## 2 Related Works  
Bee monitoring has been a field for scientific research for more than a hundred years. The first proposal of a system that enabled measuring temperature and weight of beehive was described in 1914 by [PERSON] [17]. The data were gathered hour by hour for one year. Nearly twenty years later, [PERSON] [18] used an electrical thermocouple method to monitor the temperature inside the beehive. Along with the development of technology, more and more solutions were proposed. Finally, there came a time for IoT systems. The most common methods of bee monitoring used in Precision Beekeeping [19; 20; 21] include measuring temperature and other environmental factors inside and outside the beehive, including its weight. Solutions based on monitoring temperature enable the detection of various situations inside the beehive--increased food consumption, beginning of brood rearing, pre-swarming state, or even death of the bee family while controlling the weight of beehive is helpful to indicate the time for honey harvesting, lack of food during winter or swarming state without enormous financial expenses. Systems that analyze temperature and humidity are described in [22; 23]--both enable real-time monitoring; the one developed by [PERSON] et al. [24] includes also measuring the weight of a beehive, whereas the system developed by [PERSON] [25] monitors conditions inside the beehive and can regulate them when necessary. The approach described by [PERSON] et al. [26] allows web monitoring not only for temperature and humidity but also for additional factors such as air pollution or wind speed. A similar solution is proposed in [27] and gathers data from various sensors for air gases. The solution proposed by [PERSON] et al. [28] enables video recording along with temperature and humidity monitoring, while the system described by [PERSON] et al. [29] also allows audio recording. Beehive weight-based IoT systems are presented in [30; 31]. A solution presented in [32], apart from controlling temperature, humidity, air pressure, and beehive weight, also uses a gesture sensor to analyze bee flight behavior. In recent years, some solutions were developed that use chemical analysis of the air in the beehive that enable detection of the _V. destructor_ mite inside the beehive [33; 34]. They assume that _Varroa destructor_ influences gas composition. Although the above solutions do not belong to IoT systems, they are worth mentioning. Another category of IoT systems developed for beekeping includes those that allow for audio analysis. The analysis is useful for detecting a swarming state inside a bee colony [35; 36; 37; 38]. [PERSON] et al. [39] classify the behavior of queens, scouts, forgers, and the whole bee family based on bee noises. An approach worth mentioning is presented by [PERSON] et al. [40]. Although this system analyses bee sounds to determine bee pollination efficiency, it is dedicated to fruit growers. As the development in the electronics field proceeds, camera devices are becoming more accessible and more and more often used in IoT systems. Beekeeping systems are not an exception for this. Video monitoring solutions that monitor the number of bees entering and leaving a beehive are presented in [41; 42]. [PERSON] et al. [41] described encountered problems, such as recognizing bee bodies and their shadows, while [PERSON] et al. [42] proposed a solution with tags attached to the bee legs, which eliminated the difficulty. [PERSON] et al. [43] developed a system that detects bearing honey bees, along with counting the number of bees. The real-time monitoring system proposed by [PERSON] et al. [44] records bees going through a passageway and enables counting them as well as identifying mites on their bodies. Apart from the camera, the solution uses spectral waves that illuminate the bee body and ML methods to classify bees affected by the _Varroa destructor_ mite. The accuracy of classification reached up to 99%, depending on classifier parameters. The solution developed by [PERSON] et al. [11] locates _V.