This master's thesis deals with the development and implementation of an intelligent beehive system designed to meet the challenges of modern precision beekeeping. The aim of the thesis was to develop a technological solution for the automated monitoring of key parameters in and around the hive, such as mass, temperature and acceleration, with an optimisation of energy efficiency for long-term autonomous operation.
As part of this work, two system versions were developed, offering different functionalities and price points: a platform for local measurements, based on the nRF52840 microcontroller, and a prototype platform with network communication, based on the nRF9160 microcontroller. Both platforms support the display of the collected data on an e-paper screen via a Bluetooth Low Energy connection, which enables direct local insight and is a rarity among commercially available solutions. In addition, both platforms enable temperature monitoring with wireless transmitters that work with Bluetooth Low Energy. This eliminates the need to install wired sensors in the hive and enables flexible support for different types of such sensors. The platform with network communication additionally enables data transmission to a remote server via a Long Term Evolution for Machine-Type Communications (LTE-M) mobile network. The software for both system versions was developed using the nRF Connect SDK development environment and a real-time operating system, with a focus on modularity and low power consumption.
A detailed analysis of power consumption was carried out for both platforms. The results show that the local measurement platform with a 6000 mAh battery can operate for about 521 days, while the platform with network communication can operate for about 480 days. Such long-term autonomous operation, exceeding one year, confirms the success of the implemented energy saving strategies, including the use of power saving mode (PSM) for LTE-M communication, and indicates the potential for virtually uninterrupted operation through the addition of a small solar cell.
The thesis successfully presents the comprehensive development of a smart beehive system, from hardware and software design to analysing energy efficiency. The developed solution offers a solid basis for further research and practical application in precision beekeeping with its modularity, the offer of two functionally different platforms, an innovative approach to data display and temperature measurement as well as the achieved energy efficiency. In this way, it can help to improve the health of bee colonies and gain a better understanding of factors such as colony collapse disorder.
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