Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle

This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. The recorded data were obtained from 70 real driving trips of a BMW i3 EV, where the inputs of the DL were the voltage, current, battery temperature and ambient temperature while the output was the real SOC recorded during all trips. The data were divided into 60 trips for training and the final 10 trips for testing the performance of the developed EMA-DL model. The findings of the study demonstrated the promising results of EMA-DL in terms of obtaining the minimum error, which significantly increases the accuracy of the SOC estimation. To show the effectiveness of EMA-DL, comparison studies were conducted among other metaheuristic optimizers that were also used to optimize the DL parameters viz, Particles Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE) as well as the Adaptive Moment Estimation (ADAM). According to the simulation results, the proposed EMA-DL algorithm was found to outperform all the other compared algorithms based on the evaluated metrics. Thus, it can be employed as a proficient technique to accurately estimate the state of charge (SOC) of electric vehicle batteries

Comparative study for cursor detection at endoscopic images for telepointer

Communication over the internet is a common practice among computer users. A pointer is an essential tool for effective communication, pointing to a landmark or an intended object. Telepointer have become an important gadget for telemedicine to pinpoint the exact location of lesions, especially for endoscopic images. The endoscopic image will be displayed on the monitor at the surgeon's site, and the same view will be displayed at the remote expert site. However, the challenges for endoscopic images are the unconscious movement of the tissues in the endoscopic images, uniform texture, and varied illumination, which make it hard to keep track of the intended object. In this paper, a comparative study to detect the cursor over the endoscopic images was explored. RGB color space and HSV color space were used for comparative study. Experimental results revealed that HSV color space works well for cursor detection with an accuracy of 99.59%

Comparative study on hyperspectral image enhancement for low illumination outdoor scenes images

Hyperspectral image is rich with information because it contains spatial and spectral properties of specific objects. However, the image quality may be affected by low lighting conditions caused by non-uniform illumination environments, uncontrollable weather, which tends to darken outdoor scenes. Difficulty arises for high order image processing modalities such as detection, classification and tracking. In this paper, a comparative study was conducted to identify the most appropriate enhancement method for outdoor scenes. Four techniques were investigated: Bio-Inspired Multi-Exposure Fusion (BIMEF), Dehazing, Illumination Estimation, and Multi-deviation Fusion (MF). Experiments revealed that BIMEF is the best approach with the lowest lightness of error

Development of IoT based smart sorting recycle bin using raspberry Pi3 B+

Nowadays, the expansion in population and settlement pollutes the environment due to the community’s laid-back attitude; this problem raises the authorities’ management expenses and causes environmental concerns. As a result, the goal of this initial work is to create an automated system for sorting the recycle bin with both local and distant monitoring indicators using the Raspberry Pi3 B+. The locally accessible resources were used to design and fabricate the IoT-based smart recycle container. The system was driven by a 5 V/2 A rechargeable battery that powered the recycle container. It was also made to distinguish between three different types of garbage: paper, metal, and plastic. As a result, the system was able to recognise the different types of materials that were thrown into the recycle bin. Simultaneously, the user can use their smartphone to check the status of the recycle bin. In conclusion, the development of this IoT-based smart recycle bin can help to ensure that the surrounding area is clean and environmentally friendly

Modelling of ERT for household underground pipe detection using COMSOL multiphysics

Electrical resistance tomography (ERT) is a widely used in geophysical application. The purpose of this paper is to investigate the possibility of ERT systems to detect leakage or cracking of houehold underground pipe. A COMSOL Multiphysics software is implemented as the main tool for modelling ERT systems. 8 electrodes were modelled in 2 dimensions. At the same time, tomograms were also obtained and analyzed using MATLAB software. A linear back projection algorithm is implemented to reconstruct the image of the attractive area. Several different size and positions of underground leaking were analysed. The average value of MSSIM for all results in 0.01. This is because the smearing effect occurred when the linear back projection was implemented. In summary, a non-invasive strategy based on ERT is projected to be deployed for detecting leaks or cracks in underground pipes, but more research is required

Initial study of invasive approach of electrical capacitance tomography for identifying non-conducting medium in steel pipe application

The paper aims to investigate the possibility of an invasive method for electrical capacitance tomography system for steel pipe application. This work presents the development process for modeling an ECT (Electrical Capacitance Tomography) sensor using COMSOL Multiphysics. COMSOL Multiphysics software is implemented as the main tool to model the ECT system. The 12 electrodes are modeled in 2-dimensional and it is based on the invasive approach. The ECT system is developed to obtain the electrical potential distribution between electrodes when an electric field is applied. Besides, it also obtains the permittivity distribution inside the closed pipe. This invasive approach is applied for the steel pipe that cannot be used with common ECT. Several positions of bubble air as the obstacle in the oil medium are tested. As a result, the sensor readings performance inside the region of interest is analyzed. Simultaneously, the tomograms are also obtained and analyzed using MATLAB software. A linear back-projection algorithm is implemented to reconstruct the image of the region of interest. Thus, the possibility of the ECT system applied for steel pipe can be observed and compared when there is a change of readings between the full oil and the existing obstacle inside the steel pipe. Besides, the tomograms for each condition tested can be observed. In short, the invasive approach for ECT is seen to be possible to apply for oil-gas application in steel pipe. The LBP algorithm with the average MSSIM value around 0.3 was able to detect the oil-gas regime inside the steel pipe

Does parallel projection is suitable in electrical capacitance tomography? -A comparison with common approach

Electrical Capacitance Tomography (ECT) is one of the soft field tomography that widely used for the purpose of measurement and monitoring of multiphase flow. Common problem of the soft field tomography is low quality and unstable images in the pipe especially at the center section of the pipe. In this paper, an ECT system with a comparison between common approach and a parallel approach is presented. Simulation in 2 dimensions with 16-electrode is carried out to observe a potential projection. The COMSOL Multiphysics software is used to investigate the state and response of the electric field with this approach by exporting data with 128x128 pixels. Air bubbles as a phantom in the oil medium have been tested and analyzed. Linear Back-Projection Algorithm (LBP) is implemented using MATLAB software to obtain a tomogram. A Multi Scale Structural Similarity, MSSIM was applied to compare both approaches. Consequently, the resolution and quality of the pictures in the pipes can be distinguished. However, a further investigation is needed to improve the parallel approach for ECT system

Does parallel projection is suitable in electrical capacitance tomography

Electrical Capacitance Tomography (ECT) is one of the soft field tomography that widely used for the purpose of measurement and monitoring of multiphase flow. Common problem of the soft field tomography is low quality and unstable images in the pipe especially at the center section of the pipe. In this paper, an ECT system with a comparison between common approach and a parallel approach is presented. Simulation in 2 dimensions with 16-electrode is carried out to observe a potential projection. The COMSOL Multiphysics software is used to investigate the state and response of the electric field with this approach by exporting data with 128x128 pixels. Air bubbles as a phantom in the oil medium have been tested and analyzed. Linear Back-Projection Algorithm (LBP) is implemented using MATLAB software to obtain a tomogram. A Multi Scale Structural Similarity, MSSIM was applied to compare both approaches. Consequently, the resolution and quality of the pictures in the pipes can be distinguished. However, a further investigation is needed to improve the parallel approach for ECT system

Initial study of invasive approach of electrical capacitance tomography for identifying non-conducting medium in steel pipe application

The paper aims to investigate the possibility of an invasive method for electrical capacitance tomography system for steel pipe application. This work presents the development process for modeling an ECT (Electrical Capacitance Tomography) sensor using COMSOL Multiphysics. COMSOL Multiphysics software is implemented as the main tool to model the ECT system. The 12 electrodes are modeled in 2-dimensional and it is based on the invasive approach. The ECT system is developed to obtain the electrical potential distribution between electrodes when an electric field is applied. Besides, it also obtains the permittivity distribution inside the closed pipe. This invasive approach is applied for the steel pipe that cannot be used with common ECT. Several positions of bubble air as the obstacle in the oil medium are tested. As a result, the sensor readings performance inside the region of interest is analyzed. Simultaneously, the tomograms are also obtained and analyzed using MATLAB software. A linear back-projection algorithm is implemented to reconstruct the image of the region of interest. Thus, the possibility of the ECT system applied for steel pipe can be observed and compared when there is a change of readings between the full oil and the existing obstacle inside the steel pipe. Besides, the tomograms for each condition tested can be observed. In short, the invasive approach for ECT is seen to be possible to apply for oil-gas application in steel pipe. The LBP algorithm with the average MSSIM value around 0.3 was able to detect the oil-gas regime inside the steel pipe

Implementation of fingerprint biometric template system in embedded software design

Reliable personal identification is necessary due to the growing importance of information technology and the necessity of protection and access restriction. The key task is to verify the person is who they claim to be. A biometric security system verifies user identity by comparing the behavioral or physiological trait possessed by the user to a previously stored sample of the trait. Fingerprints are the oldest and most widely used form of biometric identification. Local characteristic called minutiae points represent fingerprints. This project proposed an embedded software design of fingerprint biometric authentication system that involved interface design and software development in an embedded processor. The system consists of two components; the Graphic User Interface (GUI) on a host PC and the Fingerprint Biometric Template system on the Field Programmable Gate Array (FPGA) development board. The GUI will access the image repository and display the output image at each processing steps. The Fingerprint Biometric Template System contains three stages; image processing, feature extraction and matching stage. The image processing stage will enhance and skeletonized the fingerprint image, the feature extraction stage will extract the valid minutiae points in template based, and the matching stage will match the template with a previously stored template. An embedded software system that can verify the minutiae templates extracted a fingerprint image is resulted from this projec