## 2 Methods  
English journal and conference papers, as well as electronic preprints, published between January 2012 and August 2021, were chosen as the target of this review. PubMed, Google Scholar, Scopus, IEEE Xplore, and arXiv were queried to collect an initial list of papers containing specific search terms in their title or abstract. Additional papers were identified by scanning the reference sections of these papers. The search terms used included:  
1. _Apis mellifera_;
2. _Apis cerana_;
3. _Apis dorsata_;
4. _Apis bombus_;
5. Bumblebee;
6. Bee;
7. Hive;
8. Honeybee;
9. Apiculture;10. Sound;  
11. Audio;  
12. Acoustics;  
13. ZigBee.  
These search terms were combined using the following rule: (1 OR 2 OR 3 OR 4 OR 5 OR 6 OR 7 OR 8 OR 9) AND (10 OR 11 OR 12) AND NOT 13. The last rule was included in order to avoid erroneous hits with papers focusing on ZigBee, a wireless transmission technology used with IoT devices that is not related to the review. Since the Google Scholar search engine only allows searches of full text or titles, and not titles and abstracts, the query was performed using the flag \"allintitle\" to search titles only. On arXiv, Scopus, and PubMed, on the other hand, both abstracts and titles were queried. With IEEExplore, all metadata were queried. From the resulting hits, the inclusion and exclusion criteria presented in Table 1 were used.  
To assess the eligibility of the selected papers, the titles were read first. If the title did not clearly indicate whether the inclusion and exclusion criteria were met, the abstract was read as well. Finally, when reading the full text during the data collection process, papers that did not meet the review criteria were also rejected. For the included papers, Table 2 lists the items that were extracted and used for further analyses. The first category covers the origin of the article, i.e., whether it was published as a journal manuscript, in a conference proceedings, or as a non-peer-reviewed preprint, the first author's affiliation and country, as well as the venue in which the paper was published. These details provide a quick overview of the types of publication available, as well as which countries are working most actively in the field. It is important to highlight that we have chosen to include non-peer-reviewed articles, such as those available on arXiv electronic preprints, as there is an increasing trend in publishing preprints, especially within the artificial intelligence community, prior to submission to major conferences and/or journals. This also allows for inclusion of a more diverse pool of papers from all corners of the world.  
Next, the rationale category focuses on the goals of the selected studies. This is valuable information to understand how bee acoustics have been used and allows for trends to be characterized. Third, the experiment setup describes the species of bees, number of beehives or colonies used in each study, time of the recording, the sampling rate used, microphone information, and the preprocessing steps. These are important details needed for study replication. Fourth, the audio analysis method is assessed in order to focus on the feature extraction method, the analysis method (e.g., machine learning or simple correlations), and evaluation metrics used. Finally, the reproducibility of the work in selected articles is quantified by looking at the availability of the data and code.  
\begin{table}
\begin{tabular}{l} Inclusion–Studies using audio to: \\ \hline Detect bees \\ Predict hive strength \\ Detect swarming \\ Detect queen bee missing \\ Detect mite attack \\ Identify bee species \\ Measure pollination efficacy \\ Detect environmental effects \\ Detect arrival and departure of bees \\ \hline Exclusion–Studies focusing on: \\ \hline Software development of hive monitoring \\ Hardware development of hive monitoring \\ \hline \end{tabular}
\end{table}
Table 1: Eligibility criteria for inclusion and exclusion of articles.