iMHS: An IOT Embedded for Aedes Mosquito Home System

Wan Aezwani, Wan Abu Bakar and Mustafa, Man and Bazilah, A.Talip and Lim, Chee Hwa and Mohd Irfan Hakim, Md Noor (2019) iMHS: An IOT Embedded for Aedes Mosquito Home System. In: International Conference On Informatics, Computing And Applied Mathematics, 26-28 October 2019, TH Hotel Terengganu.

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The proposed of Intelligent Mosquitoes Home System (iMHS) encompasses of a complete Internet of Things (IoT) based solution. This IoT solution shall leverage the complete eco-system consisting of the devices (i.e.Sensors), the network connectivity, the cloud computing platform, the data analytics and a comprehensive web based system. The fundamental component of IoT embedded solution is the optimization of the device from the low-power wide-area network which is designed to enable battery-powered devices to operate with a long read range. This research is to enable a suitable method to detect to status level of fluid (Attractors), or also called as Insecticide Growth Regulator (IGR) that is equipped together in the Mosquito Home System (MH). The IGR status is plotted in three (3) different status i.e. low, medium or high by using the appropriate sensors components. Here, the battery capacity is crucial to allow for a well-received and consistent communication between sensors and signal receivers. Data sent or received is processed and inserted into a database on a public server (Cloud Server). In this research, we deployed an Arduino water level sensor that is controlled by NodeMCU (ESP8266) module as the microcontroller that is powered by AA Battery pack. Prior to implementation, the result of the battery sustainability in iMHS shows that it could last for 10 days under setting with 15 interval time, assuming under normal working condition.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Water Based Sensors, Mosquitoes Home Systems (MHS), Insect Growth Regulator, Aedes, Cloud Server, Internet of Thing (IOT)
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Informatics & Computing
Depositing User: Muhammad Akmal Azhar
Date Deposited: 29 Nov 2020 02:57
Last Modified: 29 Nov 2020 02:57

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