[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-126553-en":3,"doc-seo-126553-105":31,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},126553,13056712833777,"Logic","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",8,"Research & Report","Identifying Queenlessness in Honeybee Hives from Audio Signals Using Machine Learning","Honeybee colonies rely on a healthy queen for long-term survival, since the queen is the colony’s only reproductive female. The queen’s death or loss severely harms colony well-being, making early detection essential for beekeepers to take timely remedial actions. This paper presents methods that use acoustic signals recorded in beehives combined with machine learning algorithms to determine whether a colony contains a healthy queen. Results support decision-making on whether intervention is needed.","electronics   \nArticle  \nIdentifying Queenlessness in Honeybee Hives from Audio Signals Using Machine Learning  \nStenford Ruvinga 1,*, Gordon Hunter 1,*, Olga Duran 2 and Jean-Christophe Nebel 1  \nCitation: Ruvinga, S.; Hunter, G.; Duran, O.; Nebel, J.-C. Identifying Queenlessness in Honeybee Hives from Audio Signals Using Machine Learning. Electronics 2023, 12, 1627 . [https://doi.org/10.3390/](https://doi.org/10.3390/)[ ](https://doi.org/10.3390/)electronics12071627  \nAcademic Editors: Gwanggil Jeon and Chunjie Zhang  \nReceived: 27 January 2023  \nRevised: 9 March 2023  \nAccepted: 21 March 2023  \nPublished: 30 March 2023  \nCopyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) .  \n1 School of Computer Science and Mathematics, Kingston University, London KT1 2EE, UK  \n2 School of Engineering and the Environment, Kingston University, London SW15 3DW, UK  \n* Correspondence: [k1103714@kingston.ac.uk](k1103714@kingston.ac.uk) (S.R.); [g.hunter@kingston.ac.uk](g.hunter@kingston.ac.uk) (G.H.)  \nAbstract: Honeybees are vital to both the agricultural industry and the wider ecological system, most importantly for their role as major pollinators of flowering plants, many of which are food crops. Honeybee colonies are dependent on having a healthy queen for their long-term survival since the queen bee is the only reproductive female in the colony. Thus, as the death or loss of the queen is of great negative impact for the well-being of a honeybee colony, beekeepers need to be aware if a queen has died in any of their hives so that appropriate remedial action can be taken. In this paper, we describe our approaches to using acoustic signals recorded in beehives and machine learning algorithms to identify whether beehives do or do not contain a healthy queen. Our results are extremely positive and should help beekeepers decide whether intervention is needed to preserve the colony in each of their hives.  \nKeywords: honeybees; queen bee; bee colony; audio signal; CNN; LSTM; MLP; logistic regression; FFT; MFCC; spectrograms  \n1. Introduction  \nRecent advances in sensor technology and algorithms for the processing and interpretations of the signals they capture have now made “smart” monitoring applied to various environmental problems possible, with a view to resolving or mitigating them.  \nAmong such problems, of major concern is the serious decline in populations of pollinating insects. These are vital to the survival of many flowering plant species, including many crops for both human and animal consumption, notably fruit. Hence, the well-being of such pollinators is essential for both the agricultural industry and the wider environment. Foremost among such insects are honeybees, which are possibly the most productive of pollinating insects. Over recent years, honeybee numbers in much of Europe and North America have been dwindling. This has been attributed to a wide range of factors—from pesticides such as neonicotinoids [1] to the rise of largely monoculture agriculture in many areas [2], and even the microwave electromagnetic radiation used in mobile telecommunications [3] .  \nMonitoring the well-being of beehives offers a way of ensuring individual colonies do not fall into terminal decline. If major problems are detected sufficiently promptly, remedial action can be taken, ensuring that the colony does not die off. However, monitoring should ideally be carried out in a manner that is as non-invasive as possible in order to cause the minimum possible disruption to the natural life cycle of the bees, minimizing stress and disturbance to them and their productivity as pollinators. Monitoring the sounds produced by the bees is an appropriate moda","cbCaicJCcQPTA0M3","https://ap.wps.com/l/cbCaicJCcQPTA0M3","pdf",5021214,2,1,19,"English","en",105,"# Introduction\n## Honeybee decline and monitoring needs\n## Acoustic signals as indicators\n## Problem definition and study approach","[{\"question\":\"Why is identifying queenlessness in honeybee hives important?\",\"answer\":\"The queen is the only reproductive female in the colony, so her loss leads to a steady population decline and eventual colony failure without replacement. Early detection enables beekeepers to intervene in time.\"},{\"question\":\"What data and methods are used to detect whether a hive has a healthy queen?\",\"answer\":\"The approach records acoustic signals from beehives and applies machine learning algorithms to identify the presence or absence of a healthy queen. Techniques include analyzing audio signal features and training models on known conditions.\"},{\"question\":\"How do the authors validate their machine learning model?\",\"answer\":\"They validate the model by applying it to a second dataset collected in a different location and over a different time period, demonstrating generalization beyond the original recording conditions.\"}]","Identifying Queenlessness in Honeybee Hives from Audio Signals Using Machine Learning | PDF",1785933286,48,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":29},"identifying-queenlessness-in-honeybee-hives-from-audio-signals-using-machine-learning","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,48,51],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":20},"https://docshare.wps.com/document/","Document",{"item":49,"name":12,"@type":44,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":44,"position":53},"https://docshare.wps.com/document/identifying-queenlessness-in-honeybee-hives-from-audio-signals-using-machine-learning/126553/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":42,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-27","2026-08-05",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"Why is identifying queenlessness in honeybee hives important?","Question",{"text":76,"@type":77},"The queen is the only reproductive female in the colony, so her loss leads to a steady population decline and eventual colony failure without replacement. Early detection enables beekeepers to intervene in time.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"What data and methods are used to detect whether a hive has a healthy queen?",{"text":81,"@type":77},"The approach records acoustic signals from beehives and applies machine learning algorithms to identify the presence or absence of a healthy queen. Techniques include analyzing audio signal features and training models on known conditions.",{"name":83,"@type":74,"acceptedAnswer":84},"How do the authors validate their machine learning model?",{"text":85,"@type":77},"They validate the model by applying it to a second dataset collected in a different location and over a different time period, demonstrating generalization beyond the original recording conditions.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":20,"doc_module":4,"doc_module_name":47,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":47,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":47,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":47,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":47,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":47,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":22,"doc_module":4,"doc_module_name":47,"category_name":137,"show_sort_weight":107,"slug":138},"General","general"]