# Sound Localization Framework for Construction Site Monitoring
## 1 Introduction  
The distances, topographies, and obstacles at construction sites cause restrictions in management and supervision, which could result in minor and even fatal accidents. Therefore, safety blind spots at construction sites have motivated researchers to investigate safety-monitoring technologies. In addition, securing real-time monitoring and decision-making support technology in large-scale construction sites is crucial for achieving proactive and effective construction and process management. Various innovative technologies and measures are being applied at construction sites, considering that location information collection is essential for real-time monitoring. Various sensor-based technologies, such as radio frequency identification (RFID), Bluetooth, and inertial measurement units (IMUs) already exist. RFID technology can identify location information by reading tags associated with resources, such as for labor access control [1], material logistics [2], and equipment control [3]. Bluetooth technology uses a beacon device to identify location information based on the strength of the signal. For example, beacon devices are attached to heavy equipment at construction sites to monitor the location and condition of the equipment to increase the safety and work efficiency of workers at construction sites [4]. Finally, IMU sensors are attached to objects such as construction equipment to indicate movement and movement paths with gyroscopes to prevent collisions and improve their mobility [5]. While the above-mentioned sensor-based systems are used to collect the location information of major materials that need to be managed, they can also analyze the status and activity data of specific equipment and construction workers. However, they cannot monitor the work conditions or safety. Unlike sensor- and tag-based monitoring systems, construction sites are also monitored using signals from tactile data (e.g., temperature and material characteristics), olfactory data, and sound data generated during equipment operation and construction work on the site, as well as visual data of recorded photos and videos. Among them, olfactory and tactile data, which can check for harmful gasses or temperatures, are used for monitoring the overall atmospheric and spatial information of the space instead of determining the situation during actual work. For example, these data can identify harmful gas and oxygen concentrations underground in real time [6]. Visual data are most widely used along with a location estimation system as it is the most intuitive means of determining the worker's risk situation, construction progress, safety, and the environment via closed-circuit television (CCTV) at construction sites [7; 8]. However, visual data have limitations at construction sites [9], such as the installation location and scope of the camera, speed of specification and data transmission, accuracy of the expected location information, and influence of external environmental factors. This study focuses on sound data identification at construction sites to potentially improve risk management, either independently or combined with other technologies at construction sites (as mentioned above), even though sound-data-based position estimation systems that analyze the acoustic signals collected by microphone arrays have been actively used in other fields, such as automobiles, maritime navigation, robots, and military applications. As sound data are also considered management targets rather than noise at construction sites, studies on data pattern analysis have recently been conducted to classify equipment sounds. While most previous studies on sound data in the construction sector are focused on sound pattern analysis, studies on estimating sound-source locations are insufficient. Research on estimating sound-source locations at construction sites is essential for applying monitoring systems based on sound data.