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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Mohd Hanafi Ahmad Hijazi
Universiti Malaysia Sabah
Computer Science & IT Electrical & Electronics Engineering Engineering

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Journal : Bulletin of Electrical Engineering and Informatics

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Real-time mask detection and face recognition using eigenfaces and local binary pattern histogram for attendance system Mohd Suhairi Md Suhaimin; Mohd Hanafi Ahmad Hijazi; Chung Seng Kheau; Chin Kim On
Bulletin of Electrical Engineering and Informatics Vol 10, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i2.2859

Abstract

Face recognition is gaining popularity as one of the biometrics methods for an attendance system in an organization. Due to the pandemic, the common face recognition system needs to be modified to meet the current needs, whereby facemask detection is necessary. The main objective of this paper is to investigate and develop a real-time face recognition system for the attendance system based on the current scenarios. The proposed framework consists of face detection, mask detection, face recognition, and attendance report generation modules. The face and facemask detection is performed using the haar cascade classifier. Two techniques for face recognition were investigated, the eigenfaces and local binary pattern histogram. The initial experimental results and implementation at Kuching Community College show the effectiveness of the system. For future work, an approach that is able to perform masked face recognition will be investigated.
Automated water quality monitoring and regression-based forecasting system for aquaculture Toh Yin Wei; Emmanuel Steward Tindik; Ching Fui Fui; Haviluddin Haviluddin; Mohd Hanafi Ahmad Hijazi
Bulletin of Electrical Engineering and Informatics Vol 12, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i1.4464

Abstract

Water quality in fish tanks is essential to reduce fish mortality. Many factors affect the water quality, such as pH, dissolved oxygen, and temperature in fish tanks. Existing work has presented water quality monitoring systems for aquaculture, which are useful for automatic monitoring and notify any incidence of decline in water quality. It enables the fish farms to make interventions to reduce fish mortality. However, advanced monitoring through forecasting is necessary to ensure consistent optimum water quality. This paper presents a web-based water quality monitoring and forecasting system for aquaculture. First, a water quality forecasting model based on the long short-term memory is designed and developed. The model is evaluated and fine-tuned using the existing public dataset. Second, the prototype of the water quality monitoring and forecasting system is developed. An Arduino and Raspberry Pi based water quality data acquisition tool is built. A web-based application is then developed to present the monitoring data and forecasting. A notification module is included to send an alert message to the fish farmers when necessary. The system is tested and evaluated at the fish hatchery in Universiti Malaysia Sabah. The findings show that the proposed system provides better water quality management for fish farms.
Co-Authors Abdullah Bade Abdullah Bade Chin Kim On Ching Fui Fui Choon Beng Tan Chung Seng Kheau Emmanuel Steward Tindik Frans Coenen Frazier Kok Hairulnizam Mahdin Haviluddin Haviluddin Leong Qi Yang Mohammad Saffree Jeffree Mohammad Saffree Jeffree Mohd Saberi Mohamad Mohd Suhairi Md Suhaimin Mohd Suhairi Md Suhaimin Puteri Nor Ellyza Nohuddin Rayner Alfred Razali Yaakob Stefanus Kieu Tao Hwa Stefanus Kieu Tao Hwa Toh Yin Wei