Photoplethysmogram based biometric identification for twins incorporating gender variability

This study focuses on a Photoplethysmogram (PPG) based biometric identification for twins incorporating gender variability. To the best of our knowledge, little has been said pertaining to this research which identifies twins using PPG signals. PPG device has been widely used due to its advantages such as non-invasive, low cost and small in size which makes it a convenient analytical tool. PPG signals has the capability to ensure the person to be present during the acquisition process which suggest that PPG can provide liveness detection suitable for a biometric system which is not available in other biometric modalities such as fingerprint. A total of four couple of twins which consists of four female and four male subjects in age range between twenty two to thirty years old were used to assess the feasibility of the proposed system. The acquired PPG signals were then processed to remove unwanted noise using low pass filter. After that, multiple cycles of PPG waveforms were extracted and later classified using Radial Basis Function (RBF) and Bayes Network (BN) to categorize the subjects using the discriminant features to calculate and analyze the performance of this system. The outcome also provides a complimentary mechanism to detect twins besides using the current existing methods

Lebah Kelulut Urban ‘Maniskan’ Kehidupan Komuniti Taman Melewar

Hampir dua tahun, pandemik COVID-19 yang melanda dunia telah memberikan pelbagai kesan langsung kepada rakyat di Malaysia. Antara implikasi besar yang dibawa oleh wabak COVID-19 ialah kemerosotan ekonomi yang mengganggu proses kelangsungan hidup. Ramai yang kehilangan pekerjaan dan punca pendapatan ketika tempoh yang sukar ini. Bagi penduduk di bandar, mereka lebih terkesan lagi kerana kos hidup di bandar yang tinggi. Menurut kajian Institut Penyelidikan Ekonomi Malaysia (MIER), lebih daripada dua pertiga rakyat Malaysia tinggal di bandar. Tambahan pula, berdasarkan kajian Jabatan Perangkaan Malaysia, kadar kemiskinan penduduk telah meningkat daripada 5.6 peratus pada 2019 kepada 8.4 peratus pada tahun lepas akibat pandemik COVID-19. Kos sara hidup yang tinggi dan kemiskinan bandar semakin menekan rakyat khususnya yang berpendapatan rendah dan sederhana. Menyedari cabaran kehidupan masyarakat yang semakin menghimpit, Universiti Islam Antarabangsa Malaysia (UIAM) dan rakan industri, My Iqra PLT mengambil inisiatif untuk membantu dengan melaksanakan program penternakan kelulut bersama Pertubuhan Khairat Kematian Taman Melewar, Kuala Lumpur melalui Program Pemindahan Ilmu Skim Geran Matlamat Pembangunan Lestari (SDG)

Preliminary study on designing and development of a synthesis gas analyser in the process of gasification

Malaysia has a great development in biomass industry. The industry needs to use synthesis gas analyser for monitoring gas composition in the process of gasification. Since there is no local production of such analyser, it is commonly imported from oversea for a very high price. Furthermore, analysers in the market are not easily customized which ends up with the industry having to buy separate analysers to measure several types of gas. Therefore, this study focuses on developing a portable synthesis gas analyser for biomass gasification that suits the local industry’s application which is low cost, at the same time, maintaining its accuracy and reliability. The analyser is integrated with a monitoring system using the Internet of Things (IoT) concept. The developed analyser uses Raspberry Pi microcomputer as the core element in its electronic design along with several other necessary hardware components. The analyser is capable of measuring methane (CH4), carbon monoxide (CO), hydrogen (H2), and carbon dioxide (CO2). It also includes a web server for displaying its measurement in a local network and the internet for monitoring purpose. Selected sensors used in the analyser shows positive response toward respective gas in a sensor validation experiment. Thus, the sensors can be used for further development of the analyser. Case building, addition of the web server’s features, and accuracy and reliability experiment will be conducted in future development of the analyser. Therefore, this study shows the possibility of developing a portable synthesis gas analyser. Furthermore, the analyser may offer a cheaper yet reliable alternative for gasification process monitoring to the local biomass industry in the future

Water quality monitoring system for aquaponics and fishpond using Wireless Sensor Network

The higher the human population, the higher the demand for food supply from the agriculture sector. However, healthy and environment-friendly plant-based food production is very time-consuming. Water quality checking by the human resource is no longer efficient in the presence of technology today. Thus, a water quality monitoring system for aquaponics and fishpond is proposed in this study adapting the use of Wireless Sensor Network (WSN), Message Queuing Telemetry Transport (MQTT) protocol, and Wi-Fi signal. The completed system was successfully tested and implemented at the Malaysian Institute of Sustainable Agriculture (MISA). The devices send measurements to a base station which hosted a web server which can be viewed both locally and via the Internet. Results show the system is practical in use as it is both stable and reliable with 5 seconds maximum measurement refresh rate on its dashboard. Thus, reduces human dependency for monitoring the water quality of both the aquaponics and fishpond. Human resource can then be allocated to more crucial roles. Room for improvement includes complete use of solar renewable energy, adding Wi-Fi extender for large scale implementation, and equipping the Raspberry Pi with a cooling fan. This is the step forward to modernising agriculture

Driver drowsiness detection using different classification algorithms

Capability of electrocardiogram (ECG) signal in contributing to the daily application keeps developing days by days. As technology advances, ECG marks the possibility as a potential mechanism towards the drowsiness detection system. Driver drowsiness is a state between sleeping and being awake due to body fatigue while driving. This condition has become a common issue that leads to road accidents and death. It is proven in previous studies that biological signals are closely related to a person's reaction. Electrocardiogram (ECG) is an electrical indicator of the heart, provides such criteria as it reflects the heart activity that can detect changes in human response which relates to our emotions and reactions. Thus, this study proposed a non-intrusive detector to detect driver drowsiness by using the ECG. This study obtained ECG data from the ULg multimodality drowsiness database to simulate the different stages of sleep, which are PVT1 as early sleep while PVT2 as deep sleep. The signals are later processed in MATLAB using Savitzky-Golay filter to remove artifacts in the signal. Then, QRS complexes are extracted from the acquired ECG signal. The process was followed by classifying the ECG signal using Machine Learning (ML) tools. The classification techniques that include Multilayer Perceptron (MLP), k-Nearest Neighbour (IBk) and Bayes Network (BN) algorithms proved to support the argument made in both PVT1 and PVT2 to measure the accuracy of the data acquired. As a result, PVT1 and PVT2 are correctly classified as the result shown with higher percentage accuracy on each PVTs. Hence, this paper present and prove the reliability of ECG signal for drowsiness detection in classifying high accuracy ECG data using different classification algorithms

Photoplethysmogram Based Biometric Identification for Twins Incorporating Gender Variability

This study focuses on a Photoplethysmogram (PPG) based biometric identification for twins incorporating gender variability. To the best of our knowledge, little has been said pertaining to this research which identifies twins using PPG signals. PPG device has been widely used due to its advantages such as non-invasive, low cost and small in size which makes it a convenient analytical tool. PPG signals has the capability to ensure the person to be present during the acquisition process which suggest that PPG can provide liveness detection suitable for a biometric system which is not available in other biometric modalities such as fingerprint. A total of four couple of twins which consists of four female and four male subjects in age range between twenty two to thirty years old were used to assess the feasibility of the proposed system. The acquired PPG signals were then processed to remove unwanted noise using low pass filter. After that, multiple cycles of PPG waveforms were extracted and later classified using Radial Basis Function (RBF) and Bayes Network (BN) to categorize the subjects using the discriminant features to calculate and analyze the performance of this system. The outcome also provides a complimentary mechanism to detect twins besides using the current existing methods

Heart abnormality detection technique using PPG signal

Cardiovascular disease (CVD) is the major cause of death in the world. Previous works have been performed to overcome this issue, however, a simple yet effective detection technique scarce. Thus, in this study, photoplethysmogram (PPG) signal which are easily acquired from the fingertip, low cost, and requires low power consumption, is used. These biosignals were obtained from MIMIC II Waveform Database, Version 3 Part 1 with sampling frequency of 200 Hz with the duration of 10 seconds each. The feature of the PPG signals were then extracted using MATLAB and the peak-to-peak intervals (PPI) of PPG signals were calculated and evaluated to differentiate between the normal and abnormal PPG signals. Based on the experimentation results, PPI values between the systolic peaks of abnormal PPG signals are larger than the normal PPG signals. The significant difference between the PPI values of normal and abnormal signals indicates the reliability of the proposed method as a technique to detect heart abnormalities