The Performance of Single and Bilayer Graphene: The Initial Study

The tunable band gap has made graphene a promising material for the construction of next-generation electronic devices. In this paper, the electronic and transport characteristics of single and bilayer graphene are investigated using Extended-Huckel and Non-Equilibrium Green’s Functional (NEGF) simulations. Results from the simulations showed that the band gap opening depends on the arrangement and the layers of the graphene up to 1.701 eV and 1.854 eV for AA-stacked and AB-stacked bilayer graphene respectively. The conductance, thermal conductance, and the I-V curves changed significantly depending on the transmission spectrum of the graphene sheet or graphene device itself. The I – V curve shows p-type semiconductor behavior. Lastly, the bilayer graphene shows excellent performance compared to the single-layer device with the AA device showing superior performance than AB by 2.45%

The Ab-initio Study of Bulk Single Layer Defected Graphene Towards Graphene Device

Graphene is a promising new material for the construction of graphene devices because of its surface modification can be tuned the band gap. In this paper, the electronic and transport characteristics of defected graphene device are investigated. Both the electronic and transport characteristics are simulated using density functional theory (DFT). The band structures and transmission spectra are analyzed. The conductance and thermal conductance characteristic for both graphene is compared. From the simulation, it is found that the conductance, thermal conductance, and the I-V curves depend on the transmission spectrum of the graphene sheet or graphene device itself. The comparison between the defected graphene itself shows that the single layer with two vacancies shows better performance

Machine vision based smart parking system using Internet of Things

It is expected that in the next decade, majority of world population will be living in cities. Better public services and infrastructures in the city are needed to cope with the booming population. City vehicles that cruising for parking have indirectly causing traffic, making one harder to travel around the city. Thus, a smart parking system can certainly lays the foundation to build a smart city. This paper proposed a cost-effective IoT smart parking system to monitor city parking space and provide real-time parking information to drivers. Moreover, instead of the conventional approach that uses embedded sensors to detect vehicles in the parking area, camera image and machine vision technology are used to obtain the parking status. In the prototype, twenty outdoor parking lots are covered using a 5 megapixel camera connected to Raspberry Pi 3 installed at the 5th floor of the nearby building. Machine vision in this project that involved motion tracking and Canny edge detection are programmed in Python 2 using OpenCV technology. Corresponding data is uploaded to an IoT platform called Ubidots for possible monitoring activity. An Android mobile application is designed for user to download real-time data of parking information. This paper introduces a low cost smart parking system with the overall detection accuracy of 96.40%. Also, the mobile application allows users to alert other car owners for any emergency incidents and double parking blockage. The developed system can provide a platform for users to search for empty car parking with ease and reduce the traffic issues such as illegal double parking especially in the urban area

Low Power CMOS Electrocardiogram Amplifier Design for Wearable Cardiac Screening

The trend of health care screening devices in the world is increasingly towards the favor of portability and wearability. This is because these wearable screening devices are not restricting the patient’s freedom and daily activities. While the demand of low power and low cost biomedical system on chip is increasing in exponential way, the front-end electrocardiogram (ECG) amplifiers are still suffering from flicker noise for low frequency cardiac signal acquisition, 50Hz power line electromagnetic interference, and the large unstable input offsets due to the electrode-skin interface is not attached properly. In this paper, a CMOS based ECG amplifier that suitable for low power wearable cardiac screening is proposed. The amplifier adopts the highly stable folded cascode topology and later being implemented into RC feedback circuit for low frequency DC offset cancellation. By using  0.13µm CMOS technology from Silterra, the simulation results show that this front-end circuit can achieve a very low input referred noise of  1pV/Hz1/2 and high common mode rejection ratio of 174.05dB. It also gives voltage gain of 75.45dB with good power supply rejection ratio of 92.12dB. The total power consumption is only 3µW and thus suitable to be implemented with further signal processing and classification back end for low power wearable biomedical device

Characterization of Polydimethylsiloxane Dielectric Films for Capacitive ECG Bioelectrodes

Capacitive ECG bioelectrodes are potentials for wearable and long-term physiological monitoring applications. In non-contact ECG recordings, the dielectric material sets limit to smooth bioelectric signal acquisition. Previously used dielectrics are rigid, unconformable on the skin, induce artefact and triboelectric noise, and becomes unstable when they absorb skin exudates. Recently, polymeric materials such as PDMS have gained different biomedical applications because it is biocompatible, flexible, and easy to fabricate. However, its use as a dielectric for capacitive ECG sensing is poorly reported. In this study, 15 samples of thin PDMS films of various thicknesses were fabricated by varying the proportion of the Sylgard 184TM silicone elastomer to the crosslinker from Dow Corning Corporation and manually deposited on acrylic glass substrates. The composition ratio and thickness were used to tune the structure and dielectric properties of the films. The effects on the capacitance generated by each dielectric film were measured using the parallel plate method, and their corresponding values of relative permittivity was also estimated. The results obtained reveal that PDMS films made from a composition ratio of 10:2 yielded the maximum capacitance and relative permittivity. In contrast, the film with 0.14mm thickness revealed the highest value of capacitance (31pF). The recorded values of capacitance demonstrate the feasibility of PDMS dielectrics for capacitive ECG bioelectrodes

A low cost spectroscopy with Raspberry Pi for soil macronutrient monitoring

Soil spectroscopy measurement is widely used to determine the macronutrients content in the soil. Spectrometer is costly equipment and commonly used to determine the transmittance, absorbance or reflectance level of various liquids and opaque solids by measuring the intensity of light as a light source passes through a sample chemical substance. This paper is reported on a low cost experimental assessment of soil macronutrient for soil spectroscopy utilizing Raspberry Pi (RPI) module in visible and near-infrared (NIR) wavelength. The sensitivity measurements are mainly due to the concentration level and the intensity of light emitting diode (LED) light source. The work is focusing on the absorbance spectroscopy particularly on linear relationship to determine the Nitrogen (N), Phosphorus (P) and Potassium (K) content level in soil using colour-developing reagent. The development of low cost and portable RPI based spectrophotometer has created new possibilities to measure the concentration level of the existed soil macronutrient within visible and infrared light wavelength of light sources. The absorbance of light was computed based on Beer-Lambert Law. The low cost RPI based spectrometer costs 80% less than the spectrometer available in the market and is capable of recording the absorbance measurements up to 5 samples. The performance of this prototype shows that it is possible to build the spectrometer using open-source software and hardware by considering the limiting factors such as light transfer to the sample, spectral filtering and the sensitivity due to the signal-to-noise ratio

Agarwood grading estimation using artificial neural network technique and carving automation

Agarwood is a fragrant dark resinous wood formed when Aquilaria tress infected with a certain type of mold and appears like wood defects. It is the most valuable non-timber product has been traded in international markets because of its distinctive aroma, and can be processed into incense and perfumes. Agarwood grade is determined by several characteristics, such as black colour intensity, smell, texture and weight through visual inspection. However, this could lead to several problems such as false grading results. Traditionally, the carving process of separation of the uninfected Aquilaria wood that lacks of the dark resinous accomplished by using simple tools like knife and chisel. Hence, an expert worker is required to complete the task. In this paper, the Artificial Neural Network (ANN) technique is used to classify the Agarwood based on the features extraction from Gabor Filter and percentage of black colour estimation. At first, the images of seven groups of wood defects or knots are identified: dry, decayed, edge, encased, horn, leaf, and sound defect with total sample of 410 knots. Then, these images of knots are matched into three grade groups of Agarwood. Next, the experimental results show that the Agarwood can be classified into three grades groups based on knot and black intensity. A set of selected images of knots were used as trace patterns and carved on pieces of wood blocks by using a Computer Numerical Control (CNC) machine where the total time taken for each carving process was calculated. For each image, two Gabor Filter features and percentage of black colour were used as ANN inputs. In conclusion, the total accuracy of the experiments is 98% and the total time of carving is increased with the increased of grade group number

Ultra sensitive CMOS biosensor array for label free DNA detection: Circuit design consideration

Electrical biosensors are one strategy being explored for the development of a rapid point-of-care and onsite DNA testing tools since this technology is amenable to miniaturization, can be accurate and highly sensitive with simple instrumentation, and relatively inexpensive. A label free and fully integrated semiconductor sensor array based on differential charge-based capacitance measurement for DNA sensing is presented. The 4 × 4 sensor array circuit has been designed using a 2-poly 2-metal 1.2 μm CMOS process from ON Semiconductor. Each sensor features an integrated microelectrode of 16 μm2. The linear sensitivity is 3 mV/fF for the target input capacitance range of 1 to 103 fF. An array-clock controller scheme to selectively activate the array cell and capacitance-to-voltage conversion circuit has been proposed, enabling low power biosensor arrays

Iot-based parking violation detection for effective urban traffic management

The increasing number of vehicles on the road along with the mismanagement of available parking space leads to the parking-related problems as well as increased traffic congestion in urban areas. As result, it causes a critical issue for driver and the city municipality council. From the driver’s side, how to find an available parking lot in a city is a considerable concern. However, from the city municipality council’s side, how to manage and distribute such a limited public parking resource efficiently to give every visitor a fair chance of finding an on-street parking lot is also a considerable concern. The proposed solution to solve the problem is to raise a new perspective on such smart parking violation detection system for smart cities based on IoT. This system aims to help the parking authoritative officers to ease their job and reduce the manpower needed. It will assist parking management with a real-time detection of improper parking by estimating each vehicle’s duration of parking lot usage and automatically collect the parking charges. This system also detects the availability of parking space and allows the driver to make a reservation for parking lot beforehand. As a result, this parking violation detection system will solve city municipality council’s problem of controlling parking violation. Apart from that, this system is designed to assist authoritative officers in finding parking violations easily and recommends the least cost path for officers so that officers can achieve their highest productivity in finding parking violations and issuing parking tickets. This system will use Intel UP2 (UP Squared) board as main board for digital image processing using machine vision technology. Moreover, IoT cloud is employed to communicate with the Android mobile apps for data analysis and authorities. Mobile apps are for authoritative officers to get real-time data on a parking violation