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All Journal Indonesian Journal of Electrical Engineering and Computer Science
T. R. Razak
Universiti Teknologi MARA

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A review of IoT-based smart waste level monitoring system for smart cities A. A. I. Shah; S. S. M. Fauzi; R. A. J. M. Gining; T. R. Razak; M. N. F. Jamaluddin; R. Maskat
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 1: January 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i1.pp450-456

Abstract

Smart cities are covering the population that are seeking the best lifestyle and fulfilling their needs. Through smart cities, necessary modern facilities using ICT emerging technologies such as the internet of things (IoT) had been installed to ensure the sustainability of the city. In the perspective of waste management, several different IoT-based solutions also had been proposed as an alternative to monitor and to ensure the health of communities. This paper reviews existing IoT-based solutions in smart cites’ waste level management system to bring together the state-of-the-art. We performed reviews on 16 research articles from the past 5 years in the literature to provide a comprehensive review of different works on IoT-based solutions related to the smart waste level monitoring system, possible solutions and technologies used. The results obtained shows that existing solutions were similar in the platform used to integrate with the IoT technologies but had some differences in term of the used of sensors and communication technologies. The study also shows that many of the prior studies used Arduino Uno. Results from this study will assist the researcher, focusing on expanding further the used of different technologies or improved the existing system.
Harumanis mango leaf disease recognition system using image processing technique R. A. JM. Gining; S. S. M. Fauzi; N. M . Yusoff; T. R. Razak; M. H. Ismail; N. A. Zaki; F. Abdullah
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 1: July 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i1.pp378-386

Abstract

Current Harumanismango farming technique in Malaysia still mostlydepends on the farmers' own expertise to monitor the crops from the attack ofpests and insects. This approach is susceptible to human errors, and thosewho do not possess this skill may not be able to detect the disease at the righttime. As leaf diseases seriously affect the crop's growth and the quality of theyield, this study aims to develop a recognition system that detects thepresence of disease in the mango leaf using image processing technique.First, the image is acquired through a smartphone camera; once it has beenpre-processed, it is then segmented in which the RGB image is converted toan HSI image, then the features are extracted. Lastly, the classification ofdisease is done to determine thetype of leaf disease. The proposed systemeffectively detects and classify the disease with an accuracy of 68.89%. Thefindings of this project will contribute to farmers and society's benefit, andresearchers can use the approach to address similar issues in future works.
Co-Authors A. A. I. Shah F. Abdullah M. H. Ismail M. N. F. Jamaluddin N. A. Zaki N. M . Yusoff R. A. J. M. Gining R. A. JM. Gining R. Maskat S. S. M. Fauzi