Murdoch University Research Repository

Welcome to the Murdoch University Research Repository

The Murdoch University Research Repository is an open access digital collection of research
created by Murdoch University staff, researchers and postgraduate students.

Learn more

Remote Data Monitoring to the Cloud for Apiary Measurement

Zeng, Zheng (2017) Remote Data Monitoring to the Cloud for Apiary Measurement. Honours thesis, Murdoch University.

[img]
Preview
PDF - Whole Thesis
Download (3MB) | Preview

Abstract

Apiary industry manages bees and makes the product from this insect. There are about 10,000 registered beekeepers in Australia that operate 600,000 hives. However, these beekeepers are mostly take various measurements from beehives manually. This provides significant workloads of the beekeepers as well as the maintenance fee. Since the rapid development of IoT (Internet of Things) technology, it is possible to take measurements remotely via the IoT microcontrollers. An owner of a bee farm approached the author via their contractor, for designing a low-cost solution for a remote monitoring system that allows the various apiary measurements. The design allows different parameters to be monitored automatically without human force, including the hive weight, the temperature, the level of rainfall, and the water level of the tank for hydrating bees. This thesis contained the design procedure for the remote apiary data monitoring system, investigating various sensors, development of the system’s software, laboratories for verifying various theories/assumptions; calculations for the system’s power consumption, etc. The simulation results for this system is demonstrated in this paper; the results indicate that the system is available to monitor data via the cloud, generating reports and sending the notification message to the end user by SMS/Email. Therefore, it can reduce the workload by preventing the beekeeper from frequently coming to the Beehive.

Item Type: Thesis (Honours)
Murdoch Affiliation(s): School of Engineering and Information Technology
Supervisor(s): Lee, Gareth
URI: http://researchrepository.murdoch.edu.au/id/eprint/40012
Item Control Page Item Control Page

Downloads

Downloads per month over past year