[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127093-en":3,"doc-seo-127093-105":30,"detail-sidebar-cat-0-en-105":91},{"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":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},127093,5909887256941,"Levi","https://ap-avatar.wpscdn.com/davatar_9964176cb1d06d4a9deccf72a44ae3dc",8,"Research & Report","A Machine Learning Approach for Queen Bee Detection Through Remote Audio Sensing - read online free","Honeybees underpin ecosystem stability and agricultural productivity through crop pollination, yet rising mortality linked to stressors such as climate change makes effective colony monitoring urgent. Remote audio sensing offers a practical route to observe hive status. This study investigates lightweight machine learning models and compressed-feature extraction aimed at future microcontroller deployment. Support vector machines and neural network classifiers are evaluated while varying audio chunk durations, hyperparameters, and combining recordings from multiple hives across different datasets.","POLITECNICO DI TORINO  \nRepository ISTITUZIONALE  \nA Machine Learning Approach for Queen Bee Detection Through Remote Audio Sensing to Safeguard Honeybee Colonies  \nOriginal  \nA Machine Learning Approach for Queen Bee Detection Through Remote Audio Sensing to Safeguard Honeybee Colonies / Barbisan, Luca; Turvani, Giovanna; Riente, Fabrizio. -In: IEEE TRANSACTIONS ON AGRIFOOD ELECTRONICS.. -ISSN 2771-9529. -2:2(2024), pp. 236-243. [10 . 1109/tafe.2024.3406648]  \nAvailability:  \nThis version is available at: 11583/2995168 since: 2024-12-10T22:32:51Z  \nPublisher: IEEE  \nPublished  \nDOI:10.1109/tafe.2024.3406648  \nTerms of use:  \nThis article is made available under terms and conditions as specified in the corresponding bibliographic description in the repository  \nPublisher copyright  \n(Article begins on next page)  \n17 February 2025  \nA Machine Learning Approach for Queen Bee Detection Through Remote Audio Sensing to Safeguard Honeybee Colonies  \nLuca Barbisan, Student Member, IEEE, Giovanna Turvani, and Fabrizio Riente , Member, IEEE  \nAbstract—Honeybees play a pivotal role in maintaining global ecosystems and agricultural productivity through their indispensable contribution to crop pollination. However, the alarming rise in honeybee mortality, attributed to various stress factors including climate change, has highlighted the urgency of implementing effective monitoring strategies. Remote sensing of beehives emerges as a promising solution, with a focus on understanding and mitigating the impacts of these stressors. Differently from other approaches proposed in the literature, this study specifically explores the potential of lightweight machine learning models and the extraction of compressedfeature to enablefuture deployment on microcontroller devices. The experimentation involves the application of support vector machines and neural network classifiers, considering the influence of variable audio chunk durations, the utilization of different hyperparameters and combining the audio recorded in several hives and available in different datasets.  \nIndex Terms—Bee monitoring, edge computing, environmental monitoring, machine learning.  \nI. INTRODUCTION  \nP RESERVING global biodiversity is one of the current chal  \nlenges ofthe current era. Several studies have highlighted a decline in insects on both local and global scales [1], all of these are important for maintaining a balanced ecosystem. Among them, honeybees stand out as crucial contributors in global agricultural production, pollinating approximately 70 out of thenearly 100 crop species that contribute to 90% of the world’s food supply.  \nUnfortunately, a significant increase in colony losses has been reported worldwide in recent years, mainly attributed to the phenomenon known as “colony collapse disorder’ [2] . Factors, such as climate change, intensive agriculture, land-use alterations, pesticides, biodiversity decline, Varroa mites, and pollution, are identified as the primary causes of global bee mortality. This decline in honeybee health has prompted a growing demand among beekeepers and researchers for innovative methods to monitor colony health effectively.  \nDifferent factors can be monitored to detect possible problems that affect the health of a beehive [3] . Some studies focused  \nManuscript received 5 February 2024; revised 4 May 2024; accepted 22 May 2024. Date of publication 14 June 2024; date of current version 10 October 2024. This work was supported by the project PNRR-NGEU under Grant MUR-DM 352/2022 . This article was recommended by Associate Editor F. Rivet.(Corresponding author: Fabrizio Riente.)  \nThe authors are with the Electronics and Telecommunications Department of Politecnico di Torino, 10129 Torino, Italy (e-mail: fabrizio.riente@polito.it) .  \nDigital Object Identifier 10.1109/TAFE.2024.3406648  \non the detection of swarm activities using a combination of weight sensors and microphones [4] or accelerometers [5], [6] and analyzing the signals by m","cbCaiqgAPlYqnEy3","https://ap.wps.com/l/cbCaiqgAPlYqnEy3","pdf",2019462,1,9,"English","en",105,"# Abstract\n## Introduction\n## Related Work and Motivation","[{\"question\":\"Why is queen bee detection important for honeybee colonies?\",\"answer\":\"The queen bee is the only fertile female and is essential for colony survival. Detecting absence early helps beekeepers act before the hive loses viability.\"},{\"question\":\"What is the main technical goal of the study?\",\"answer\":\"To enable future deployment by using lightweight machine learning models and compressed-feature extraction on microcontroller devices for remote audio-based detection.\"},{\"question\":\"How are the machine learning models evaluated in the experiments?\",\"answer\":\"Experiments use support vector machines and neural network classifiers while varying audio chunk durations, hyperparameters, and combining audio recordings from several hives across different datasets.\"}]","A Machine Learning Approach for Queen Bee Detection Through Remote Audio Sensing - read online free | PDF",1785936817,23,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"a-machine-learning-approach-for-queen-bee-detection-through-remote-audio-sensing-read-online-free","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/a-machine-learning-approach-for-queen-bee-detection-through-remote-audio-sensing-read-online-free/127093/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is queen bee detection important for honeybee colonies?","Question",{"text":75,"@type":76},"The queen bee is the only fertile female and is essential for colony survival. Detecting absence early helps beekeepers act before the hive loses viability.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What is the main technical goal of the study?",{"text":80,"@type":76},"To enable future deployment by using lightweight machine learning models and compressed-feature extraction on microcontroller devices for remote audio-based detection.",{"name":82,"@type":73,"acceptedAnswer":83},"How are the machine learning models evaluated in the experiments?",{"text":84,"@type":76},"Experiments use support vector machines and neural network classifiers while varying audio chunk durations, hyperparameters, and combining audio recordings from several hives across different datasets.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]