## 1 Introduction  
Traffic-induced vibrations can unfavorably affect both a building's structure and its occupants. Recent research has revealed that vibrations may also considerably affect humans, particularly during sleep [1]. The results of the research show that low-frequency vibrations can negatively affect sleep quality and the sense of feeling sufficiently rested [2]. To address these adverse impacts, several vibration isolation methods are used to mitigate the negative effects. Based on frequency characteristics, materials such as rubber or cork mats and sheets are deliberately applied to efficiently reduce low-frequency vibrations. For heavy loads, configurations of springs and pads can be implemented in the building. Intensive research has revealed the fact that humans exhibit a greater sensitivity to vibrations than the structures themselves, highlighting the necessity of recognizing this difference [3]. The results of some studies (see [4]) show that vibrations produced by road traffic, particularly from heavy trucks and rail vehicles [5], especially affect people's comfort levels and the structural integrity of buildings [6; 7]. Other investigations examined the effects of low-frequency noise and vibrations on human health [8]. The results indicate that vibrations within 5 Hz-25 Hz can cause internal organs to resonate, resulting in several physiological reactions, including elevated heart rate, nausea, and confusion [1]. The vibrations caused by moving vehicles are associated with the building's dynamic characteristics, typically defined by a number of parameters, such as velocity or acceleration. The results of various studies clearly demonstrate that traffic-induced vibrations significantly affect human health and comfort [9; 10; 11]. Low-frequency vibrations can be particularly irritating and may lead to health issues and discomfort. Traffic-induced vibrations, especially in buildings with wooden slabs, may significantly affect the comfort of residents. The results of previous investigations shows that these vibrations are most felt on the lower floors of buildings [12]. The impact of vibrations on humans depends on duration, intensity and frequency of vibrations, and it can cause discomfort and even health problems. According to the standard [13], vibrations can be classified as short-term or long-term (lasting less or more than 30 min a day, respectively). In buildings, vertical vibrations of slabs have a decisive impact on the feelings of the residents [1]. The results of analyses show that vibrations caused by traffic can lead to fatigue and stress in people staying in buildings exposed to such vibrations. The vibration acceleration values that are felt by people are lower than those that affect the building structure. Therefore, it is important to design buildings with appropriate technologies that minimize undesirable effects of vibrations [1]. Therefore, further research and development of methods for evaluating and reducing the effects of vibrations on individuals is really essential. Consequently, this study considers utilizing machine learning (ML) to assess the potential impacts of vibrations on a building's residents. ML has wide applications, and it is increasingly being used in various fields of science and industry [14; 15; 16]. The approach is based on modern mathematical developments. The usefulness of ML in civil engineering and construction should be highlighted (see [17; 18; 19], for example). The system based on artificial intelligence and ML techniques to help detect a threat such as a fire, and based on analysis of surveillance images, should be underlined. An example of such a system is a model of technical wear and tear of buildings located in mining regions subjected to paraseismic excitations [20]. The study presents ML methods, among other approaches, used in predicting the degree of operational wear of the analyzed buildings. Interesting applications can also be found in previous studies. For example, the idea of fault detection in a windmill was presented in [21].