X’MOS-IOT: IOT BASED MOSQUITO SPRAY DISPENSER SYSTEM
Article 1
DOI:
https://doi.org/10.46754/jmsi.2021.12.001Keywords:
Dengue, Mosquito, Spray dispenser, X’MOSAbstract
Dengue remains among the major causes of mortality worldwide. Many research and medical institutions are still investigating a treatment or vaccine and vector control that would be a key strategy for dengue fever prevention. We introduce Intelligent Mosquito Spray Dispenser system X’MOS-IOT, An innovative concept that includes IR4.0 for the cloud storage automation as well as data analytics and exchange across cyber-physical systems and cognitive computing. The X’MOS-IOT provides a solution for spray interval automation using sensor and battery optimizations with direct Wifi module technology. The device is equipped with X’MOS spray mini aerosol repellent, offering effective environmentally friendly Aedes mosquito control. This all-in-one system ensures a mosquito-free environment in your home. The implementation shows the X’MOS-IOT system is able to update the level of each X’MOS in X’MOSIOT
devices, reducing the cost of manual human checking for X’Mos refill.
References
P. R. Prasad, N. Narayan, S. Gayathri & S. Ganna. (2018). An efficient E-Health monitoring with smart dispensing system for remote areas. In 3rd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), pp. 2120-2124.
K. A. Kumar. (2020). An Internet of Thing based Agribot (IOT-Agribot) for precision agriculture and farm monitoring. Int. J. Educ. Manag. Eng, 10(4), 33-39.
J. Krishna, K. Lokesh, O. Silver, W. F. Malende & K. Anuradha. (2017). Internet of things application for implementation of smart agriculture system. In International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), IEEE, pp. 54-59.
R. Kumar & M. P. Rajasekaran. (2016). An IoT based patient monitoring system using raspberry Pi. In International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE’16), IEEE, pp. 1-4.
T. S. Gunawan, I. R. H. Yaldi, M. Kartiwi & H. Mansor. (2018). Performance evaluation of smart home system using internet of things. International Journal of Electrical and Computer Engineering, 8(1), 400.
D. D. Koo, J. J. Lee, A. Sebastiani & J. Kim. (2016). An Internet-of-Things (IoT) system development and implementation for bathroom safety enhancement. Procedia Engineering, 145, 396-403.
M. Man, W. A. W. A. Bakar & M. A. B. A. Razak. (2020). MUS-Tracker: An IoT based system in controlling and monitoring of beehives. International Journal, 8(6).
W. A. W. A. Bakar, M. Man, B. A. Talip, L. C. Hwa & M. I. H. M. Noor. (2019). iMHS: An IOT Embedded for Aedes Mosquito Home System.
M. Man, W. A. W. A. Bakar, L. C. Hwa, W. N. J. W. M. Yusoff, M. Affendi & M. I. H. M. Noor. (2020). Dengue innovation: A sustainability approach for preventing and controlling of dengue diseases outbreaks via IoT technology. In IOP Conference Series: Materials Science and Engineering, 769(1), 012012. IOP Publishing.
M. Man, W. A. B. W. A. Bakar, M. I. H. B. M. Noor. (2019). ITDS: An intelligent tissue dispenser system. International Journal of Recent Technology and Engineering, 8(3), 2613-2619.
S. Himanshu, V. Pallagani, V. Khandelwal & U. Venkanna. (2018). IoT based smart home automation system using sensor node. In 4th International Conference on Recent Advances in Information Technology (RAIT), IEEE, pp. 1-5.
N. Ayadi, M. Turki, R. Ghribi & N. Derbel. (2017). Identification and development of a real-time motion control for a mobile robot’s DC gear motor. International Journal of Computer Applications in Technology, 55(1), 61-69.
Z. Wang, S. Ambrogio, S. Balatti & D. (2015). Ielmini. A 2-transistor/1-resistor artificial synapse capable of communication and stochastic learning in neuromorphic systems. Frontiers in Neuroscience, 8, 438.
S. Q. Liu, S. C. Li, K. L. Huang & B. L. Gong. (2007). Lithium-ion battery cathode material Li~ 3V~ 2 (PO~ 4)~ 3 prepared by sol-gel procedure. Chinese Journal of Power Sources, 31(2), 123.
M. K. Yusof & M. Man. (2017). Efficiency of JSON for data retrieval in big data. Indonesian Journal of Electrical Engineering and Computer Science, 7(1), 250-262.
M. Man, W. A. W. A. Bakar, Z. Abdullah, M. A. Jalil & T. Herawan. (2016). Mining association rules: A case study on benchmark dense data. Indonesian Journal of Electrical Engineering and Computer Science, 3(3), 546-553
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
