Long-Term and Extensive Monitoring for Bee Colonies Based on Internet of Things

Hong, Wei; Xu, Baohua; Chi, Xuepeng; Cui, Xuepei; Yan, Yinfa; Li, Tongyang

doi:10.1109/jiot.2020.2981681

Cited by 34 publications

(19 citation statements)

References 45 publications

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“…In [Kviesis et al, 2015], data is also transmitted from each hive to the central unit, using the 433 MHz radio frequency band. The systems' structure in [Gil-Lebrero et al, 2017] and [Hong et al, 2020] are also star networks using IEEE 802.15.4 and Wi-Fi protocols, respectively. Each beehive can establish a connection with a local database server to send the data, and each server transfers the information to a global cloud database.…”

Section: Network Architecture: Transmission Of Datamentioning

confidence: 99%

Toward an intelligent and efficient beehive: A survey of precision beekeeping systems and services

Hadjur

Ammar

Lefèvre

2022

Computers and Electronics in Agriculture

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Since the end of the 20 th century, bees are suffering from increasing stress factors, leading domesticated colonies to die or at least be less productive. Precision beekeeping (PB) is an emerging field of agriculture that aims at protecting bees, supporting beekeepers, and optimizing apiary production thanks to digital infrastructures. The digitalization of apiculture first involves systems from the field of the Internet of Things (IoT), with the development of sensors to collect and transfer bee-related data. Then, data analysis comes into play, providing models that connect the data with the biological states of beehives, sometimes thanks to artificial intelligence (AI).In this paper, we describe the recent advances in precision beekeeping as systems and as services. Different types of sensors, networks, and power sources in PB are covered. The collection and use of data are described, and the performances of PB services are assessed. We also estimate the sustainability of the proposed solutions, taking into account their scalability, efficiency, and economic cost, because beekeepers need deployable research results.

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Section: Network Architecture: Transmission Of Datamentioning

confidence: 99%

Toward an intelligent and efficient beehive: A survey of precision beekeeping systems and services

Hadjur

Ammar

Lefèvre

2022

Computers and Electronics in Agriculture

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“…In contrast, [76] described an innovative IoT-based system with multiple sensors, wireless data transfer, and selfsustaining power for long-term and robust bee colony monitoring. The suggested system can detect hive temperature and humidity, bee comb weight, colony sounds, and the number of bees entering the hive.…”

Section: F Internet Of Animals (Ioa)mentioning

confidence: 99%

Wireless Transmissions, Propagation and Channel Modelling for IoT Technologies: Applications and Challenges

et al. 2022

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The Internet of Things (IoT) has rapidly expanded for a wide range of applications towards a smart future world by connecting everything. As a result, new challenges emerge in meeting the requirements of IoT applications while retaining optimal performance. These challenges may include power consumption, quality of service, localization, security, and accurate modeling and characterization of wireless channel propagation. Among these challenges, the latter is critical to establishing point-to-point wireless communication between the sensors. Channel modeling also varies depending on the features of the surrounding area, which have a direct impact on the propagation of wireless signals. This presents a difficult task for network planners to efficiently design and deploy IoT applications without understanding the appropriate channel model to analyze coverage and predict optimal deployment configurations. As a result, this challenge has attracted considerable interest in academic and industrial communities in recent years. Therefore, this review presents an overview of current breakthroughs in wireless IoT technologies. The challenges in such applications are then briefly reviewed, focusing on wireless channel propagation modeling and characterization. Finally, the study gives a generalized form of commonly used channel models and a summary of recent channel modeling developments for wireless IoT technology. The outcome of this review is expected to provide a new understanding of the propagation behavior of present and future wireless IoT technologies, allowing network engineers to undertake correct planning and deployment in any environment. Additionally, the study may serve as a guideline for future channel modeling and characterization studies.

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“…The significance of constant monitoring [32][33][34][35][36][37][38] in terms of monitoring and measuring various parameters of influence within and immediately around the hive is shown in a large number of papers [39][40][41][42][43][44][45][46][47][48]. Most papers relied on the application of IoT technologies in designing these systems [19,[49][50][51][52][53][54][55][56][57][58].…”

Section: Related Workmentioning

confidence: 99%

IoT Monitoring and Prediction Modeling of Honeybee Activity with Alarm

et al. 2022

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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, analysis, and alarm generation. A time-series forecasting model capable of estimating the volume of bee exits and entrances per hour, which simulates dependence between environmental conditions and bee activity, was devised. The applied mathematical models based on recurrent neural networks exhibited high accuracy. A web application for monitoring and prediction displays parameters, measured values, and predictive and analytical alarms in real time. The predictive component utilizes artificial intelligence by applying advanced analytical methods to find correlation between sensor data and the behavioral patterns of bees, and to raise alarms should it detect deviations. The analytical component raises an alarm when it detects measured values that lie outside of the predetermined safety limits. Comparisons of the experimental data with the model showed that our model represents the observed processes well.

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Long-Term and Extensive Monitoring for Bee Colonies Based on Internet of Things

Cited by 34 publications

References 45 publications

Toward an intelligent and efficient beehive: A survey of precision beekeeping systems and services

Toward an intelligent and efficient beehive: A survey of precision beekeeping systems and services

Wireless Transmissions, Propagation and Channel Modelling for IoT Technologies: Applications and Challenges

IoT Monitoring and Prediction Modeling of Honeybee Activity with Alarm

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