Abstract
The bee honey industry is a very lucrative industry and in just 2015, Malaysia imported RM58 millions ringgit worth of honey products. Although stingless bee keeping seemingly simple, there are a few problems that could affect the failure of success. Stingless bee industry in Malaysia are facing major challenges especially in the respect of the queen, quality inconsistency, low honey production and high price. This is because most of the stingless beehive farm in Malaysia do not have a proper system to monitor and control the environmental parameter of beehive. Moreover, because of the medicinal value of the stingless beehive, there are also a few cases of stolen beehive in Malaysia. Therefore, to prevent these issues, a project named Smart Stingless Beehive Monitoring System (SSBMS) is being developed to monitor and control the environmental parameter of beehive automatically. Sensors are installed at stingless beehive to monitor and control the environmental parameter of stingless beehive such as temperature, humidity, water level as well as the geographical location of beehive through Internet of Things (IoT) platform. The feedback system such as DC fan motor and diaphragm pump have been implemented to ensure the temperature of stingless beehive and water supply for stingless bee can be maintained below 30 °C and in an adequate level respectively. In conclusion, SSBMS is able to help reducing manpower in monitoring the environmental parameter of stingless beehive, gives feedback to maintain the internal beehive temperature and water supply level automatically or based on beekeepers’ desires and tracks the geographical location of the stingless beehive through Global Positioning System (GPS).
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Acknowledgements
The authors would like to thank the Registrar Office and Universiti Tun Hussein Onn Malaysia (UTHM) for providing resources and financial support for this research.
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Edmund, C., Ab. Rahman, M. (2021). Smart Stingless Beehive Monitoring System. In: Alfred, R., Iida, H., Haviluddin, H., Anthony, P. (eds) Computational Science and Technology. Lecture Notes in Electrical Engineering, vol 724. Springer, Singapore. https://doi.org/10.1007/978-981-33-4069-5_44
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DOI: https://doi.org/10.1007/978-981-33-4069-5_44
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