Summary
- Year: 2023
- Total papers: 22
- Research papers hub
- All years
Topics
- Audio Acoustics (2)
- Bee Behaviour (8)
- Colony Health (1)
- Computer Vision (12)
- Datasets Benchmarks (2)
- Edge AI Energy (1)
- IoT Sensors (8)
- Pollination Ecology (4)
- Reviews Surveys (3)
- Varroa Health (4)
Product areas
- Colony Health (7)
- Gate Tracker (7)
- Hive Scanner (1)
- Monitoring Platform (9)
Papers by topic
Audio Acoustics
- Automated, non-invasive Varroa mite detection by vibrational measurements of gait combined with machine learning — 🇬🇧 Nottingham Trent University
- Identifying Queenlessness in Honeybee Hives from Audio Signals Using Machine Learning — 🇬🇧 Kingston University
Bee Behaviour
- Ambient Electromagnetic Radiation as a Predictor of Honey Bee (Apis mellifera) Traffic in Linear and Non-Linear Regression: Numerical Stability, Physical Time and Energy Efficiency — 🇺🇸 Utah State University
- Approximation of functions determining colony activity using neural networks. Master thesis — 🇨🇿 Brno University of Technology
- Comparing weight dynamics between urban and rural honeybee colonies in Latvia — 🇱🇻 Latvia University of Life Sciences and Technologies
- Defined exposure of honey bee colonies to simulated radiofrequency electromagnetic fields (RF-EMF): Negative effects on the homing ability, but not on brood development or longevity — 🇩🇪 University of Hohenheim; 🇩🇪 Karlsruhe Institute of Technology
- Honey bees modify plantpollinator network structure — 🇨🇦 University of Alberta
- Identifying Queenlessness in Honeybee Hives from Audio Signals Using Machine Learning — 🇬🇧 Kingston University
- Precision Monitoring of Honey Bee (Hymenoptera: Apidae) Activity and Pollen Diversity during Pollination to EvaluateColony Health — 🇦🇺 La Trobe University
- The Be-Hive Project - Counting Bee Traffic based on Deep Learning and Pose Estimation — 🇨🇾 CYENS Centre of Excellence; 🇨🇾 Cyprus University of Technology; 🇳🇱 University of Twente
Colony Health
- Recognizing Beehives’ Health Abnormalities Based on Mobile Net Deep Learning Model — 🇪🇬 Egyptian Russian University; 🇪🇬 Cairo University; 🇪🇬 Tanta University; 🇪🇬 Scientific Research Group in Egypt
Computer Vision
- Accuracy vs. Energy: An Assessment of Bee Object Inference inVideos from On-Hive Video Loggers with YOLOv3,YOLOv4-Tiny, and YOLOv7-Tiny — 🇺🇸 Utah State University
- Approximation of functions determining colony activity using neural networks. Master thesis — 🇨🇿 Brno University of Technology
- BeeNet: An End-To-End Deep Network For Bee Surveillance — 🇦🇺 Australian National University; 🇧🇩 BRAC University; 🇦🇺 Curtin University; 🇦🇺 Commonwealth Scientific and Industrial Research Organisation
- Detection of Varroa destructor Infestation of Honeybees Based on Segmentation and Object Detection Convolutional Neural Networks — 🇨🇳 Shandong Agriculture University
- Labeled dataset for bee detection and direction estimation on entrance to beehive — 🇱🇹 Vilnius Gediminas Technical University
- Machine Learning and Computer Vision Techniques in Continuous Beehive Monitoring Applications: A Survey — 🇨🇿 Brno University of Technology
- Pollinators as Data Collectors: Estimating Floral Diversity with Bees and Computer Vision — 🇩🇪 Karlsruhe Institute of Technology; 🇩🇪 apic.ai GmbH
- Precision Monitoring of Honey Bee (Hymenoptera: Apidae) Activity and Pollen Diversity during Pollination to EvaluateColony Health — 🇦🇺 La Trobe University
- Raspberry Pi Bee Health Monitoring Device — 🇨🇿 Brno University of Technology
- Recognizing Beehives’ Health Abnormalities Based on Mobile Net Deep Learning Model — 🇪🇬 Egyptian Russian University; 🇪🇬 Cairo University; 🇪🇬 Tanta University; 🇪🇬 Scientific Research Group in Egypt
- The Be-Hive Project - Counting Bee Traffic based on Deep Learning and Pose Estimation — 🇨🇾 CYENS Centre of Excellence; 🇨🇾 Cyprus University of Technology; 🇳🇱 University of Twente
- Varroa Destructor Classification Using Legendre Fourier Moments with Different Color Spaces — 🇲🇽 Universidad Politécnica de Tulancingo
Datasets Benchmarks
- BeeNet: An End-To-End Deep Network For Bee Surveillance — 🇦🇺 Australian National University; 🇧🇩 BRAC University; 🇦🇺 Curtin University; 🇦🇺 Commonwealth Scientific and Industrial Research Organisation
- Labeled dataset for bee detection and direction estimation on entrance to beehive — 🇱🇹 Vilnius Gediminas Technical University
Edge AI Energy
- Accuracy vs. Energy: An Assessment of Bee Object Inference inVideos from On-Hive Video Loggers with YOLOv3,YOLOv4-Tiny, and YOLOv7-Tiny — 🇺🇸 Utah State University
IoT Sensors
- Ambient Electromagnetic Radiation as a Predictor of Honey Bee (Apis mellifera) Traffic in Linear and Non-Linear Regression: Numerical Stability, Physical Time and Energy Efficiency — 🇺🇸 Utah State University
- Automated, non-invasive Varroa mite detection by vibrational measurements of gait combined with machine learning — 🇬🇧 Nottingham Trent University
- Bee colony remote monitoring based on IoT using ESP-NOW protocol — 🇱🇻 Latvia University of Life Sciences and Technologies
- Comparing weight dynamics between urban and rural honeybee colonies in Latvia — 🇱🇻 Latvia University of Life Sciences and Technologies
- Defined exposure of honey bee colonies to simulated radiofrequency electromagnetic fields (RF-EMF): Negative effects on the homing ability, but not on brood development or longevity — 🇩🇪 University of Hohenheim; 🇩🇪 Karlsruhe Institute of Technology
- HiveLink – IoT based Smart Bee Hive MonitoringSystem — 🇮🇳 St. Joseph Engineering College; 🇮🇳 Canara Engineering College
- Precision Beekeeping Systems: State of the Art, Pros and Cons, and Their Application as Tools for Advancing theBeekeeping Sector — 🇮🇹 University of Tuscia; 🇮🇹 University of Napoli Federico II
- Raspberry Pi Bee Health Monitoring Device — 🇨🇿 Brno University of Technology
Pollination Ecology
- Honey bees modify plantpollinator network structure — 🇨🇦 University of Alberta
- Importance of GIS solutions for beekeepers: a review — 🇱🇻 Latvia University of Life Sciences and Technologies
- Pollinators as Data Collectors: Estimating Floral Diversity with Bees and Computer Vision — 🇩🇪 Karlsruhe Institute of Technology; 🇩🇪 apic.ai GmbH
- Precision Monitoring of Honey Bee (Hymenoptera: Apidae) Activity and Pollen Diversity during Pollination to EvaluateColony Health — 🇦🇺 La Trobe University
Reviews Surveys
- Importance of GIS solutions for beekeepers: a review — 🇱🇻 Latvia University of Life Sciences and Technologies
- Machine Learning and Computer Vision Techniques in Continuous Beehive Monitoring Applications: A Survey — 🇨🇿 Brno University of Technology
- Precision Beekeeping Systems: State of the Art, Pros and Cons, and Their Application as Tools for Advancing theBeekeeping Sector — 🇮🇹 University of Tuscia; 🇮🇹 University of Napoli Federico II
Varroa Health
- Automated, non-invasive Varroa mite detection by vibrational measurements of gait combined with machine learning — 🇬🇧 Nottingham Trent University
- Detection of Varroa destructor Infestation of Honeybees Based on Segmentation and Object Detection Convolutional Neural Networks — 🇨🇳 Shandong Agriculture University
- Recognizing Beehives’ Health Abnormalities Based on Mobile Net Deep Learning Model — 🇪🇬 Egyptian Russian University; 🇪🇬 Cairo University; 🇪🇬 Tanta University; 🇪🇬 Scientific Research Group in Egypt
- Varroa Destructor Classification Using Legendre Fourier Moments with Different Color Spaces — 🇲🇽 Universidad Politécnica de Tulancingo