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Journal articles on the topic 'Hive Monitoring'

Author: Grafiati

Published: 22 February 2025

Last updated: 31 July 2025

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1

Kulyukin, Vladimir A., Aleksey V. Kulyukin, and William G. Meikle. "Discrete Time Series Forecasting in Non-Invasive Monitoring of Managed Honey Bee Colonies: Part II: Are Hive Weight and In-Hive Temperature Seasonal and Colony-Specific?" Sensors 25, no. 14 (2025): 4319. https://doi.org/10.3390/s25144319.

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We explored the stationarity, trend, and seasonality of the hive weight and in-hive temperature of ten managed honey bee (Apis mellifera) colonies at a research apiary of the Carl Hayden Bee Research Center in Tucson, Arizona, USA. The hives were monitored with electronic scales and in-hive temperature sensors from June to October 2022. The weight and temperature were recorded every five minutes around the clock. The collected data were curated into 2160 timestamped weight and 2160 timestamped temperature observations. We performed a systematic autoregressive integrated moving average (ARIMA)

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Khrystyuk, Andriy, and Kirpichnikov Anton. "Automatic apiary care system." Modeling Control and Information Technologies, no. 5 (November 21, 2021): 54–55. http://dx.doi.org/10.31713/mcit.2021.16.

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An automatic control system for remote control and monitoring of bee life parameters in hives is developed. Based on the research of the main parameters of the life of bees in the hive, we have developed a scheme for managing and monitoring the weight of the hive, temperature and humidity, noise level, prevention of theft.

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Kuch, Ostap, and Ilona Lahun. "APIARY MONITORING AND AUTOMATION IOT SYSTEM." Measuring Equipment and Metrology 83, no. 4 (2022): 24–29. http://dx.doi.org/10.23939/istcmtm2022.04.024.

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A system of remote monitoring and automation apiary has been developed. This is a low-cost and scalable solution designed for deployment in distant rural areas. An unconventional solution is applying the industrial standard Modbus protocol to transfer data from the hives to a central server. This made it possible to reduce the cost of the system and standardize it. Monitoring the temperature and humidity inside the hives is important for analyzing the condition of bee colonies. The automation of the temperature and humidity control process is implemented based on a fuzzy model of the servo dri

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Bricout, Augustin, Philippe Leleux, Pascal Acco, et al. "Bee Together: Joining Bee Audio Datasets for Hive Extrapolation in AI-Based Monitoring." Sensors 24, no. 18 (2024): 6067. http://dx.doi.org/10.3390/s24186067.

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Beehive health monitoring has gained interest in the study of bees in biology, ecology, and agriculture. As audio sensors are less intrusive, a number of audio datasets (mainly labeled with the presence of a queen in the hive) have appeared in the literature, and interest in their classification has been raised. All studies have exhibited good accuracy, and a few have questioned and revealed that classification cannot be generalized to unseen hives. To increase the number of known hives, a review of open datasets is described, and a merger in the form of the “BeeTogether” dataset on the open K

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Otesbelgue, Alex, Amara Jean Orth, Chandler David Fong, Carol Anne Fassbinder-Orth, Betina Blochtein, and Maria João Ramos Pereira. "Hidden Markov model for acoustic pesticide exposure detection and hive identification in stingless bees." PLOS One 20, no. 6 (2025): e0325732. https://doi.org/10.1371/journal.pone.0325732.

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Pollinator populations are declining globally at an unprecedented rate, driven by factors such as pathogens, habitat loss, climate change, and the widespread application of pesticides. Although colony losses remain difficult to prevent, precision beekeeping has introduced non-invasive strategies for monitoring hive conditions. Acoustic data, combined with machine learning techniques, has proven effective in detecting stressors and specific events in honeybee colonies; however, such methodologies remain underexplored for stingless bees, a group of native pantropical pollinators. Meliponiculture

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König, Andreas. "An in-hive soft sensor based on phase space features for <i>Varroa</i> infestation level estimation and treatment need detection." Journal of Sensors and Sensor Systems 11, no. 1 (2022): 29–40. http://dx.doi.org/10.5194/jsss-11-29-2022.

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Abstract. Bees are recognized as an indispensable link in the human food chain and general ecological system. Numerous threats, from pesticides to parasites, endanger bees, enlarge the burden on hive keepers, and frequently lead to hive collapse. The Varroa destructor mite is a key threat to bee keeping, and the monitoring of hive infestation levels is of major concern for effective treatment. Continuous and unobtrusive monitoring of hive infestation levels along with other vital bee hive parameters is coveted, although there is currently no explicit sensor for this task. This problem is strik

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Nour Elhouda Bakri, Khaled Bouchoucha, Walid Nagara, and M’Naouer Djemali. "Enhancing honeybee breeding for sustainable agriculture through temperature and relative humidity monitoring." World Journal of Advanced Research and Reviews 21, no. 2 (2024): 286–92. http://dx.doi.org/10.30574/wjarr.2024.21.2.0412.

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Through their vital role in pollination, honeybee colonies play a crucial part in sustaining biodiversity and ensuring global food security. This paper aims to: 1) assess temperature and relative humidity variations within the hive and at the brood level; 2) determine genetic parameters for these traits; and 3) predict Breeding Values (PBVs) for honeybee colonies. Temperature and relative humidity data, during the period 2020-2023, were collected in Northern Tunisia using sensors placed inside hives and at the brood level. A dataset comprising 214,128 records for temperature and relative humid

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Nour, Elhouda Bakri, Bouchoucha Khaled, Nagara Walid, and Djemali M'Naouer. "Enhancing honeybee breeding for sustainable agriculture through temperature and relative humidity monitoring." World Journal of Advanced Research and Reviews 21, no. 2 (2024): 286–92. https://doi.org/10.5281/zenodo.13996572.

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Through their vital role in pollination, honeybee colonies play a crucial part in sustaining biodiversity and ensuring global food security. This paper aims to: 1) assess temperature and relative humidity variations within the hive and at the brood level; 2) determine genetic parameters for these traits; and 3) predict Breeding Values (PBVs) for honeybee colonies. Temperature and relative humidity data, during the period 2020-2023, were collected in Northern Tunisia using sensors placed inside hives and at the brood level. A dataset comprising 214,128 records for temperature and relative humid

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Krishnasamy, Venkateswaran, N. Sridhar, and L. Niranjan. "IoT-Based Beehive Monitoring System for Real-Time Monitoring of Apis cerana indica Colonies." Sociobiology 70, no. 4 (2023): e9352. http://dx.doi.org/10.13102/sociobiology.v70i4.9352.

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A study was conducted to monitor the bee activity in the colonies of diferente strengths in real time using an IoT-based device. The in-hive temperature and relative humidity were measured in the colonies of Apis cerana indica Fabricius of different strengths using the sensor-laden IoT device that was correlated with the movement of foragers into and out of the hive. A significantly higher movement of foragers was recorded at an in-hive temperature and relative humidity of 27.84 ºC and 61.47% at 5-6 p.m. with an observed activity of 9,638 bees/hive/hour in the strong colonies. In the weak colo

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Grigoryan, Leonty Rustemovich, Maxim Sergeevich Kovalenko, Anastasia Leontyevna Grigoryan, and Dmitry Yuryevich Paroshin. "Intellectual beehives monitoring system." Agrarian Scientific Journal, no. 10 (October 23, 2019): 59–65. http://dx.doi.org/10.28983/asj.y2019i10pp59-65.

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A system for remote monitoring of the parameters of bee hives is considered. The problem of remote monitoring at long distances, taking into account the changing weather factors, is very relevant. Among the variety of hardware for keeping bees, there is currently no unified monitoring system. The studies carried out allowed us to determine the optimal circuitry and software components of the construction of a monitoring system. The result of the development of a system with a local hive monitoring system and a remote data collection system using cloud technologies is presented in this work.&#x

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Catania, Pietro, and Mariangela Vallone. "Application of A Precision Apiculture System to Monitor Honey Daily Production." Sensors 20, no. 7 (2020): 2012. http://dx.doi.org/10.3390/s20072012.

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Precision beekeeping or precision apiculture is an apiary management strategy based on the monitoring of individual bee colonies to minimize resource consumption and maximize the productivity of bees. Bees play a fundamental role in ensuring pollination; they can also be considered as indicators of the state of pollution and are used as bio monitors. Beekeeping needs continuous monitoring of the animals and can benefit from advanced intelligent ambiance technologies. The aim of this study was the design of a precision apiculture system (PAS) platform for monitoring and controlling the followin

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Newton, Michael I., Luke Chamberlain, Adam McVeigh, and Martin Bencsik. "Winter Carbon Dioxide Measurement in Honeybee Hives." Applied Sciences 14, no. 4 (2024): 1679. http://dx.doi.org/10.3390/app14041679.

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Sensor technologies have sufficiently advanced to provide low-cost devices that can quantify carbon dioxide levels in honeybee hives with high temporal resolution and in a small enough package for hive deployment. Recent publications have shown that summer carbon dioxide levels vary throughout the day and night over ranges that typically exceed 5000 ppm. Such dramatic changes in a measurable parameter associated with bee physiology are likely to convey information about the colony health. In this work, we present data from four UK-based hives collected through the winter of 2022/2023, with a f

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Sanz, Milagros Casado, Rubén Prado-Jimeno, and Juan Francisco Fuentes-Pérez. "Comparative Study of Natural Fibres to Improve Insulation in Wooden Beehives Using Sensor Networks." Applied Sciences 14, no. 13 (2024): 5760. http://dx.doi.org/10.3390/app14135760.

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The beekeeping sector is increasingly focused on creating optimal and natural environments for honeybees to reduce dependence on external factors, especially given progressively hotter summers. Improving hive thermal conditions can enhance bee wellbeing and production. While pinewood hives are predominant, some have started using insulating materials like polystyrene. However, many synthetic materials, despite their excellent insulation properties, are incompatible with organic food production, requiring alternative solutions. This study compares the thermal insulation properties of various na

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Dragomir, Florin, Otilia Elena Dragomir, and Adrian Oprea. "Stand-Alone Power System for Monitoring and Control of the Temperature." Applied Mechanics and Materials 291-294 (February 2013): 2570–73. http://dx.doi.org/10.4028/www.scientific.net/amm.291-294.2570.

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The main objective of the article is to stimulate interest of the consumers for the green energy considering the environmental and the financial impact (in this case by increasing productivity) of this one. For these arguments, this article proposes a real application, with autonomy in the power supply, for control the temperature in the hive using energy from alternative sources (through a solar panel). The temperature regulation is controlled by a microcontroller. For setting the temperature of the hive some bees are used at the expense of honey production. If there would be no need to adjus

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Bencsik, Martin, Adam McVeigh, Costas Tsakonas, Tarun Kumar, Luke Chamberlain, and Michael I. Newton. "A Monitoring System for Carbon Dioxide in Honeybee Hives: An Indicator of Colony Health." Sensors 23, no. 7 (2023): 3588. http://dx.doi.org/10.3390/s23073588.

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Non-dispersive infra-red (NDIR) detectors have become the dominant method for measuring atmospheric CO2, which is thought to be an important gas for honeybee colony health. In this work we describe a microcontroller-based system used to collect data from Senserion SCD41 NDIR sensors placed in the crown boards and queen excluders of honeybee colonies. The same sensors also provide relative humidity and temperature data. Several months of data have been recorded from four different hives. The mass change measurements, from hive scales, when foragers leave the hive were compared with the data fro

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McAfee, Alison, David R. Tarpy, and Leonard J. Foster. "Western red cedar (Thuja plicata) beehives have no impact on honey bee (Apis mellifera) overwintering colony survival or detoxification enzyme expression." PLOS ONE 20, no. 4 (2025): e0318764. https://doi.org/10.1371/journal.pone.0318764.

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In North America, wooden honey bee hives are most often constructed from pine, but some companies also produce and sell boxes made of western red cedar (Thuja plicata) as a result of its local availability and desirable properties. However, there is debate within the beekeeping community about whether cedar is a safe hive material for bees, since resins within the wood are known to be insecticidal or insect deterrents. There is very little empirical evidence to support or refute these arguments. Here, we recorded health metrics of honey bee nucleus colonies hived in western red cedar and pine

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Daisley, Brendan A., Andrew P. Pitek, John A. Chmiel, et al. "Novel probiotic approach to counter Paenibacillus larvae infection in honey bees." ISME Journal 14, no. 2 (2019): 476–91. http://dx.doi.org/10.1038/s41396-019-0541-6.

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Abstract American foulbrood (AFB) is a highly virulent disease afflicting honey bees (Apis mellifera). The causative organism, Paenibacillus larvae, attacks honey bee brood and renders entire hives dysfunctional during active disease states, but more commonly resides in hives asymptomatically as inactive spores that elude even vigilant beekeepers. The mechanism of this pathogenic transition is not fully understood, and no cure exists for AFB. Here, we evaluated how hive supplementation with probiotic lactobacilli (delivered through a nutrient patty; BioPatty) affected colony resistance towards

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18

Ai, Hiroyuki, and Shinya Takahashi. "The Lifelog Monitoring System for Honeybees: RFID and Camera Recordings in an Observation Hive." Journal of Robotics and Mechatronics 33, no. 3 (2021): 457–65. http://dx.doi.org/10.20965/jrm.2021.p0457.

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A typical honeybee colony contains more than 15,000 individuals, each with its own task related to supporting the hive and maintaining the colony. In previous studies on honeybees, observing individual animals’ behaviors has been a difficult and time-consuming task to understand the relationship between in-hive communication and environmental changes outside the hive, therefore it is necessary in any attempt to develop applying a remote sensing technology. To allow researchers to pass much of this tracking work on to computers, we have developed the lifelog monitoring system for honeybees, whi

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ANDRIJEVIĆ, Nebojša, Dejana HERCEG, Srđan MARIČIĆ, Vladan RADIVOJEVIĆ, and Goran JOCIĆ. "CONCEPT SOLUTION OF AUTONOMOUS IOT SMART HIVE AND OPTIMIZATION OF ENERGY CONSUMPTION USING ARTIFICIAL INTELLIGENCE." Journal of process management and new technologies 12, no. 1-2 (2024): 41–48. http://dx.doi.org/10.5937/jpmnt12-49567.

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In this paper the authors present a conceptual solution for an autonomous smart beehive with a focus on energy efficiency; the hive's existence is based on artificial intelligence. The hive is equipped with an advanced system for monitoring the entry and exit of bees, as well as for collecting data on the weather inside and around the hive. Using an array of sensors controlled by Espressif ESP32 and Arduino Mega microcontroller boards, the hive continuously optimizes the operation of the ventilation system and other components, monitoring energy consumption and adapting to changing conditions.

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Ziegler, Cristiano, Renan Mitsuo Ueda, Tiago Sinigaglia, Felipe Kreimeier, and Adriano Mendonça Souza. "Correlation of Climatic Factors with the Weight of an Apis mellifera Beehive." Sustainability 14, no. 9 (2022): 5302. http://dx.doi.org/10.3390/su14095302.

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The bee Apis mellifera plays an important role in the balance of the ecosystem. New technologies are used for the evaluation of hives, and to determine the quality of the honey and the productivity of the hive. Climatic factors, management, flowering, and other factors affect the weight of a hive. The objective of this research was to explain the interrelationship between climatic variables and the weight of an Apis mellifera beehive using a vector autoregressive (VAR) model. The adjustment of a VAR model was carried out with seven climatic variables, and hive weight and its lags, by adjusting

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Muhammad Ammar Asyraf Che Ali, Bukhari Ilias, Norasmadi Abdul Rahim, et al. "Development of Artificial Stingless Bee Hive Monitoring using IoT System on Developing Colony." Journal of Advanced Research in Applied Sciences and Engineering Technology 33, no. 2 (2023): 254–68. http://dx.doi.org/10.37934/araset.33.2.254268.

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The trend of stingless bees’ farm in Malaysia has increased recently as it has been proven that its honey gives various benefits to human beings. This trend requires beekeepers to do more frequent inspections of beehives. However, the current practice of opening the cover to inspect the colony and honey will disrupt colony activity. According to a recent study, these stingless bees can only survive between 22 and 38 degrees Celsius, and harsh weather conditions might lead to the collapse of bee colonies. In order to ensure a consistent honey production, the IoT monitoring system will be implem

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Evsyukova, V. K., M. S. Savvinova, V. V. Sysolyatina, F. V. Nikolaeva, and A. Ya Fedorov. "Innovative method for optimizing the microclimate of the winter hive for bees in the conditions of the cryolithozone." E3S Web of Conferences 282 (2021): 07022. http://dx.doi.org/10.1051/e3sconf/202128207022.

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The article discusses the practical significance of the use of infrared scanning method for optimizing the microclimate of winter hives and monitoring bee colonies in extreme conditions of cryolithozone. When monitoring the microclimate by generally accepted zoohygienic methods, the devices record specific indicators of a particular parameter (temperature, humidity, air velocity, pressure, noise, light), while the reason for the deviation from the standard indicators for microclimate optimization is not always possible to find out. When using the infrared scanning method with the Irtis 2000SN

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Rafael Braga, Antonio, Juliana De Castro Rabelo, Arthur De Castro Callado, Atslands Rego da Rocha, Breno M. Freitas, and Danielo G. Gomes. "BeeNotified! A Notification System of Physical Quantities for Beehives Remote Monitoring." Revista de Informática Teórica e Aplicada 27, no. 3 (2020): 50–61. http://dx.doi.org/10.22456/2175-2745.90724.

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One of the ways to reduce inappropriate management of hives and monitor bee health is to send notifications/alerts about the data collected through sensors. This study presents BeeNotified!, a solution for sending notifications through Telegram, e-mail, and SMS. The notifications warn about the level of temperature, humidity, sound, carbon dioxide, oxygen, hive weight and delay in data gathering. From this data, researchers and beekeepers can be informed and make changes in the locations of the hives, avoiding catastrophes and possible diseases. The results obtained with the processing time in

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Terenzi, Alessandro, Stefania Cecchi, and Susanna Spinsante. "On the Importance of the Sound Emitted by Honey Bee Hives." Veterinary Sciences 7, no. 4 (2020): 168. http://dx.doi.org/10.3390/vetsci7040168.

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Recent years have seen a worsening in the decline of honey bees (Apis mellifera L.) colonies. This phenomenon has sparked a great amount of attention regarding the need for intense bee hive monitoring, in order to identify possible causes, and design corresponding countermeasures. Honey bees have a key role in pollination services of both cultivated and spontaneous flora, and the increase in bee mortality could lead to an ecological and economical damage. Despite many smart monitoring systems for honey bees and bee hives, relying on different sensors and measured quantities, have been proposed

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Sledevič, Tomyslav, Artūras Serackis, and Darius Plonis. "FPGA Implementation of a Convolutional Neural Network and Its Application for Pollen Detection upon Entrance to the Beehive." Agriculture 12, no. 11 (2022): 1849. http://dx.doi.org/10.3390/agriculture12111849.

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The condition of a bee colony can be predicted by monitoring bees upon hive entrance. The presence of pollen grains gives beekeepers significant information about the well-being of the bee colony in a non-invasive way. This paper presents a field-programmable-gate-array (FPGA)-based pollen detector from images obtained at the hive entrance. The image dataset was acquired at native entrance ramps from six different hives. To evaluate and demonstrate the performance of the system, various densities of convolutional neural networks (CNNs) were trained and tested to find those suitable for pollen

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Braga, Diogo, Ana Madureira, Fabio Scotti, Vincenzo Piuri, and Ajith Abraham. "An Intelligent Monitoring System for Assessing Bee Hive Health." IEEE Access 9 (2021): 89009–19. http://dx.doi.org/10.1109/access.2021.3089538.

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Takahashi, Shinya, Koji Hashimoto, Sakashi Maeda, Naoyuki Tsuruta, and Hiroyuki Ai. "Development of Behavior Monitoring System for Honeybees in Hive." Transactions of the Japanese Society for Artificial Intelligence 32, no. 4 (2017): B—GC2_1–11. http://dx.doi.org/10.1527/tjsai.b-gc2.

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Bowles, Tim, Kevin M. Trentino, Adam Lloyd, et al. "Health in a Virtual Environment (HIVE): A Novel Continuous Remote Monitoring Service for Inpatient Management." Healthcare 12, no. 13 (2024): 1265. http://dx.doi.org/10.3390/healthcare12131265.

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The aim of this study was to describe the implementation of a novel 50-bed continuous remote monitoring service for high-risk acute inpatients treated in non-critical wards, known as Health in a Virtual Environment (HIVE). We report the initial results, presenting the number and type of patients connected to the service, and assess key outcomes from this cohort. This was a prospective, observational study of characteristics and outcomes of patients connected to the HIVE continuous monitoring service at a major tertiary hospital and a smaller public hospital in Western Australia between January

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Kulyukin, Vladimir A., and Aleksey V. Kulyukin. "Accuracy vs. Energy: An Assessment of Bee Object Inference in Videos from On-Hive Video Loggers with YOLOv3, YOLOv4-Tiny, and YOLOv7-Tiny." Sensors 23, no. 15 (2023): 6791. http://dx.doi.org/10.3390/s23156791.

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A continuing trend in precision apiculture is to use computer vision methods to quantify characteristics of bee traffic in managed colonies at the hive’s entrance. Since traffic at the hive’s entrance is a contributing factor to the hive’s productivity and health, we assessed the potential of three open-source convolutional network models, YOLOv3, YOLOv4-tiny, and YOLOv7-tiny, to quantify omnidirectional traffic in videos from on-hive video loggers on regular, unmodified one- and two-super Langstroth hives and compared their accuracies, energy efficacies, and operational energy footprints. We

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Sledevič, Tomyslav, Artūras Serackis, Dalius Matuzevičius, Darius Plonis, and Gabriela Vdoviak. "Visual recognition of honeybee behavior patterns at the hive entrance." PLOS ONE 20, no. 2 (2025): e0318401. https://doi.org/10.1371/journal.pone.0318401.

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This study presents a novel method for automatically recognizing honeybee behavior patterns at the hive entrance, significantly contributing to beekeeping and hive management. Utilizing advanced YOLOv8 models for detection and segmentation, our approach analyzes various aspects of bee behavior, including location, direction, path trajectory, and movement speed within a designated area on the hive’s landing board. The system effectively detects multiple bee activities such as foraging, fanning, washboarding, and defense, achieving a mean detection accuracy of 98% and operating at speeds of up t

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O.O., Zhukov, та Horbenko V.I. "АДАПТИВНИЙ ПІДХІД ДО ВИЗНАЧЕННЯ СТАНУ ВУЛИКА ЗА ДОПОМОГОЮ НЕЙРОННИХ МЕРЕЖ ТА АНАЛІЗУ АУДІО". System technologies 4, № 153 (2024): 3–12. http://dx.doi.org/10.34185/1562-9945-4-153-2024-01.

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Problem statement. Monitoring the queen bee is crucial for the health and produc-tivity of a bee colony. The queen plays a vital role in reproduction and maintaining the colony's population. Utilizing neural networks, such as CNNs along with sound analysis, can be a valuable tool for monitoring queen bees and assessing their behavior and health within the hive. Purpose. Finding the best way to preprocess audio data and review it is an important task that, if performed well, will help to track the bee hive population and its health state in general. Related work. With the development of deep le

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Drummond, Francis A., and Aaron Kinyu Hoshide. "An Economic Cost/Benefit Tool to Assess Bee Pollinator Conservation, Pollination Strategies, and Sustainable Policies: A Lowbush Blueberry Case Study." Sustainability 16, no. 8 (2024): 3242. http://dx.doi.org/10.3390/su16083242.

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Lowbush blueberry is a mass-flowering plant species complex that grows in both unmanaged wild landscapes and managed agricultural fields in northeastern regions of both the USA and Canada. During pollination, more than 120 native bee species are associated with lowbush blueberry ecosystems in Maine, USA, in addition to three commercially managed bees. Over a 29-year period, we sampled 209 lowbush blueberry fields using quadrat and transect sampling, recording both native bee and honey bee densities, honey bee hive stocking density, and native bees as a proportion of total bees. These data were

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Atanasov, Atanas Z., Ivaylo S. Hristakov, Kaloyan E. Stoyanov, and Presiyan А. Zhelyazkov. "Monitoring honeybee (Apis mellifera) flight activity and within-day hive weight changes during rapeseed (Brassica napus) flowering." Technium: Romanian Journal of Applied Sciences and Technology 14 (October 9, 2023): 90–93. http://dx.doi.org/10.47577/technium.v14i.9685.

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Honeybee (Apis mellifera) flight activity and beehive changing weight during rapeseed (Brassica napus) flowering was evaluated. The research was carried out during the 2021 agricultural period in the northeastern region of Bulgaria, specifically in Yuper village. The experimental site is situated at 43°54'28.59" N, 26°23'49.02"E coordinates, with an elevation of 107 meters. Within the experiment, there were 130 bee colonies kept in Dadant-Blatt hives. The bees belong to the species known as (Apis mellifera macedonica). Throughout the research duration, the study focuses on tracking the quantit

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Kulyukin, Vladimir A., Daniel Coster, Aleksey V. Kulyukin, William Meikle, and Milagra Weiss. "Discrete Time Series Forecasting of Hive Weight, In-Hive Temperature, and Hive Entrance Traffic in Non-Invasive Monitoring of Managed Honey Bee Colonies: Part I." Sensors 24, no. 19 (2024): 6433. http://dx.doi.org/10.3390/s24196433.

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From June to October, 2022, we recorded the weight, the internal temperature, and the hive entrance video traffic of ten managed honey bee (Apis mellifera) colonies at a research apiary of the Carl Hayden Bee Research Center in Tucson, AZ, USA. The weight and temperature were recorded every five minutes around the clock. The 30 s videos were recorded every five minutes daily from 7:00 to 20:55. We curated the collected data into a dataset of 758,703 records (280,760–weight; 322,570–temperature; 155,373–video). A principal objective of Part I of our investigation was to use the curated dataset

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Hunor, Bartos, Zsolt Bodor, Ágnes Keresztesi, et al. "Advances in Beehive Monitoring Systems: Low-Cost Integrating Sensor Technology for Improved Apiculture Management." E3S Web of Conferences 589 (2024): 04001. http://dx.doi.org/10.1051/e3sconf/202458904001.

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The integration of monitoring systems in beekeeping has significant implications for the health and sustainability of honeybee colonies. These advanced systems, which include sensors for temperature, humidity, hive weight, and sound analysis, allow for real-time tracking of hive conditions, enabling beekeepers to respond promptly to potential threats such as disease, pests, or environmental stressors. Research shows that such technology can lead to improved colony management, reducing the incidence of colony collapse disorder (CCD) by facilitating early intervention. Additionally, continuous d

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Thompson, Aleesha, Drianca Naidoo, Eliza Becker, Kevin M. Trentino, Dharjinder Rooprai, and Kenneth Lee. "Remote Monitoring and Virtual Appointments for the Assessment and Management of Depression via the Co-HIVE Model of Care: A Qualitative Descriptive Study of Patient Experiences." Healthcare 12, no. 20 (2024): 2084. http://dx.doi.org/10.3390/healthcare12202084.

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Objective: This qualitative study sought to explore patient experiences with technologies used in the Community Health in a Virtual Environment (Co-HIVE) pilot trial. Technology is becoming increasingly prevalent in mental healthcare, and user acceptance is critical for successful adoption and therefore clinical impact. The Co-HIVE pilot trialled a model of care whereby community-dwelling patients with symptoms of depression utilised virtual appointments and remote monitoring for the assessment and management of their condition, as an adjunct to routine care. Methods: Using a qualitative descr

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Serri, Evelina, Giacomo Rossi, Alessio Angorini, Lucia Biagini, Livio Galosi, and Alessandra Roncarati. "Acquisitions and evaluation of beehive parameters through an electronic system." Acta IMEKO 13, no. 2 (2024): 1–5. http://dx.doi.org/10.21014/actaimeko.v13i2.1626.

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This study highlights the management of the hive superorganism, with the help of technology. Precision beekeeping is today a growing sector, used as apiary management strategy, based on the constant monitoring of families, minimization of consumption of resources and maximizing of productivity. Thanks to the scales and a probe placed inside each hive, we obtained data relating to winter 2021 and spring 2022, where we had flowerings 30 days in advance of the seasonality. The fluctuation of temperatures entailed the early start of laying of the queen with fresh brood to feed and heat, even when

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Panova-Vatcheva, Denitsa. "Classification of acoustic data with Transformer model." Proceedings. College Dobrich XVI (November 29, 2024): 165–86. https://doi.org/10.5281/zenodo.14247672.

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<em>Bees are essential to global ecosystems, particularly for pollinating crops, yet in recent years their populations have faced significant decline. One critical aspect of bee colony health is the ability to detect negative in-hive events such as a queen leaving the hive. Traditionally, beekeepers rely on manual inspections to assess hive conditions, a labor-intensive and time-consuming process. However, recent advances in machine learning offer new approaches to automating this task. Since 2016, there have been attempts to classify bee sounds using machine learning, employing the power of d

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Vorapatratorn, Surapol. "Enhancing monitoring of suspicious activities with AI-based and big data fusion." PeerJ Computer Science 10 (January 25, 2024): e1741. http://dx.doi.org/10.7717/peerj-cs.1741.

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This study provides an AI-based detection tool for the surveillance of suspicious activities using data fusion. The system leverages time, location, and specific data pertaining to individuals, objects, and vehicles associated with the agency. The study’s training data was obtained from Thailand’s military institution. The study focuses on comparing the efficiency between MySQL and Apache Hive for big data processing. According to the findings, MySQL is better suited for quick data retrieval and low storage capacity, while Hive demonstrates higher scalabilities for larger datasets. Furthermore

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Cecchi, Stefania, Susanna Spinsante, Alessandro Terenzi, and Simone Orcioni. "A Smart Sensor-Based Measurement System for Advanced Bee Hive Monitoring." Sensors 20, no. 9 (2020): 2726. http://dx.doi.org/10.3390/s20092726.

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The widespread decline of honey bee (Apis mellifera L.) colonies registered in recent years has raised great attention to the need of gathering deeper knowledge about this phenomenon, by observing the colonies’ activity to identify possible causes, and design corresponding countermeasures. In fact, honey bees have well-known positive effects on both the environment and human life, and their preservation becomes critical not only for ecological reasons, but also for the social and economic development of rural communities. Smart sensor systems are being developed for real-time and long-term mea

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Struye, M. H., H. J. Mortier, G. Arnold, C. Miniggio, and R. Borneck. "Microprocessor-controlled monitoring of honeybee flight activity at the hive entrance." Apidologie 25, no. 4 (1994): 384–95. http://dx.doi.org/10.1051/apido:19940405.

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Che Ali, M. A. A., B. Ilias, N. Abdul Rahim, S. A. Abdul Shukor, A. H. Adom, and M. A. H. Saad. "A Review on the Stingless Beehive Conditions and Parameters Monitoring using IoT and Machine Learning." Journal of Physics: Conference Series 2107, no. 1 (2021): 012040. http://dx.doi.org/10.1088/1742-6596/2107/1/012040.

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Abstract One of the stingless bee types named Heterotrigona Itama are widespread in the tropics and subtropics especially in Malaysia. Due to its excellent nutritional content, stingless bee honey has gained favour in recent years. According to some studies, stingless bee honey has been used to cure eye infections, open wounds, diabetes, hypertension, and a variety of other diseases. Additionally, this stingless bee is non-venomous and smaller in size than common bees. Nevertheless, beekeepers may encounter a number of obstacles that may result in colony failure and under-production. These pro

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Kulyukin, Vladimir, Anastasiia Tkachenko, Kristoffer Price, William Meikle, and Milagra Weiss. "Integration 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." Sensors 22, no. 13 (2022): 4824. http://dx.doi.org/10.3390/s22134824.

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The relationship between beehive weight and traffic is a fundamental open research problem for electronic beehive monitoring and digital apiculture, because weight and traffic affect many aspects of honeybee (Apis mellifera) colony dynamics. An investigation of this relationship was conducted with a nondisruptive two-sensor (scale and camera) system on the weight and video data collected on six Apis mellifera colonies in Langstroth hives at the USDA-ARS Carl Hayden Bee Research Center in Tucson, Arizona, USA, from 15 May to 15 August 2021. Three hives had positive and two hives had negative co

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Vijaykumar, Pashte Vrushali, and Patil Chidanand Shivshankar. "Monitoring on impact of insecticides on mortality of honey bees (Apis mellifera L.) in front of beehives." Journal of Applied and Natural Science 9, no. 2 (2017): 905–11. http://dx.doi.org/10.31018/jans.v9i2.1296.

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The present study investigated effect of pesticide usage and public awareness on honey bee mortality. The experiments were conducted at three different sites at Maharashtra, India with domesticated bee hives of Apis mellifera L. The maximum bee mortality during 51st week of 2012-13 (1559.10 bees/hive/week) clearly indicated towards the direct and indirect effect of insecticides in general at study site I (Case I). Similar experiments were repeated at other two different sites during 2013-14. Farmers (Case II and III) were aware of beekeeping and ill effects of pesticides. Farmers followed some

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Negi, Neha, Babita Bharti, Bharti Gautam, Jag Mohan, and Ridhima Arya. "Honeybee (Apis mellifera L.) colony loss linked to diseases: A mini review." Journal of Entomological Research 49, no. 2 (2025): 487–91. https://doi.org/10.5958/0974-4576.2025.00081.3.

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This review will focus on certain bee pests that have been shown to be implicated in colony losses in various parts of the world and are thus considered contemporary risks to honey bees and beekeeping. Bacterial, fungal, and viral illnesses pose serious dangers to honeybee populations, resulting in larval death and hive contamination. To combat these diseases, beekeepers use a variety of tactics, including Integrated Pest Management (IPM), genetic selection for resistance, antibiotic treatments, and hive upkeep. However, ongoing study, monitoring, and education are required for successful prev

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Calderón-Fallas, Rafael A., Luis A. Sánchez-Chaves, and Paola Hernández-Ching. "Strategies for detection and monitoring of the small hive beetle (Aethina tumida) in Africanized honeybee colonies in Costa Rica." Ciencias Veterinarias 42, no. 1 (2024): 1–8. http://dx.doi.org/10.15359/rcv.42-1.2.

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The small hive beetle (SHB), Aethina tumida, is a pest of honeybee (Apis mellifera) colonies. Endemic to sub-Saharan Africa, this pest has been reported in Africanized honeybee (AHB) colonies in North, Central, and South America. Specifically in Central America, it was first found in El Salvador in 2013, in Nicaragua in March 2014, and in Guatemala in August 2020. In Nicaragua, SHB was confirmed in AHB colonies in San Juan del Sur, Department of Rivas, approximately eight kilometers north of the Costa Rican border, which increased the risk of entry to this country. After SHB was confirmed in N

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Vdoviak, Gabriela, Tomyslav Sledevič, Artūras Serackis, Darius Plonis, Dalius Matuzevičius, and Vytautas Abromavičius. "Evaluation of Deep Learning Models for Insects Detection at the Hive Entrance for a Bee Behavior Recognition System." Agriculture 15, no. 10 (2025): 1019. https://doi.org/10.3390/agriculture15101019.

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Monitoring insect activity at hive entrances is essential for advancing precision beekeeping practices by enabling non-invasive, real-time assessment of the colony’s health and early detection of potential threats. This study evaluates deep learning models for detecting worker bees, pollen-bearing bees, drones, and wasps, comparing different YOLO-based architectures optimized for real-time inference on an RTX 4080 Super and Jetson AGX Orin. A new publicly available dataset with diverse environmental conditions was used for training and validation. Performance comparisons showed that modified Y

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Andrijević, Nebojša, Vlada Urošević, Branko Arsić, Dejana Herceg, and Branko Savić. "IoT Monitoring and Prediction Modeling of Honeybee Activity with Alarm." Electronics 11, no. 5 (2022): 783. http://dx.doi.org/10.3390/electronics11050783.

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A significant number of recent scientific papers have raised awareness of changes in the biological world of bees, problems with their extinction, and, as a consequence, their impact on humans and the environment. This work relies on precision beekeeping in apiculture and raises the scale of measurement and prediction results using the system we developed, which was designed to cover beehive ecosystem. It is equipped with an IoT modular base station that collects a wide range of parameters from sensors on the hive and a bee counter at the hive entrance. Data are sent to the cloud for storage,

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Rivera-Gomis, Jorge, Ales Gregorc, Andrea Maroni Ponti, Francesco Artese, Gertruida Zowitsky, and Giovanni Formato. "Monitoring of Small Hive Beetle (Aethina Tumida Murray) in Calabria (Italy) from 2014 to 2016: Practical Identification Methods." Journal of Apicultural Science 61, no. 2 (2017): 257–62. http://dx.doi.org/10.1515/jas-2017-0022.

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Abstract The Small Hive Beetle (SHB), Aethina tumida, is an invasive pest of honey bee colonies that causes significant damage to the beekeeping sector. SHB was detected in southern Italy (EU) in 2014 and despite adopted eradication measures, is still present there. After three years of observations of SHB in Calabria (2014-2016), we provide here some practical tips for improving control measures. A new time-saving colony examination method, including the use of an internal divider reduced the time needed for hive inspections by 31.86 % on average. Prioritizating the inspection of pollen and h

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Guruprasad, Shreyas M., and Benjamin Leiding. "BeeOpen—An Open Data Sharing Ecosystem for Apiculture." Agriculture 14, no. 3 (2024): 470. http://dx.doi.org/10.3390/agriculture14030470.

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The digital transformation of apiculture initially encompasses Internet of Things (IoT) systems, incorporating sensor technologies to capture and transmit bee-centric data. Subsequently, data analysis assumes a vital role by establishing correlations between the collected data and the biological conditions of beehives, often leveraging artificial intelligence (AI) approaches. The field of precision bee monitoring has witnessed a surge in the collection of large volumes of diverse data, ranging from the hive weight and temperature to health status, queen bee presence, pests, and overall hive ac

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