- Type/position classification of noise at unlearned positions was shown.
- We collected inter-floor noise at new positions around the noise source positions in SNU-B36-50 and the new data was not used in learning.
EUSIPCO 2020 (accepted, repo.)
- We collected more inter-floor noises in two apartment buildings.
- The generalizability of the proposed method in Appl. Sci. was addressed against the new inter-floor noise datasets.
- The viability of inter-floor noise type classification knowledge transfer was demonstrated.
Mobile phone application (under development, repo.)
- The single acoustical sensor approach can be implemented on a smartphone device.
- Our inter-floor noise identification method was implemented on a smartphone application (iOS).