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Research & science

We want to be aware of recent and historical development in research. Here we track publications that are most relevant.

An good overview is presented in Machine Learning and Computer Vision Techniques in Bee Monitoring Applications

Teams

World-wide there are several research teams dealing in the area of digital beekeeping

One-time yet very notable works were also in:

Scientific publications

hive area + methodTeam / UniversityPublication NameyearmethodAuthorsURL
👁️‍🗨️Entrance Observer South Westphalia University of Applied Sciences🔬BeeAlarmed. Masters thesis2021image/videoHickert F.Ries S.
👁️‍🗨️Entrance Observer Federal University of Itajuba in BrazilJosé Anderson Reis Master thesis - Pi Zero 2W, Yolo v82024Ferreira Filho JAReis Jhttps://www.hackster.io/518000/buzztech-machine-learning-at-the-edge-07c951
Utah State UniversityAmbient Electromagnetic Radiation as a Predictor of Honey Bee (Apis mellifera) Traffic in Linear and Non-Linear Regression: Numerical Stability, Physical Time and Energy Efficiency2023Coster DHornberger DKulyukin AVKulyukin VTkachenko A
nestKingston UniversityIdentifying Queenlessness in Honeybee Hives from Audio Signals Using Machine Learning2023audioDuran OHunter GNebel JCRuvinga S
BeeNet: An End-To-End Deep Network For Bee Surveillance2023
Honey bees (Apis mellifera) modify plantpollinator network structure, but do not alter wild species’ interactions2023Acorn JHFrost CMWorthy SH
👁️‍🗨️Entrance Observer Puerto RicoAutomated Video Monitoring of Unmarked and Marked Honey Bees at the Hive Entrance2022image / videoAgosto-Rivera JLAlvarez Rios MBranson KChan JGiray TMégret RRodriguez IF
👁️‍🗨️Entrance Observer Puerto RicoHoneybee Re-identification in Video: New Datasets and Impact of Self-supervision2022image / videoAgosto-Rivera JLCarrion HChan JGiray TMégret R
Utah State UniversityIntegration of Scales and Cameras in Nondisruptive Electronic Beehive Monitoring: On the Within-Day Relationship of Hive Weight and Traffic in Honeybee (Apis mellifera) Colonies in Langstroth Hives in Tucson, Arizona, USA 2022Kulyukin VMeikle WPrice KTkachenko AWeiss M
👁️‍🗨️Entrance Observer Brno University of TechnologyMachine Learning and Computer Vision Techniques in Bee Monitoring Applications2022image / videoBilik SHorak KKratochvila LRicanek DRichter MZambanini SZemcik T
👁️‍🗨️Entrance Observer Utah State UniversityBeePIV: A Method to Measure Apis Mellifera Traffic with Particle Image Velocimetry in Videos2021image / videoKulyukin VMinichiello AMukherjee STruscott T
👁️‍🗨️Entrance Observer Utah State University Audio, Image, Video, and Weather Datasets for Continuous Electronic Beehive Monitoring2021image / videoKulyukin V
👁️‍🗨️Entrance Observer Utah State UniversityOn Image Classification in Video Analysis of Omnidirectional Apis Mellifera Traffic: Random Reinforced Forests vs. Shallow Convolutional Networks2021image / videoKulyukin V
nestOkinawa Institute of Science and Technology Graduate University🔬Markerless tracking of an entire honey bee colony2021image / videoBozek KHebert LMikheyev APortugal YStephens G
👁️‍🗨️Entrance Observer Incheon National University🔬Honeybee In-Out Monitoring System by Object Recognition and Tracking from Real-Time Webcams2021videoChoi BJJeong CHJung JWKwon HWLee MIRyu JS
👁️‍🗨️Entrance Observer Utah State UniversityApplication of Digital Particle Image Velocimetry to Insect Motion: Measurement of Incoming, Outgoing, and Lateral Honeybee Traffic2020image / videoKulyukin VMukherjee S
nestFederal Technological University of Paraná🔬Automatic detection and classification of honey bee comb cells using deep learning2020image / videoAlves TBiron DFilho PLDPGiray TJunior ACNeves CJPinto MARodrigues PJVentura P
nestThe prediction of swarming in honeybee colonies using vibrational spectra2020audioBencsik MCrauser DDelso NSLe Conte YNewton MIPioz MRamsey MTReyes M
👁️‍🗨️Entrance Observer Karlsruhe Institute of Technology🔬DeepBees – Building and Scaling Convolutional Neuronal Nets For Fast and Large-scale Visual Monitoring of Bee Hives2019image / videoMarstaller JStock STausch F
👁️‍🗨️Entrance Observer Utah State UniversityOn Video Analysis of Omnidirectional Bee Traffic: Counting Bee Motions with Motion Detection and Image Classification2019image / videoKulyukin VMukherjee S
👁️‍🗨️Entrance ObserverUtah State UniversityBEE SHADOW RECOGNITION IN VIDEO ANALYSIS OF OMNIDIRECTIONAL BEE TRAFFIC (Master thesis)2019image / videoAlavala LKulyukin V
👁️‍🗨️Entrance ObserverPuerto Rico🔬LabelBee: a web platform for large-scale semi-automated analysis of honeybee behavior from video2019image/videoAcuna EAgosto-Rivera JLFord ICGiray TMégret RRodriguez IF
👁️‍🗨️Entrance ObserverPuerto RicoRecognition of Pollen-bearing Bees from Video using Convolutional Neural Network2018image / videoAcuna EAgosto-Rivera JLGiray TMégret RRodriguez IF
Utah State UniversityToward Audio Beehive Monitoring: Deep Learning vs. Standard Machine Learning in Classifying Beehive Audio Samples2018audioAmlathe PKulyukin VMukherjee S
nestOkinawa Institute of Science and Technology Graduate UniversityTowards dense object tracking in a 2D honeybee hive2018image / videoBozek KHebert LMikheyev A
nestVienna University of TechnologyA Preliminary Study of Image Analysis for Parasite Detection on Honey Bees2018image / videoKampel MRadeva PRemeseiro BSchurischuster S
nestThe development of honey bee colonies assessed using a new semi-automated brood counting method: CombCount2018imageBarron ABBruce JColin TMeikle WG
👁️‍🗨️Entrance ObserverUtah State UniversityIn Situ Omnidirectional Vision-Based Bee Counting Using 1D Haar Wavelet Spikes2017image / videoKulyukin V
👁️‍🗨️Entrance ObserverUtah State UniversityA Computer Vision Algorithm for Omnidirectional Bee Counting at Langstroth Beehive Entrances2016image / videoKulyukin VReka SK
👁️‍🗨️Entrance ObserverUtah State UniversityToward Sustainable Electronic Beehive Monitoring: Algorithms for Omnidirectional Bee Counting from Images and Harmonic Analysis of Buzzing Signals2016image / videoKulyukin VReka SK
nestUtah State UniversityDigitizing Buzzing Signals into A440 Piano Note Sequences and Estimating Forager Traffic Levels from Images in Solar-Powered, Electronic Beehive Monitoring 2016audioKulyukin VPuTnam MReka SK
Toward an intelligent and efficient beehive: A survey of precision beekeeping systems and servicesAmmar DHadjur HLefevre L
👁️‍🗨️Entrance ObserverUtah State UniversityAccuracy vs. Energy: An Assessment of Bee Object Inference in Videos from On-Hive Video Loggers with YOLOv3, YOLOv4-Tiny, and YOLOv7-Tinyimage / videoKulyukin AVKulyukin V
Puerto RicoMultiple Animals Tracking in Video Using Part Affinity FieldsAcuna EAgosto-Rivera JLBranson KEgnor RGiray TMégret RRodriguez IF
Visual Diagnosis of the Varroa Destructor Parasitic Mite in Honeybees Using Object Detector TechniquesBilik SBostik OHorak KHybl MKratochvila LLigocki AZalud LZemcik T
Biodiversity, conservation and current threats to European honeybees2009Dall'Olio RDe la Rúa PJaffé RMuñoz ISerrano J
BeeNet: An End-To-End Deep Network For Bee Surveillance2003Asif Ahmed K.Hossain Z.Liu X.Siddiqua R.Yoo J.
Varroa Destructor Classification Using Legendre–Fourier Moments with Different Color Spaces2023
🌻Honeybees are far too insufficient to supply optimum pollination services in agricultural systems worldwide2022
🌻The lost opportunity from insufficient pollinators for global food supplies and human health
Brno University of Technology🔬Machine Learning and Computer Vision Techniques in Continuous Beehive Monitoring Applications: A Survey2023Bilik SHorak KKratochvila LRicanek DRichter MZambanini SZemcik T
Brno University of TechnologyVarroa destructor detection on honey bees using hyperspectral imagery2024
👁️‍🗨️Entrance ObserverBrno University of TechnologyRaspberry Pi Bee Health Monitoring Device2023image / videoBilik SHorak KNevlacil Jhttps://arxiv.org/pdf/2304.14444
Evaluation of the honey bee colonies weight gain during the intensive foraging period2022weight
Brno University of TechnologyApproximation of functions determining colony activity using neural networks. Master thesis2023audioHonec P.Nevláčil J.


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Related journals

Apidologie

http://www.apian.ch/pages/about/