Summary
- Year: 2026
- Total papers: 33
- Research papers hub
- All years
Topics
- Audio Acoustics (8)
- Bee Behaviour (10)
- Bee Counting (1)
- Bee Traffic (1)
- Behavior Recognition (1)
- Colony Health (8)
- Computer Vision (16)
- Datasets (1)
- Datasets Benchmarks (6)
- Edge AI Energy (10)
- IoT Sensors (14)
- Pollination Ecology (2)
- Pollination Monitoring (1)
- Precision Beekeeping (8)
- Reviews Surveys (3)
- Robotics (1)
- Varroa Health (5)
Product areas
- Colony Health (18)
- Edge Device (7)
- Gate Tracker (2)
- Hive Scanner (6)
- Monitoring Platform (27)
- Robotics (1)
Papers by topic
Audio Acoustics
- A Multimodal Machine Learning System for Non-Invasive Detection of Varroa destructor Infestations in Honey Bee Colonies — 🇺🇸 Green Valley High School
- Acoustic Signatures of Hive: Detecting Queen Bee Absence Through Machine Learning of Short Audio Segments — 🇨🇱 Universidad de Viña del Mar; 🇨🇱 Universidad Técnica Federico Santa María
- BeeVe: Unsupervised Acoustic State Discovery in Honey Bee Buzzing — 🇺🇳 arXiv author-supplied preprint by Hamze Hammami and Nidhal Abdulaziz
- Communication-efficient Embedded FFT Processing for Acoustic Telemetry in LPWAN-based Beehive Monitoring Systems — 🇵🇱 Lodz University of Technology
- Development of Wingbeat-Based Acoustic Health Monitoring System for Bee Colonies — 🇹🇼 National Formosa University
- Improved Monitoring of Honey bee Colony Strength via Audio IoT Sensors, Modulation Tensorgrams and Recurrent Neural Networks — 🇨🇦 Institut national de la recherche scientifique (INRS); 🇨🇦 Université Laval; 🇨🇦 Nectar Technologies Inc.
- On the Prediction of Varroa Mite Infestations in Honeybee Colonies via Acoustic Monitoring — 🇨🇦 Institut national de la recherche scientifique (INRS); 🇨🇦 Nectar Technologies Inc.; 🇨🇦 Université Laval
- Spectrogram-Based Deep Learning Models for Acoustic Identification of Honey Bees in Complex Environmental Noises — 🇵🇰 Namal University; 🇵🇰 University of Mianwali; 🇦🇪 Abu Dhabi University; 🇹🇷 Nişantaşı University
Bee Behaviour
- A Hall-Effect Sensor-Based Queen Bee Detection System – a Proof of Concept — 🇵🇱 AGH University of Krakow; 🇵🇱 Wrocław University of Science and Technology
- Acoustic Signatures of Hive: Detecting Queen Bee Absence Through Machine Learning of Short Audio Segments — 🇨🇱 Universidad de Viña del Mar; 🇨🇱 Universidad Técnica Federico Santa María
- An open-source high-precision hive for long-term honeybee observation and research — 🇨🇿 Czech Technical University in Prague; 🇦🇹 University of Graz
- Assessing Honey Bee Colony Health Using Temperature Time Series — 🇦🇺 The University of Sydney; 🇦🇺 Macquarie University
- BeeVe: Unsupervised Acoustic State Discovery in Honey Bee Buzzing — 🇺🇳 arXiv author-supplied preprint by Hamze Hammami and Nidhal Abdulaziz
- COMB: Common Open Modular robotic platform for Bees — 🇩🇪 University of Konstanz; 🇩🇪 Freie Universität Berlin
- Continuous Non-Invasive Monitoring of Hive Entrance Activity Reveals Honey Bee Colony Dynamics — 🇹🇷 Van Yüzüncü Yıl University
- Detection and classification of honeybee castes using thermal imaging and deep learning — 🇮🇷 Razi University
- Estimating colony strength and pollination efficiency in honey bees using a novel dataset and deep learning-based models — 🇺🇸 University of Arkansas at Fayetteville; 🇺🇸 Washington State University; 🇺🇸 University of Arkansas System; 🇺🇸 Mississippi State University; 🇺🇸 University of Tennessee at Knoxville
- Physics-aware vision instrumentation for stingless bee counting at hive entrance using hybrid edge-cloud object detection — 🇲🇾 Universiti Teknologi Malaysia; 🇮🇩 Universitas Negeri Jakarta; 🇮🇩 Institut Teknologi Indonesia; 🇮🇩 Politeknik Negeri Bandung; 🇮🇩 National Research and Innovation Agency
Bee Counting
- Honeybee Counting on Comb Images via Part-Level Annotation and Hungarian Matching — 🇯🇵 Utsunomiya University
Bee Traffic
- The Relevance of Compound Events in Bee Traffic Monitoring — 🇵🇷 University of Puerto Rico at Río Piedras
Behavior Recognition
- The Relevance of Compound Events in Bee Traffic Monitoring — 🇵🇷 University of Puerto Rico at Río Piedras
Colony Health
- A Wireless Sensor Platform for Beehive Monitoring — 🇺🇸 North Dakota State University; 🇺🇸 USDA Agricultural Research Service
- An Automated AI-Based Vision Inspection System for Bee Mite and Deformed Bee Detection Using YOLO Models — 🇰🇷 Kangwon National University; 🇰🇷 National Institute of Agricultural Sciences; 🇰🇷 Terramolab Ltd.
- Deep Learning and Computer Vision for Honey Bee Health Monitoring: A Systematic Survey and Future Directions — 🇮🇳 SSVPS's Bapusaheb Shivajirao Deore College of Engineering
- From Hive Sensors to Environmental DNA: Toward a Systems Biology Framework for Honeybee-Based Early Warning of Colony and Ecosystem Health — 🇨🇳 Yangzhou University; 🇸🇦 Imam Mohammad Ibn Saud Islamic University
- Honeybee Counting on Comb Images via Part-Level Annotation and Hungarian Matching — 🇯🇵 Utsunomiya University
- Improved Monitoring of Honey bee Colony Strength via Audio IoT Sensors, Modulation Tensorgrams and Recurrent Neural Networks — 🇨🇦 Institut national de la recherche scientifique (INRS); 🇨🇦 Université Laval; 🇨🇦 Nectar Technologies Inc.
- On the Prediction of Varroa Mite Infestations in Honeybee Colonies via Acoustic Monitoring — 🇨🇦 Institut national de la recherche scientifique (INRS); 🇨🇦 Nectar Technologies Inc.; 🇨🇦 Université Laval
- Transforming Beekeeping Through Technology: A Systematic Review of Precision Beekeeping — 🇧🇳 Universiti Brunei Darussalam; 🇱🇰 Uva Wellassa University
Computer Vision
- A Multimodal Machine Learning System for Non-Invasive Detection of Varroa destructor Infestations in Honey Bee Colonies — 🇺🇸 Green Valley High School
- An Automated AI-Based Vision Inspection System for Bee Mite and Deformed Bee Detection Using YOLO Models — 🇰🇷 Kangwon National University; 🇰🇷 National Institute of Agricultural Sciences; 🇰🇷 Terramolab Ltd.
- An open-source high-precision hive for long-term honeybee observation and research — 🇨🇿 Czech Technical University in Prague; 🇦🇹 University of Graz
- Continuous Non-Invasive Monitoring of Hive Entrance Activity Reveals Honey Bee Colony Dynamics — 🇹🇷 Van Yüzüncü Yıl University
- Deep Learning and Computer Vision for Honey Bee Health Monitoring: A Systematic Survey and Future Directions — 🇮🇳 SSVPS's Bapusaheb Shivajirao Deore College of Engineering
- Detection and classification of honeybee castes using thermal imaging and deep learning — 🇮🇷 Razi University
- Estimating colony strength and pollination efficiency in honey bees using a novel dataset and deep learning-based models — 🇺🇸 University of Arkansas at Fayetteville; 🇺🇸 Washington State University; 🇺🇸 University of Arkansas System; 🇺🇸 Mississippi State University; 🇺🇸 University of Tennessee at Knoxville
- FAIRHiveFrames-1K: A Public FAIR Dataset of 1265 Annotated Hive Frame Images with Preliminary YOLOv8 and YOLOv11 Baselines — 🇺🇸 Utah State University
- Honeybee Counting on Comb Images via Part-Level Annotation and Hungarian Matching — 🇯🇵 Utsunomiya University
- InsectDCT: A generalized pipeline for detection, taxonomic classification, and tracking of insects in camera-trap recordings — 🇩🇰 Aarhus University; 🇩🇪 Helmholtz Centre for Environmental Research; 🇪🇸 Mediterranean Institute for Advanced Studies; 🇬🇪 Ilia State University
- Interpretable Deep Learning for Varroa Mite Detection: Integrating Deblurring, Morphology-Preserving Preprocessing, and Explainability Analysis — 🇰🇷 Kangwon National University; 🇰🇷 National Institute of Agricultural Sciences
- M3DANet: A Lightweight Semi-Supervised Network and Embedded System for Bee Colony Counting — 🇨🇳 Shandong Agricultural University; 🇨🇳 Apiculture Institute of Jiangxi Province
- Physics-aware vision instrumentation for stingless bee counting at hive entrance using hybrid edge-cloud object detection — 🇲🇾 Universiti Teknologi Malaysia; 🇮🇩 Universitas Negeri Jakarta; 🇮🇩 Institut Teknologi Indonesia; 🇮🇩 Politeknik Negeri Bandung; 🇮🇩 National Research and Innovation Agency
- PolliCrop: A high-throughput computer vision pipeline for pollinator monitoring in agroecosystems — 🇫🇷 INRAE; 🇫🇷 CNRS; 🇺🇸 University of California, Berkeley; 🇩🇪 Julius Kühn Institute; 🇩🇪 Technische Universität Braunschweig
- The Relevance of Compound Events in Bee Traffic Monitoring — 🇵🇷 University of Puerto Rico at Río Piedras
- Transforming Beekeeping Through Technology: A Systematic Review of Precision Beekeeping — 🇧🇳 Universiti Brunei Darussalam; 🇱🇰 Uva Wellassa University
Datasets
- Time-series dataset of honey bee colony dynamics before, during, and after sunflower pollination — 🇺🇦 AmoHive / Ukraine smart-hive deployment
Datasets Benchmarks
- Detection and classification of honeybee castes using thermal imaging and deep learning — 🇮🇷 Razi University
- Estimating colony strength and pollination efficiency in honey bees using a novel dataset and deep learning-based models — 🇺🇸 University of Arkansas at Fayetteville; 🇺🇸 Washington State University; 🇺🇸 University of Arkansas System; 🇺🇸 Mississippi State University; 🇺🇸 University of Tennessee at Knoxville
- FAIRHiveFrames-1K: A Public FAIR Dataset of 1265 Annotated Hive Frame Images with Preliminary YOLOv8 and YOLOv11 Baselines — 🇺🇸 Utah State University
- InsectDCT: A generalized pipeline for detection, taxonomic classification, and tracking of insects in camera-trap recordings — 🇩🇰 Aarhus University; 🇩🇪 Helmholtz Centre for Environmental Research; 🇪🇸 Mediterranean Institute for Advanced Studies; 🇬🇪 Ilia State University
- PolliCrop: A high-throughput computer vision pipeline for pollinator monitoring in agroecosystems — 🇫🇷 INRAE; 🇫🇷 CNRS; 🇺🇸 University of California, Berkeley; 🇩🇪 Julius Kühn Institute; 🇩🇪 Technische Universität Braunschweig
- Spectrogram-Based Deep Learning Models for Acoustic Identification of Honey Bees in Complex Environmental Noises — 🇵🇰 Namal University; 🇵🇰 University of Mianwali; 🇦🇪 Abu Dhabi University; 🇹🇷 Nişantaşı University
Edge AI Energy
- A Wireless Sensor Platform for Beehive Monitoring — 🇺🇸 North Dakota State University; 🇺🇸 USDA Agricultural Research Service
- Adaptive Measurement Noise for Robust Kalman Filtering in Smart Beehive Telemetry — 🇬🇧 University of Westminster; 🇲🇾 Technical University of Malaysia Malacca; 🇫🇮 University of Oulu
- An Automated AI-Based Vision Inspection System for Bee Mite and Deformed Bee Detection Using YOLO Models — 🇰🇷 Kangwon National University; 🇰🇷 National Institute of Agricultural Sciences; 🇰🇷 Terramolab Ltd.
- An intelligent monitoring system for forecasting and anomaly detection in precision beekeeping — 🇫🇷 EFREI Research Lab; 🇫🇷 Université Paris-Panthéon-Assas
- Communication-efficient Embedded FFT Processing for Acoustic Telemetry in LPWAN-based Beehive Monitoring Systems — 🇵🇱 Lodz University of Technology
- InsectDCT: A generalized pipeline for detection, taxonomic classification, and tracking of insects in camera-trap recordings — 🇩🇰 Aarhus University; 🇩🇪 Helmholtz Centre for Environmental Research; 🇪🇸 Mediterranean Institute for Advanced Studies; 🇬🇪 Ilia State University
- M3DANet: A Lightweight Semi-Supervised Network and Embedded System for Bee Colony Counting — 🇨🇳 Shandong Agricultural University; 🇨🇳 Apiculture Institute of Jiangxi Province
- Physics-aware vision instrumentation for stingless bee counting at hive entrance using hybrid edge-cloud object detection — 🇲🇾 Universiti Teknologi Malaysia; 🇮🇩 Universitas Negeri Jakarta; 🇮🇩 Institut Teknologi Indonesia; 🇮🇩 Politeknik Negeri Bandung; 🇮🇩 National Research and Innovation Agency
- Spectrogram-Based Deep Learning Models for Acoustic Identification of Honey Bees in Complex Environmental Noises — 🇵🇰 Namal University; 🇵🇰 University of Mianwali; 🇦🇪 Abu Dhabi University; 🇹🇷 Nişantaşı University
- Technical Specification of a Novel Apivoltaic System: Integrating Digital Hive Monitoring with Photovoltaic Energy Systems — 🇷🇴 University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca; 🇷🇴 APIVOLT S.R.L.; 🇮🇹 University of Molise
IoT Sensors
- A Hall-Effect Sensor-Based Queen Bee Detection System – a Proof of Concept — 🇵🇱 AGH University of Krakow; 🇵🇱 Wrocław University of Science and Technology
- A Multimodal Machine Learning System for Non-Invasive Detection of Varroa destructor Infestations in Honey Bee Colonies — 🇺🇸 Green Valley High School
- A Wireless Sensor Platform for Beehive Monitoring — 🇺🇸 North Dakota State University; 🇺🇸 USDA Agricultural Research Service
- Adaptive Measurement Noise for Robust Kalman Filtering in Smart Beehive Telemetry — 🇬🇧 University of Westminster; 🇲🇾 Technical University of Malaysia Malacca; 🇫🇮 University of Oulu
- An intelligent monitoring system for forecasting and anomaly detection in precision beekeeping — 🇫🇷 EFREI Research Lab; 🇫🇷 Université Paris-Panthéon-Assas
- Assessing Honey Bee Colony Health Using Temperature Time Series — 🇦🇺 The University of Sydney; 🇦🇺 Macquarie University
- Communication-efficient Embedded FFT Processing for Acoustic Telemetry in LPWAN-based Beehive Monitoring Systems — 🇵🇱 Lodz University of Technology
- Development of Wingbeat-Based Acoustic Health Monitoring System for Bee Colonies — 🇹🇼 National Formosa University
- From Hive Sensors to Environmental DNA: Toward a Systems Biology Framework for Honeybee-Based Early Warning of Colony and Ecosystem Health — 🇨🇳 Yangzhou University; 🇸🇦 Imam Mohammad Ibn Saud Islamic University
- Improved Monitoring of Honey bee Colony Strength via Audio IoT Sensors, Modulation Tensorgrams and Recurrent Neural Networks — 🇨🇦 Institut national de la recherche scientifique (INRS); 🇨🇦 Université Laval; 🇨🇦 Nectar Technologies Inc.
- STAG-CN: Spatio-Temporal Apiary Graph Convolutional Network for Disease Onset Prediction in Beehive Sensor Networks — 🇰🇷 Korea University
- Technical Specification of a Novel Apivoltaic System: Integrating Digital Hive Monitoring with Photovoltaic Energy Systems — 🇷🇴 University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca; 🇷🇴 APIVOLT S.R.L.; 🇮🇹 University of Molise
- Time-series dataset of honey bee colony dynamics before, during, and after sunflower pollination — 🇺🇦 AmoHive / Ukraine smart-hive deployment
- Transforming Beekeeping Through Technology: A Systematic Review of Precision Beekeeping — 🇧🇳 Universiti Brunei Darussalam; 🇱🇰 Uva Wellassa University
Pollination Ecology
- InsectDCT: A generalized pipeline for detection, taxonomic classification, and tracking of insects in camera-trap recordings — 🇩🇰 Aarhus University; 🇩🇪 Helmholtz Centre for Environmental Research; 🇪🇸 Mediterranean Institute for Advanced Studies; 🇬🇪 Ilia State University
- PolliCrop: A high-throughput computer vision pipeline for pollinator monitoring in agroecosystems — 🇫🇷 INRAE; 🇫🇷 CNRS; 🇺🇸 University of California, Berkeley; 🇩🇪 Julius Kühn Institute; 🇩🇪 Technische Universität Braunschweig
Pollination Monitoring
- Time-series dataset of honey bee colony dynamics before, during, and after sunflower pollination — 🇺🇦 AmoHive / Ukraine smart-hive deployment
Precision Beekeeping
- A Wireless Sensor Platform for Beehive Monitoring — 🇺🇸 North Dakota State University; 🇺🇸 USDA Agricultural Research Service
- An open-source high-precision hive for long-term honeybee observation and research — 🇨🇿 Czech Technical University in Prague; 🇦🇹 University of Graz
- Communication-efficient Embedded FFT Processing for Acoustic Telemetry in LPWAN-based Beehive Monitoring Systems — 🇵🇱 Lodz University of Technology
- Improved Monitoring of Honey bee Colony Strength via Audio IoT Sensors, Modulation Tensorgrams and Recurrent Neural Networks — 🇨🇦 Institut national de la recherche scientifique (INRS); 🇨🇦 Université Laval; 🇨🇦 Nectar Technologies Inc.
- On the Prediction of Varroa Mite Infestations in Honeybee Colonies via Acoustic Monitoring — 🇨🇦 Institut national de la recherche scientifique (INRS); 🇨🇦 Nectar Technologies Inc.; 🇨🇦 Université Laval
- Technical Specification of a Novel Apivoltaic System: Integrating Digital Hive Monitoring with Photovoltaic Energy Systems — 🇷🇴 University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca; 🇷🇴 APIVOLT S.R.L.; 🇮🇹 University of Molise
- Time-series dataset of honey bee colony dynamics before, during, and after sunflower pollination — 🇺🇦 AmoHive / Ukraine smart-hive deployment
- Transforming Beekeeping Through Technology: A Systematic Review of Precision Beekeeping — 🇧🇳 Universiti Brunei Darussalam; 🇱🇰 Uva Wellassa University
Reviews Surveys
- Deep Learning and Computer Vision for Honey Bee Health Monitoring: A Systematic Survey and Future Directions — 🇮🇳 SSVPS's Bapusaheb Shivajirao Deore College of Engineering
- From Hive Sensors to Environmental DNA: Toward a Systems Biology Framework for Honeybee-Based Early Warning of Colony and Ecosystem Health — 🇨🇳 Yangzhou University; 🇸🇦 Imam Mohammad Ibn Saud Islamic University
- Transforming Beekeeping Through Technology: A Systematic Review of Precision Beekeeping — 🇧🇳 Universiti Brunei Darussalam; 🇱🇰 Uva Wellassa University
Robotics
- COMB: Common Open Modular robotic platform for Bees — 🇩🇪 University of Konstanz; 🇩🇪 Freie Universität Berlin
Varroa Health
- A Multimodal Machine Learning System for Non-Invasive Detection of Varroa destructor Infestations in Honey Bee Colonies — 🇺🇸 Green Valley High School
- An Automated AI-Based Vision Inspection System for Bee Mite and Deformed Bee Detection Using YOLO Models — 🇰🇷 Kangwon National University; 🇰🇷 National Institute of Agricultural Sciences; 🇰🇷 Terramolab Ltd.
- Interpretable Deep Learning for Varroa Mite Detection: Integrating Deblurring, Morphology-Preserving Preprocessing, and Explainability Analysis — 🇰🇷 Kangwon National University; 🇰🇷 National Institute of Agricultural Sciences
- On the Prediction of Varroa Mite Infestations in Honeybee Colonies via Acoustic Monitoring — 🇨🇦 Institut national de la recherche scientifique (INRS); 🇨🇦 Nectar Technologies Inc.; 🇨🇦 Université Laval
- Technical Specification of a Novel Apivoltaic System: Integrating Digital Hive Monitoring with Photovoltaic Energy Systems — 🇷🇴 University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca; 🇷🇴 APIVOLT S.R.L.; 🇮🇹 University of Molise