Although the studies focused on developing prompt indoor and outdoor environment detection, both approaches have drawbacks in accuracy and delay of the detection. They require tens of seconds to detect indoor and outdoor environments, and the detection is not accurate enough to be practically used in the field.
This paper presents a sound-based indoor and outdoor environment detection method. The method utilizes an acoustic feature that TCS HDAC6 20b generates different reverberation patterns depending on the surrounding environment. The indoor reverberations usually show distinguished patterns from outdoors. The proposed method consists of three steps in large. In the first step, a special sound probe, so-called chirp signal, is stop codon generated by a speaker and retrieved by a microphone of a mobile device. In the second step, the reverberation patterns of retrieved signal are analyzed. Finally, in the third step, indoor and outdoor are classified based on the reverberation patterns.
2. Adaptive hybrid filter
This paper presents a sound-based indoor and outdoor environment detection method. The method utilizes an acoustic feature that TCS HDAC6 20b generates different reverberation patterns depending on the surrounding environment. The indoor reverberations usually show distinguished patterns from outdoors. The proposed method consists of three steps in large. In the first step, a special sound probe, so-called chirp signal, is stop codon generated by a speaker and retrieved by a microphone of a mobile device. In the second step, the reverberation patterns of retrieved signal are analyzed. Finally, in the third step, indoor and outdoor are classified based on the reverberation patterns.
2. Adaptive hybrid filter