## 1 Introduction  
Honeybees (_Apis mellifera_) are vital to environmental welfare. Beyond producing honey, bees wax, and royal jelly, their pollination activity supports biodiversity and major agricultural crops, making them an important agro-environmental \"service provider\" [1]. In fact, close to 75 percent of the crops in the United States of America producing fruits and seeds for human consumption depend, at least in part, on honeybees for sustained production, yield, and quality [2]. While all types of bees contribute to pollination, honey bees are the main pollinators of almonds, citrus fruits, blueberries, and curcubits [2]. Therefore, any change in bee colony behaviour and health, as well as drops in population sizes, can have drastic effects on the food industry. To this end, continuous monitoring of honey bee health and colony strength is performed by beekeepers. Traditionally, beehive monitoring has relied on manual and visual examinations. These inspections, however, are time-consuming for the beekeepers and disruptive for the colonies, hence are not performed continuously. Commonly, beekeepers inspect their hives every two weeks during pollination services or honey production periods and less often, if at all, during winter months. Important changes in population dynamics of a colony and in overall colony health can occur, however, during a two-week period (e.g., full colony death due to swarming or parasite infestation), hence there is a need for continuous monitoring. In fact, massive colony losses have been observed all over the world [3, 4, 5, 6, 7, 8]. Scientists believe that multiple stressors, either acting independently, in combination, or even synergistically, are responsible for this phenomenon [9, 10, 11]. As such, passive monitoring of honey bee colony health has become of great interest to the beekeeping and honey bee research communities [12]. With advances in Internet of Things (IoT) sensors and devices, such passive monitoring has become a reality, and precision beekeeping applications have emerged [13]. For example, hive health and colony strength monitoring applications have emerged based on temperature, humidity, and CO\({}_{2}\) sensors [12; 14; 15; 16]. More recently, audio and vibrations monitoring have also emerged as a viable alternative to remote hive monitoring. For example, honeybees are known to generate special sounds in response to triggers such as airborne toxicants, predatory mites, and failing queens [17]. In fact, bees communicate within the colony via vibration and sound signals [18]. Gross body movements, wing movements, high-frequency muscle contractions without wing movements, and pressing the thorax against the substrates or another bee are just some of these vibroacoustic signals present within a hive [19]. Moreover, vibroacoustic signals generated by bees modulate behaviours that affect swarming, as well as the queen's behaviour during swarming. In this regard, research has shown correlations between the frequencies of the vibroacoustic signals and their amplitudes with events such as swarming [20; 21]. Additionally, unique auditory signatures are present in a hive when multiple queen bees are present, typically a virgin bee and a mature queen bee; such sounds have been termed piping, quacking, and tooting [22]. Queen piping, for example, is emitted by young queens to signal readiness for battle with the mature queen (only one queen can lead the colony). The sound made as soon as they emerge is called tooting, which has been shown to have a fundamental frequency between 400 Hz during the day of emergence, to around 500 Hz two to four days post-emergence. It starts with around 17 short pulses, and the number decreases to around 7 after several days [23]. When a virgin queen emerges, several other mature queens may still be in their cells. These typically reply with a sound called quacking. Quacking is described as a series of short pulses (with duration shorter than 0.2 s) having a fundamental frequency of around 350 Hz [23].