i-BeeHOME: An intelligent stingless honey beehives monitoring tool based on TOPSIS method by implementing LoRaWan – a preliminary study

Syadiah Nor, Wan Shamsuddin and Aznida Hayati, Zakaria@Mohamad and Zarina, Mohamad and Abdul Azim, Azlan (2020) i-BeeHOME: An intelligent stingless honey beehives monitoring tool based on TOPSIS method by implementing LoRaWan – a preliminary study. In: 6th International Conference on Computational Science and Technology, ICCST 2019, 29-30 Aug 2019, Kota Kinabalu, Malaysia.

[img] Text
FH03-FIK-20-36892.pdf
Restricted to Registered users only

Download (334kB)

Abstract

This paper describes a preliminary study on the development of an intelligent bee hives monitoring tool called iBeeHOME. This tool benefits LoRa and LoRaWan (LoRa in low power WANs) technology. This intelligent tool is capable to collect crucial information on bee colony hives in real-time despite of its remote location. The capability as a smart device of i-BeeHOME is further advanced when these information is then analyzed using one of the most wellknown multi-criteria decision making (MCDM) method, i.e. TOPSIS. Therefore, it is realized that the capability of iBeeHOME is three-fold, i.e. (1) collects and retrieves crucial information from beehives despite of its remote/rural location where WiFi/BLE based networks are ineffective by using LoRa technology, (2) analyzes information collected to predict the conformity of bee hives location for high quality of honey production by using TOPSIS method, and (3) tracking the geographical location of beehives in protecting it from being stolen/lost by using LoRaWAN technology. It is expected that the development of this tool will not only help the beekeepers to monitor honey beehives with minimum effort, but also implicitly allows further investigation on how to promote high quality of honey production by stingless bees.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Geographical locations, Honey production, Intelligent tools, Internet of Things (IOT), Minimum efforts, Monitoring tools, Multi-criteria decision making, TOPSIS method
Subjects: G Geography. Anthropology. Recreation > G Geography (General)
G Geography. Anthropology. Recreation > GE Environmental Sciences
T Technology > T Technology (General)
Divisions: Faculty of Informatics & Computing
Depositing User: Muhammad Akmal Azhar
Date Deposited: 25 Nov 2020 06:29
Last Modified: 25 Nov 2020 06:29
URI: http://eprints.unisza.edu.my/id/eprint/1958

Actions (login required)

View Item View Item