## 2 Literature Review  
### Accident Detection Studies Based on Acoustic Analysis  
Sound is a wave in which the vibration of an object is transmitted by a medium and is divided into voice and acoustics, such as human voices or speech. Prior studies were primarily conducted for educational use by analyzing features, such as change in rhythm, intonation, and speech speed [9], in the field of humanities and for developing a medical system for laryngeal cancer detection and voice therapy in the field of medical engineering [10]. In the field of information and communication, artificial intelligence, such as Siri, and technology to match the facial expression and voice of a character in animation games are being developed through voice recognition [11]. Sound waves are used not only to detect the situation around vehicles [12], but also to identify diseases and abnormal signs through the cries of livestock [13]. Voice analysis technology is also applied to determine whether a person is the identical person for scientific investigation of a criminal case [14] or to respond to a disaster situation by determining emotions or circumstances of a person [15]. Studies related to accident detection are being conducted in various industrial fields using the unique features of sound data. First, in the case of a traffic accident automatic detection system [16], CCTV was installed in a designated area and data were analyzed in real time to automatically detect the accident situation [17] in a tunnel and provide information to prevent secondary accidents. However, because the system in the study was applied to a tunnel [18], which is a linear space, it cannot be applied to a construction site in a three-dimensional space. The landslide monitoring system [19] in the field of civil engineering predicts the risk in advance by detecting changes in water temperature using a thermometer and analyzing the acoustics when the earth moves down a slope. However, this system is difficult to be applied to construction sites where various sounds are generated outdoors because not only the ground needs to be drilled, but also the acoustics of an accident are detected when external noise is blocked after drilling. The study of tracking and monitoring of the working status and productivity of heavy equipment through sound analysis [20] can be viewed as similar to this study in terms of improving the problems of monitoring through the attached sensors and analyzing sound patterns. However, acoustic analysis was not performed across the construction site because the activity of only a single machine, which was relatively distant from external noise, was analyzed in heavy equipment monitoring, and there were significant limitations to be applied to the safety management field of the construction site as the setting and layout of the device were not considered for measurement (i.e., position, distance, direction, and number of microphones). Although studies for accident detection in construction are also being conducted, most of them monitor dangerous situations in real time using equipment that has recently been miniaturized and advanced. In previous studies on accident monitoring using advanced equipment, USN-based real-time monitoring [21] was performed using several measurement sensors (i.e., ultrasonic wave, load, and inclination) in a temporary formwork construction. In addition, signs of collapse must be detected quickly, as roads and railroad slopes often collapse due to heavy rains caused by extreme weather conditions. Therefore, a system that can determine the risk of sudden slope collapse has been developed [22]. A new analysis algorithm has also been developed to detect signs of sudden slope collapse, which means that actions, such as warnings, evacuation instructions, and road closures, can be taken more quickly by detecting the signs.