Electrical energy is often wasted through human negligence when people do not switch off electrical appliances such as lighting after leaving a place. Such a scenario often happens in a classroom when the last person leaves the class and forgets to switch off the electrical appliances. Such wastage may not be able to be afforded by schools that are limited financially. Therefore, this research proposed a simple and cost-effective system that can analyze whether there is or is not a human presence in the classroom by applying a counter to count the total number of people entering and leaving the classroom based on the sensing signals of a set of dual PIR sensors only and then correlating this to automatically turn on or off the electrical appliances mentioned. The total number of people identified in the classroom is also displayed on an LCD screen. A TRIZ approach is used to support the ideation of the system. The system can switch on several electrical output loads simultaneously when the presence of people is detected and switch them off when there are no people in the classroom. The proposed system can be expanded to be used in homes, offices, and buildings to prevent the high cost of electricity consumption caused by the negligence of people. This enables smarter control of electricity consumption.
Cardiovascular disease continues to be one of the most prevalent medical conditions in modern society, especially among elderly citizens. As the leading cause of deaths worldwide, further improvements to the early detection and prevention of these cardiovascular diseases is of the utmost importance for reducing the death toll. In particular, the remote and continuous monitoring of vital signs such as electrocardiograms are critical for improving the detection rates and speed of abnormalities while improving accessibility for elderly individuals. In this paper, we consider the design and deployment characteristics of a remote patient monitoring system for arrhythmia detection in elderly individuals. Thus, we developed a scalable system architecture to support remote streaming of ECG signals at near real-time. Additionally, a two-phase classification scheme is proposed to improve the performance of existing ECG classification algorithms. A prototype of the system was deployed at the Sarawak General Hospital, remotely collecting data from 27 unique patients. Evaluations indicate that the two-phase classification scheme improves algorithm performance when applied to the MIT-BIH Arrhythmia Database and the remotely collected single-lead ECG recordings.
The ability to detect users' emotions for the purpose of emotion engineering is currently one of the main endeavors of machine learning in affective computing. Among the more common approaches to emotion detection are methods that rely on electroencephalography (EEG), facial image processing and speech inflections. Although eye-tracking is fast in becoming one of the most commonly used sensor modalities in affective computing, it is still a relatively new approach for emotion detection, especially when it is used exclusively. In this survey paper, we present a review on emotion recognition using eye-tracking technology, including a brief introductory background on emotion modeling, eye-tracking devices and approaches, emotion stimulation methods, the emotional-relevant features extractable from eye-tracking data, and most importantly, a categorical summary and taxonomy of the current literature which relates to emotion recognition using eye-tracking. This review concludes with a discussion on the current open research problems and prospective future research directions that will be beneficial for expanding the body of knowledge in emotion detection using eye-tracking as the primary sensor modality.
Gallium nitride (GaN), widely known as a wide bandgap semiconductor material, has been mostly employed in high power devices, light emitting diodes (LED), and optoelectronic applications. However, it could be exploited differently due to its piezoelectric properties, such as its higher SAW velocity and strong electromechanical coupling. In this study, we investigated the affect of the presence of a guiding layer made from titanium/gold on the surface acoustic wave propagation of the GaN/sapphire substrate. By fixing the minimum thickness of the guiding layer at 200 nm, we could observe a slight frequency shift compared to the sample without a guiding layer, with the presence of different types of surface mode waves (Rayleigh and Sezawa). This thin guiding layer could be efficient in transforming the propagation modes, acting as a sensing layer for the binding of biomolecules to the gold layer, and influencing the output signal in terms of frequency or velocity. The proposed GaN/sapphire device integrated with a guiding layer could possibly be used as a biosensor and in wireless telecommunication applications.
As the main exporter in the oil palm industry, the need to improve the quality of palm oil has become the main interest among all the palm oil millers in Malaysia. To produce good quality palm oil, it is important for the miller to harvest a good oil palm Fresh Fruit Bunch (FFB). Conventionally, the main reference used by Malaysian harvesters is the manual grading standard published by the Malaysian Palm Oil Board (MPOB). A good oil palm FFB consists of all matured fruitlets, aged between 18 to 21 weeks of antheses (WAA). To expedite the harvesting process, it is crucial to implement an automated detection system for determining the maturity of the oil palm FFB. Various automated detection methods have been proposed by researchers in the field to replace the conventional method. In our preliminary study, a novel oil palm fruit sensor to detect the maturity of oil palm fruit bunch was proposed. The design of the proposed air coil sensor based on the inductive sensor was further investigated mainly in the context of the effect of coil diameter to improve its sensitivity. In this paper, the sensitivity of the inductive sensor was further examined with a dual flat-type shape of air coil. The dual air coils were tested on fifteen samples of fruitlet from two categories, namely ripe and unripe. Samples were tested within 20 Hz to 10 MHz while evaluations on both peaks were done separately before the gap between peaks was analyzed. A comparative analysis was conducted to investigate the improvement in sensitivity of the induction-based oil palm fruit sensor as compared to previous works. Results from the comparative study proved that the inductive sensor using a dual flat-type shape air coil has improved by up to 167%. This provides an indication in the improvement in the coil sensitivity of the palm oil fruit sensor based on the induction concept.
Among palm oil millers, the ripeness of oil palm Fresh Fruit Bunch (FFB) is determined through visual inspection. To increase the productivity of the millers, many researchers have proposed with a new detection method to replace the conventional one. The sensitivity of such a sensor plays a crucial role in determining the effectiveness of the method. In our preliminary study a novel oil palm fruit sensor to detect the maturity of oil palm fruit bunches is proposed. The design of the proposed air coil sensor based on an inductive sensor is further investigated to improve its sensitivity. This paper investigates the results pertaining to the effects of the air coil structure of an oil palm fruit sensor, taking consideration of the used copper wire diameter ranging from 0.10 mm to 0.18 mm with 60 turns. The flat-type shape of air coil was used on twenty samples of fruitlets from two categories, namely ripe and unripe. Samples are tested with frequencies ranging from 20 Hz to 120 MHz. The sensitivity of the sensor between air to fruitlet samples increases as the coil diameter increases. As for the sensitivity differences between ripe and unripe samples, the 5 mm air coil length with the 0.12 mm coil diameter provides the highest percentage difference between samples and it is amongst the highest deviation value between samples. The result from this study is important to improve the sensitivity of the inductive oil palm fruit sensor mainly with regards to the design of the air coil structure. The efficiency of the sensor to determine the maturity of the oil palm FFB and the ripening process of the fruitlet could further be enhanced.
From the Malaysian harvester's perspective, the determination of the ripeness of the oil palm (FFB) is a critical factor to maximize palm oil production. A preliminary study of a novel oil palm fruit sensor to detect the maturity of oil palm fruit bunches is presented. To optimize the functionality of the sensor, the frequency characteristics of air coils of various diameters are investigated to determine their inductance and resonant characteristics. Sixteen samples from two categories, namely ripe oil palm fruitlets and unripe oil palm fruitlets, are tested from 100 Hz up to 100 MHz frequency. The results showed the inductance and resonant characteristics of the air coil sensors display significant changes among the samples of each category. The investigations on the frequency characteristics of the sensor air coils are studied to observe the effect of variations in the coil diameter. The effect of coil diameter yields a significant 0.02643 MHz difference between unripe samples to air and 0.01084 MHz for ripe samples to air. The designed sensor exhibits significant potential in determining the maturity of oil palm fruits.
The domain of underwater wireless sensor networks (UWSNs) had received a lot of attention recently due to its significant advanced capabilities in the ocean surveillance, marine monitoring and application deployment for detecting underwater targets. However, the literature have not compiled the state-of-the-art along its direction to discover the recent advancements which were fuelled by the underwater sensor technologies. Hence, this paper offers the newest analysis on the available evidences by reviewing studies in the past five years on various aspects that support network activities and applications in UWSN environments. This work was motivated by the need for robust and flexible solutions that can satisfy the requirements for the rapid development of the underwater wireless sensor networks. This paper identifies the key requirements for achieving essential services as well as common platforms for UWSN. It also contributes a taxonomy of the critical elements in UWSNs by devising a classification on architectural elements, communications, routing protocol and standards, security, and applications of UWSNs. Finally, the major challenges that remain open are presented as a guide for future research directions.
Piezoelectric energy harvesting systems have been drawing the attention of the research community over recent years due to their potential for recharging/replacing batteries embedded in low-power-consuming smart electronic devices and wireless sensor networks. However, conventional linear piezoelectric energy harvesters (PEH) are often not a viable solution in such advanced practices, as they suffer from a narrow operating bandwidth, having a single resonance peak present in the frequency spectrum and very low voltage generation, which limits their ability to function as a standalone energy harvester. Generally, the most common PEH is the conventional cantilever beam harvester (CBH) attached with a piezoelectric patch and a proof mass. This study investigated a novel multimode harvester design named the arc-shaped branch beam harvester (ASBBH), which combined the concepts of the curved beam and branch beam to improve the energy-harvesting capability of PEH in ultra-low-frequency applications, in particular, human motion. The key objectives of the study were to broaden the operating bandwidth and enhance the harvester's effectiveness in terms of voltage and power generation. The ASBBH was first studied using the finite element method (FEM) to understand the operating bandwidth of the harvester. Then, the ASBBH was experimentally assessed using a mechanical shaker and real-life human motion as excitation sources. It was found that ASBBH achieved six natural frequencies within the ultra-low frequency range (<10 Hz), in comparison with only one natural frequency achieved by CBH within the same frequency range. The proposed design significantly broadened the operating bandwidth, favouring ultra-low-frequency-based human motion applications. In addition, the proposed harvester achieved an average output power of 427 μW at its first resonance frequency under 0.5 g acceleration. The overall results of the study demonstrated that the ASBBH design can achieve a broader operating bandwidth and significantly higher effectiveness, in comparison with CBH.
This paper presents the design of a non-intrusive system to measure ultra-low water content in crude oil. The system is based on a capacitance to phase angle conversion method. Water content is measured with a capacitance sensor comprising two semi-cylindrical electrodes mounted on the outer side of a glass tube. The presence of water induces a capacitance change that in turn converts into a phase angle, with respect to a main oscillator. A differential sensing technique is adopted not only to ensure high immunity against temperature variation and background noise, but also to eliminate phase jitter and amplitude variation of the main oscillator that could destabilize the output. The complete capacitive sensing system was implemented in hardware and experiment results using crude oil samples demonstrated that a resolution of ± 50 ppm of water content in crude oil was achieved by the proposed design.
A 360° twisted helical capacitance sensor was developed for holdup measurement in horizontal two-phase stratified flow. Instead of suppressing nonlinear response, the sensor was optimized in such a way that a 'sine-like' function was displayed on top of the linear function. This concept of design had been implemented and verified in both software and hardware. A good agreement was achieved between the finite element model of proposed design and the approximation model (pure sinusoidal function), with a maximum difference of ±1.2%. In addition, the design parameters of the sensor were analysed and investigated. It was found that the error in symmetry of the sinusoidal function could be minimized by adjusting the pitch of helix. The experiments of air-water and oil-water stratified flows were carried out and validated the sinusoidal relationship with a maximum difference of ±1.2% and ±1.3% for the range of water holdup from 0.15 to 0.85. The proposed design concept therefore may pose a promising alternative for the optimization of capacitance sensor design.
This research aimed to optimize the camera calibration process by identifying the optimal distance and angle for capturing checkered board images, with a specific focus on understanding the factors that influence the reprojection error (ϵRP). The objective was to improve calibration efficiency by exploring the impacts of distance and orientation factors and the feasibility of independently manipulating these factors. The study employed Zhang's camera calibration method, along with the 2k full-factorial analysis method and the Latin Hypercube Sampling (LHS) method, to identify the optimal calibration parameters. Three calibration methods were devised: calibration with distance factors (D, H, V), orientation factors (R, P, Y), and the combined two influential factors from both sets of factors. The calibration study was carried out with three different stereo cameras. The results indicate that D is the most influential factor, while H and V are nearly equally influential for method A; P and R are the two most influential orientation factors for method B. Compared to Zhang's method alone, on average, methods A, B, and C reduce ϵRP by 25%, 24%, and 34%, respectively. However, method C requires about 10% more calibration images than methods A and B combined. For applications where lower value of ϵRP is required, method C is recommended. This study provides valuable insights into the factors affecting ϵRP in calibration processes. The proposed methods can be used to improve the calibration accuracy for stereo cameras for the applications in object detection and ranging. The findings expand our understanding of camera calibration, particularly the influence of distance and orientation factors, making significant contributions to camera calibration procedures.
Carrageenans are linear sulphated polysaccharides that are commonly added into confectionery products but may exert a detrimental effect to human health. A new and simpler way of carrageenan determination based on an optical sensor utilizing a methylcellulose/poly(n-butyl acrylate) (Mc/PnBA) composite membrane with immobilized methylene blue (MB) was developed. The hydrophilic Mc polymer membrane was successfully modified with a more hydrophobic acrylic polymer. This was to produce an insoluble membrane at room temperature where MB reagent could be immobilized to build an optical sensor for carrageenan analysis. The fluorescence intensity of MB in the composite membrane was found to be proportional to the carrageenan concentrations in a linear manner (1.0-20.0 mg L-1, R2 = 0.992) and with a detection limit at 0.4 mg L-1. Recovery of spiked carrageenan into commercial fruit juice products showed percentage recoveries between 90% and 102%. The optical sensor has the advantages of improved sensitivity and better selectivity to carrageenan when compared to other types of hydrocolloids. Its sensitivity was comparable to most sophisticated techniques for carageenan analysis but better than other types of optical sensors. Thus, this sensor provides a simple, rapid, and sensitive means for carageenan analysis.
β-Thalassemia is a public health problem where 4.5% of Malaysians are β-thalassemia carriers. The genetic disorder is caused by defects in the β-globin gene complex which lead to reduced or complete absence of β-globin chain synthesis. Five TaqMan genotyping assays were designed and developed to detect the common β-thalassemia mutations in Malaysian Malays. The assays were evaluated with 219 "blinded" DNA samples and the results showed 100% sensitivity and specificity. The in-house designed TaqMan genotyping assays were found to be cost- and time-effective for characterization of β-thalassemia mutations in the Malaysian population.
This paper investigated the throughput performance of a secondary user (SU) for a random primary user (PU) activity in a realistic experimental model. This paper proposed a sensing and frame duration of the SU to maximize the SU throughput under the collision probability constraint. The throughput of the SU and the probability of collisions depend on the pattern of PU activities. The pattern of PU activity was obtained and modelled from the experimental data that measure the wireless local area network (WLAN) environment. The WLAN signal has detected the transmission opportunity length (TOL) which was analyzed and clustered into large and small durations in the CTOL model. The performance of the SU is then analyzed and compared with static and dynamic PU models. The results showed that the SU throughput in the CTOL model was higher than the static and dynamic models by almost 45% and 12.2% respectively. Furthermore, the probability of collisions in the network and the SU throughput were influenced by the value of the minimum contention window and the maximum back-off stage. The simulation results revealed that the higher contention window had worsened the SU throughput even though the channel has a higher number of TOLs.
This paper reports a method that enables real-time displacement monitoring and control of micromachined resonant-type actuators using wireless radiofrequency (RF). The method is applied to an out-of-plane, spiral-coil microactuator based on shape-memory-alloy (SMA). The SMA spiral coil forms an inductor-capacitor resonant circuit that is excited using external RF magnetic fields to thermally actuate the coil. The actuation causes a shift in the circuit's resonance as the coil is displaced vertically, which is wirelessly monitored through an external antenna to track the displacements. Controlled actuation and displacement monitoring using the developed method is demonstrated with the microfabricated device. The device exhibits a frequency sensitivity to displacement of 10 kHz/µm or more for a full out-of-plane travel range of 466 µm and an average actuation velocity of up to 155 µm/s. The method described permits the actuator to have a self-sensing function that is passively operated, thereby eliminating the need for separate sensors and batteries on the device, thus realizing precise control while attaining a high level of miniaturization in the device.
A DNA micro-optode for dengue virus detection was developed based on the sandwich hybridization strategy of DNAs on succinimide-functionalized poly(n-butyl acrylate) (poly(nBA-NAS)) microspheres. Gold nanoparticles (AuNPs) with an average diameter of ~20 nm were synthesized using a centrifugation-based method and adsorbed on the submicrometer-sized polyelectrolyte-coated poly(styrene-co-acrylic acid) (PSA) latex particles via an electrostatic method. The AuNP-latex spheres were attached to the thiolated reporter probe (rDNA) by Au-thiol binding to functionalize as an optical gold-latex-rDNA label. The one-step sandwich hybridization recognition involved a pair of a DNA probe, i.e., capture probe (pDNA), and AuNP-PSA reporter label that flanked the target DNA (complementary DNA (cDNA)). The concentration of dengue virus cDNA was optically transduced by immobilized AuNP-PSA-rDNA conjugates as the DNA micro-optode exhibited a violet hue upon the DNA sandwich hybridization reaction, which could be monitored by a fiber-optic reflectance spectrophotometer at 637 nm. The optical genosensor showed a linear reflectance response over a wide cDNA concentration range from 1.0 × 10-21 M to 1.0 × 10-12 M cDNA (R2 = 0.9807) with a limit of detection (LOD) of 1 × 10-29 M. The DNA biosensor was reusable for three consecutive applications after regeneration with mild sodium hydroxide. The sandwich-type optical biosensor was well validated with a molecular reverse transcription polymerase chain reaction (RT-PCR) technique for screening of dengue virus in clinical samples, e.g., serum, urine, and saliva from dengue virus-infected patients under informed consent.
An intelligent transportation system (ITS) aims to improve traffic efficiency by integrating innovative sensing, control, and communications technologies. The industrial Internet of things (IIoT) and Industrial Revolution 4.0 recently merged to design the industrial Internet of things-intelligent transportation system (IIoT-ITS). IIoT sensing technologies play a significant role in acquiring raw data. The application continuously performs the complex task of managing traffic flows effectively based on several parameters, including the number of vehicles in the system, their location, and time. Traffic density estimation (TDE) is another important derived parameter desirable to keep track of the dynamic state of traffic volume. The expanding number of vehicles based on wireless connectivity provides new potential to predict traffic density more accurately and in real time as previously used methodologies. We explore the topic of assessing traffic density by using only a few simple metrics, such as the number of surrounding vehicles and disseminating beacons to roadside units and vice versa. This research paper investigates TDE techniques and presents a novel Markov model-based TDE technique for ITS. Finally, an OMNET++-based approach with an implementation of a significant modification of a traffic model combined with mathematical modeling of the Markov model is presented. It is intended for the study of real-world traffic traces, the identification of model parameters, and the development of simulated traffic.
Ripeness classification of oil palm fresh fruit bunches (FFBs) during harvesting is important to ensure that they are harvested during optimum stage for maximum oil production. This paper presents the application of color vision for automated ripeness classification of oil palm FFB. Images of oil palm FFBs of type DxP Yangambi were collected and analyzed using digital image processing techniques. Then the color features were extracted from those images and used as the inputs for Artificial Neural Network (ANN) learning. The performance of the ANN for ripeness classification of oil palm FFB was investigated using two methods: training ANN with full features and training ANN with reduced features based on the Principal Component Analysis (PCA) data reduction technique. Results showed that compared with using full features in ANN, using the ANN trained with reduced features can improve the classification accuracy by 1.66% and is more effective in developing an automated ripeness classifier for oil palm FFB. The developed ripeness classifier can act as a sensor in determining the correct oil palm FFB ripeness category.
Recently, there has been increasing interest in electrochemical printed sensors for a wide range of applications such as biomedical, pharmaceutical, food safety, and environmental fields. A major challenge is to obtain selective, sensitive, and reliable sensing platforms that can meet the stringent performance requirements of these application areas. Two-dimensional (2D) nanomaterials advances have accelerated the performance of electrochemical sensors towards more practical approaches. This review discusses the recent development of electrochemical printed sensors, with emphasis on the integration of non-carbon 2D materials as sensing platforms. A brief introduction to printed electrochemical sensors and electrochemical technique analysis are presented in the first section of this review. Subsequently, sensor surface functionalization and modification techniques including drop-casting, electrodeposition, and printing of functional ink are discussed. In the next section, we review recent insights into novel fabrication methodologies, electrochemical techniques, and sensors' performances of the most used transition metal dichalcogenides materials (such as MoS2, MoSe2, and WS2), MXenes, and hexagonal boron-nitride (hBN). Finally, the challenges that are faced by electrochemical printed sensors are highlighted in the conclusion. This review is not only useful to provide insights for researchers that are currently working in the related area, but also instructive to the ones new to this field.