An IoT-Based Ovitrap System Applied for Aedes Mosquito Surveillance
Ismaliza Isa1, Ahmad Razali Ishak2, Nazri Che Dom3, Zulkifli Mohamed4, M. Azhan Anuar5
1Ismaliza Isa, Centre of Environmental Health and Safety, Faculty of Health Sciences, University Technology MARA, Puncak Alam, Selangor, Malaysia.
2Ahmad Razali Ishak, Centre of Environmental Health and Safety, Faculty of Health Sciences, University Technology MARA, Puncak Alam, Selangor, Malaysia.
3Nazri Che Dom, Centre of Environmental Health and Safety, Faculty of Health Sciences, University Technology MARA, Puncak Alam, Selangor, Malaysia.
4Zulkifli Mohamed, Faculty of Mechanical Engineering, Universiti Technologi MARA, UiTM Shah Alam, Selangor, Malaysia.
5Muhamad Azhan Anuar*, Faculty of Mechanical Engineering, Universiti Technologi MARA, UiTM Shah Alam, Selangor, Malaysia.
Manuscript received on September 23, 2019. | Revised Manuscript received on October 15, 2019. | Manuscript published on October 30, 2019. | PP: 5752-5758 | Volume-9 Issue-1, October 2019 | Retrieval Number: A3058109119/2019©BEIESP | DOI: 10.35940/ijeat.A3058.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Since the number of dengue fever cases has become the endemic disease in Malaysia, it is urgently need for rapid and efficient calculation of mosquito populations particularly for early detection and control measures. An ovitrap surveillance is used to determine the density of Aedes mosquito and it is one of the implemented method for vector control application. In this study, the prototype of an IoT-based ovitrap system was developed to automatically and simultaneously detect the Aedes mosquitoes using Node MCU as the main IoT platform. The existing sticky ovitrap was modified to integrate the selected IoT components and to ensure its functionality for automatic detection. There are two phases were conducted in this study, with phase 1 evaluating the right IoT components to be selected and applied for automatic detection. Integrating the selected IoT components and modification of present ovitrap was carried out in phase 2 and the final revised design was considered. SWOT analysis and Pugh chart analysis also known as decision matrix method were used to select the best IoT components and final ovitrap design. It has been observed that the prototype D was the best design and be able to detect the adult mosquitoes. The lessons learned in the development of the IoT-based ovitrap were discussed in order to be employed for Aedes mosquitoes surveillance in the future.
Keywords: Aedes mosquito, IoT, Node MCU, Ovitrap.