## 1 Introduction
### Features of Extinguishing Fires
On the other hand, a future solution may be the use of acoustic technology not only in firefighting actions, but also in fire detection. This is due to the fact that sound is generated by the heat flow associated with the flame (in practice, many materials that are exposed to heat cause acoustic emissions, which includes their heating, pyrolysis, and combustion process) [87]. These emissions take on a variety of forms, from crackling or popping to the release of gases. This is important because acoustic sensors can detect flames before a difficult-to-extinguish fire breaks out. [PERSON] presents aspects of the use of acoustic waves in the field of preventive measures, including the detection of flames in the initial stage of fires using spectral signal processing techniques, e.g., [88; 89]. Moreover, in the long term, acoustic technology may also find application in the fight against pollution that is the result of fires. Through the use of an acoustic extinguisher electrically connected to an AI (Artificial Intelligence) module, it becomes possible to automatically detect the source of flames from a particular type of organic substance and, in the case of positive detection, immediately generate the acoustic waves necessary to extinguish them. Images from both visible and infrared bands may be applied for flame detection (in the second case, higher pixel intensities are observed [90]). For practical implementation, a number of techniques and libraries can be used, including Matplotlib, OpenCV, TensorFlow, NumPy, and Imutil, among others. An example of a flame and smoke detection system dedicated to acoustic technology is provided in Figure 1. It can be a module permanently implemented in a fire extinguisher or, as shown in Figure 1, a standalone platform that allows the remote detection of flame outbreaks. More information on this subject can be found in the publications: [84; 85; 86; 91; 92]. Whether the optional smart platform is permanently installed in the acoustic extinguisher or is an additional mobile (portable) component of the acoustic extinguisher, the recognition results will be the same and depend on the effectiveness of the deep neural networks to detect flames and smoke. The step-by-step algorithm is described in the articles of [PERSON] et al. [84; 85; 86; 91; 92]. Such a robotic platform makes it possible to test various flame detection algorithms and assess the source of the flames, which is important for the growing use of robots [93; 94]. The installation of a physically connected driving device to the extinguisher may allow the extinguisher to move and change direction, so that the outlet of the device is always directed towards the source of the flames and is kept at the correct distance from the fire source using ultrasonic and temperature sensors [85]. For this purpose, an algorithmic method may be applied to design control systems and structural implementations of systems can be implemented, e.g., [95; 96]. In practice, concentrating the acoustic beam makes it possible to improve the range of the extinguisher and reduce the required acoustic power [97; 98]. However, despite the many advantages, the use of the acoustic method is associated with certain limitations (including design constraints, the size of the extinguisher, and the limited range of the extinguisher--depending, among other things, on the power delivered to the sound source, which determines the difficulties when extinguishing large fires). Therefore, more research is needed to determine the limits of the use of this technology. A separate issue is the continuation of research focused on the safety of living beings (including humans) when exposed to acoustic waves, as well as research in terms of the strength of materials exposed to low-frequency acoustic waves [83]. To increase the scalability of flame extinguishing by acoustic waves, acoustic systems consisting of multiple sound sources may be necessary for larger fires, allowing effective flames in an improved acoustic field [91].