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A Practical Study of Intelligent Image-Based Mobile Robot for Tracking Colored Objects

Computers, Materials & Continua 2024年第8期80卷 2181-2197页

作者： Mofadal Alymani Mohamed Esmail Karar Hazem Ibrahim Shehata College of Computing and Information Technology Shaqra UniversityShaqra11961Saudi Arabia Faculty of Electronic Engineering Menoufia UniversityMenouf32952Egypt Faculty of Engineering Zagazig UniversityZagazig44519Egypt

Object tracking is one of the major tasks for mobile robots in many real-world ***,artificial intelligence and automatic control techniques play an important role in enhancing the performance of mobile robot *** contrast to previous simulation studies,this paper presents a new intelligent mobile robot for accomplishing multi-tasks by tracking red-green-blue(RGB)colored objects in a real experimental ***,a practical smart controller is developed based on adaptive fuzzy logic and custom proportional-integral-derivative(PID)schemes to achieve accurate tracking results,considering robot command delay and tolerance *** design of developed controllers implies some motion rules to mimic the knowledge of experienced *** scenarios of three colored object combinations have been successfully tested and evaluated by using the developed controlled image-based robot *** PID control failed to handle some tracking scenarios in this *** proposed adaptive fuzzy PID control achieved the best accurate results with the minimum average final error of 13.8 cm to reach the colored targets,while our designed custom PID control is efficient in saving both average time and traveling distance of 6.6 s and 14.3 cm,*** promising results demonstrate the feasibility of applying our developed image-based robotic system in a colored object-tracking environment to reduce human workloads.

关键词： Mobile robot autonomous systems fuzzy logic control real-time image processing

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Optimal aeration management strategy for a small-scale food waste composting

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Carbon Resources Conversion 2024年第1期7卷 79-88页

作者： Jia Chi Lai Yi Lung Then Siaw San Hwang Chung Sien Lee School of Engineering and Science Faculty of EngineeringComputing and ScienceSwinburne University of Technology93350 KuchingSarawakMalaysia Department of Electrical and Electronic Engineering Faculty of EngineeringUniversiti Malaysia Sarawak94300 Kota SamarahanSarawakMalaysia

Food waste is a significant contributor to greenhouse gas emissions when it ends up in *** turns out to be a sustainable solution to this problem,but it requires controlled and continuous airflow for optimal *** study focused on the effect of aeration rates and airflow directions on food waste composting using a closed system with forced *** was entered into the composting vessel in three directions,which were upward,downward,and a combination of both *** direction was run at aeration rates of 0.1,0.4,and 0.7 L/*** findings showed that the compost pile aerated at 0.4 L/min by using two-directional airflow can reach the thermophilic temperature within half of the *** compost pile achieved temperature of 40.94℃ after 10.5 *** the compost experienced slightly high in moisture loss(4.3%),the compost still attained the standard values for *** compost produced from food waste could be applied in soil to improve its fertility.

关键词： Small-scale composting Two-directional airflow Intermittent aeration Food waste

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Optimisation and Performance Computation of a Phase Frequency Detector Module for IoT Devices

Annals of Emerging Technologies in Computing

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Annals of Emerging Technologies in computing 2024年第1期8卷 13-21页

作者： Hemel, Md. Shahriar Khan Reaz, Mamun Bin Ibne Ali, Sawal Hamid Bin Md Bhuiyan, Mohammad Arif Sobhan Miraz, Mahdi H. Department of Electrical Electronic and Systems Engineering Universiti Kebangsaan Malaysia Malaysia Department of Electrical and Electronic Engineering Independent University Bangladesh School of Electrical Engineering and Artificial Intelligence Xiamen University Malaysia Malaysia School of Computing and Data Science Xiamen University Malaysia Malaysia Faculty of Arts Science and Technology Wrexham University United Kingdom Faculty of Computing Engineering and Science University of South Wales United Kingdom

The Internet of Things (IoT) is pivotal in transforming the way we live and interact with our surroundings. To cope with the advancement in technologies, it is vital to acquire accuracy with the speed. A phase frequency detector (PFD) is a critical device to regulate and provide accurate frequency in IoT devices. Designing a PFD poses challenges in achieving precise phase detection, minimising dead zones, optimising power consumption, and ensuring robust performance across various operational frequencies, necessitating complex engineering and innovative solutions. This study delves into optimising a PFD circuit, designed using 90 nm standard CMOS technology, aiming to achieve superior operational frequencies. An efficient and high-frequency PFD design is crafted and analysed using cadence virtuoso. The study focused on investigating the impact of optimising PFD design. With the optimised PFD, an operational frequency of 5 GHz has been achieved, along with a power consumption of only 29 µW. The dead zone of the PFD was only 25 ps. © 2024 by the author(s).

关键词： Phase locked loops

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Traffic Control Based on Integrated Kalman Filtering and Adaptive Quantized Q-Learning Framework for Internet of Vehicles

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Computer Modeling in engineering & Sciences 2024年第3期138卷 2103-2127页

作者： Othman S.Al-Heety Zahriladha Zakaria Ahmed Abu-Khadrah Mahamod Ismail Sarmad Nozad Mahmood Mohammed Mudhafar Shakir Hussein Alsariera Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka(UTeM)Durian TunggalMalaysia College of Computing&Informatics Saudi Electronic UniversityRiyadhSaudi Arabia Department of Electrical Electronic and System EngineeringUniversiti Kebangsaan MalaysiaUKM BangiSelangorMalaysia Computer Technology Engineering College of Engineering TechnologyAl-Kitab UniversityKirkukIraq Faculty of Engineering and Electronic Engineering Universiti Tun Hussein Onn Malaysia(UTHM)Batu PahatMalaysia 6Research Center DepartmentThe University of MashreqBaghdadIraq

Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the *** this article,these issues are handled by proposing a novel framework for traffic control using vehicular communications and Internet of Things *** framework integrates Kalman filtering and *** smoothing Kalman filtering,our data fusion Kalman filter incorporates a process-aware model which makes it superior in terms of the prediction *** traditional Q-learning,our Q-learning algorithm enables adaptive state quantization by changing the threshold of separating low traffic from high traffic on the road according to the maximum number of vehicles in the junction *** evaluation,the model has been simulated on a single intersection consisting of four roads:east,west,north,and south.A comparison of the developed adaptive quantized Q-learning(AQQL)framework with state-of-the-art and greedy approaches shows the superiority of AQQL with an improvement percentage in terms of the released number of vehicles of AQQL is 5%over the greedy approach and 340%over the state-of-the-art ***,AQQL provides an effective traffic control that can be applied in today’s intelligent traffic system.

关键词： Q-learning intelligent transportation system(ITS) traffic control vehicular communication kalman filtering smart city Internet of Things

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Development of Android Application for Intelligent 2D Breast Cancer Visualization 1

Development of Android Application for Intelligent 2D Breast...

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1st IEEE International Conference on Communication engineering and Emerging Technologies, ICoCET 2024

作者： Vijayasarveswari, V. Nadeson, Pavitraa Fwen Hoon, Wee Mahrom, Norfadila Centre of Excellence Universiti Malaysia Perlis Faculty of Electronic Engineering Technology Perlis Malaysia Universiti Malaysia Perlis Faculty of Electronic Engineering Technology Perlis Malaysia Universiti Malaysia Perlis Advanced Computing Centre of Excellence Universiti Malaysia Perlis Faculty of Electronic Engineering Technology Perlis Malaysia

ISBN: (纸本)9798331504144

Most often affecting women after puberty, breast cancer is one of the most common cancer-related disorders globally. Even though the condition kills thousands of people every year, if it is discovered promptly, it can usually be treated. Therefore, quick and accurate detection techniques are essential for the patient's survival. In the past, medical professionals used manual detection methods to achieve this goal. Most of the researches usually focusing more on detecting compared to visualizing. Visualizing Breast cancer is important so many people can understand their condition easily. The goal of this research is to create a new Android application that will visualize the detected breast cancer in 2D environment using Android based smartphone. This in project, there are two phases. Phase 1 is data preparation for the visualization and phase 2 visualization of tumor in 2D environment. In this process, data is extracted from Matlab and it visualize in mobile application. The data is processed by using machine learning. The detected tumor is visualizes using Android based smart phone. The application is developed by using 000webhost, MySQL and Android Studio. The utilization of android applications is quite advantageous as they advance technology and provide consumers with a variety of viewpoints. It is able to handle and visualize these data better than other standard systems. To test the system, we initially tried it with 10 data sets. Once 10 data are appropriately visualized. To check its functionality, we added more data, Additionally, the application can help user to understand the state of their breast health without the expertise. © 2024 IEEE.

关键词： Diseases

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Towards Accurate RPM Detection Using Primary Ignition Pulses 49

Towards Accurate RPM Detection Using Primary Ignition Pulses

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49th Annual Conference of the IEEE Industrial electronics Society, IECON 2023

作者： Wijayaraja, Jaliya L. Abhayasinghe, Nimsiri Wellalage, Sasini Sliit Faculty of Computing Department of Computer Systems Engineering Malabe Sri Lanka Sliit Faculty of Engineering Department of Electrical and Electronic Engineering Malabe Sri Lanka

ISBN: (纸本)9798350331820

Enhancing the performance and extending the life-cycle of older vehicles through retrofitting with improved systems presents an alluring opportunity. However, achieving accurate sensing of crucial parameters, such as engine revolutions per minute (RPM), poses challenges due to the need for mechanical manipulation and some designs, which may result in diminished accuracy in adverse settings. This study proposes using the primary ignition pulse signal to accurately determine engine speed without mechanical manipulation. We investigate the effectiveness of signal processing methods, including the RC filter, 2nd and 6th order Butterworth filter, to improve the accuracy of the readings. Our proposed method successfully collects data from conventional internal combustion engines, with simulated signal processing methods producing accurate detection of RPM and reduced fluctuations. The proposed method eliminated the noise, leading to accurate RPM measurements, while the maximum standard deviation observed for the RC filter implementation was 38.74. By accurately sensing key parameters, older vehicles can be retrofitted with improved systems, leading to enhanced performance and an extended lifecycle. The introduced methods can be practically implemented using custom electronics or embedded systems and can contribute to future research on automotive retrofitting. © 2023 IEEE.

关键词： Life cycle

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Towards Holistic Crime Management Through Descriptive Analysis and Predictive Forecasting 6

Towards Holistic Crime Management Through Descriptive Analys...

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6th International Conference on Advancements in computing, ICAC 2024

作者： Wijethunge, Tinaya Edirisinghe, Sampath Jeon, Mansik Kim, Jeehyun Wijesinghe, Ruchire Silva, Bhagya Faculty of Engineering Department of Computer Engineering Nugegoda Sri Lanka Daegu Korea Republic of Faculty of Engineering Department of Electrical and Electronic Engineering Malabe Sri Lanka Malabe Sri Lanka Faculty of Computing Department of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798331517878

Throughout the evolution of humankind, devising effective crime prevention strategies has been a concern in fostering safer communities. Although achieving a zero-crime rate is not possible yet, using data management methods can contribute to preventing and minimizing crimes. This article presents an integrated approach to proactive crime prevention. Data insights derived from analysis and visualization provide a comprehensive overview of historical trends and scenarios, aiding understanding of past and present situations. The forecasting of crime rates extends this comprehension to the future, spotlighting the severity of the potential threat to the safety of the community. Three distinct prediction models are presented to predict the occurrence of violent/non-violent crimes, the most probable crime type, and the most probable crime location in a spatial-temporal context, facilitating optimal resource allocation of police patrolling. Combining these three analytical components, an application is designed to present this holistic solution for effective crime prevention, with a 73% accuracy in predicting violent crimes. To achieve higher accuracy in predicting the most probable crime types and locations, it is essential to go beyond spatiotemporal context and augment data on other factors that affect the occurrence of crimes. © 2024 IEEE.

关键词： Prediction models

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Developed Fall Detection of Elderly Patients in Internet of Healthcare Things

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Computers, Materials & Continua 2023年第8期76卷 1689-1700页

作者： Omar Reyad Hazem Ibrahim Shehata Mohamed Esmail Karar College of Computing and Information Technology Shaqra UniversityP.O.Box 33Shaqra11961Saudi Arabia Faculty of Computers and Artificial Intelligence Sohag UniversitySohag82524Egypt Faculty of Engineering Zagazig UniversityZagazig44519Egypt Faculty of Electronic Engineering Menoufia UniversityMenouf32952Egypt

Falling is among the most harmful events older adults may *** the continuous growth of the aging population in many societies,developing effective fall detection mechanisms empowered by machine learning technologies and easily integrable with existing healthcare systems becomes *** paper presents a new healthcare Internet of Health Things(IoHT)architecture built around an ensemble machine learning-based fall detection system(FDS)for older *** to deep neural networks,the ensemble multi-stage random forest model allows the extraction of an optimal subset of fall detection features with minimal *** number of cascaded random forest stages is automatically *** study uses a public dataset of fall detection samples called SmartFall to validate the developed fall detection *** SmartFall dataset is collected based on the acquired measurements of the three-axis accelerometer in a *** scenario in this dataset is classified and labeled as a fall or a *** comparison to the three machine learning models—K-nearest neighbors(KNN),decision tree(DT),and standard random forest(SRF),the proposed ensemble classifier outperformed the other models and achieved 98.4%*** developed healthcare IoHT framework can be realized for detecting fall accidents of older people by taking security and privacy concerns into account in future work.

关键词： Elderly population fall detection wireless sensor networks Internet of health things ensemble machine learning

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IoT-Based Smart Underground Cable Fault Detector 1

IoT-Based Smart Underground Cable Fault Detector

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1st IEEE International Conference on Communication engineering and Emerging Technologies, ICoCET 2024

作者： Jayachandran, Murugakummar Abdul Rani, Khairul Najmy Wahab, Alawiyah Abd Universiti Malaysia Perlis Faculty of Electronic Engineering & Technology Perlis Malaysia Universiti Malaysia Perlis Centre of Excellence Advanced Communication Engineering Faculty of Electronic Engineering & Technology Perlis Malaysia School of Computing College of Arts & Sciences Universiti Utara Malaysia Kedah Malaysia

ISBN: (纸本)9798331504144

Underground high-voltage cable usage is expanding due to their resistance to pollutants, severe weather, heavy rain, and storms. However, these cables are prone to damage due to improper installation, poor jointing, and potential harm from third-party activities such as curb edging or trenching. Additionally, environmental factors, abrasion, and animal threats further complicate the process of locating and repairing faults. This project introduces a diagnosis system utilizing the Internet of Things (IoT) to identify and locate faults in underground cables. By enabling faster fault detection, the system aims to reduce the time, money, and effort associated with repairs. The IoT-based solution utilizes a set of voltage dividers mounted on the cable to detect faults. When a fault occurs due to a shortening between two cables, a voltage is generated, which is then detected by an ESP32 microcontroller. This microcontroller notifies the user by providing the fault location in kilometers. The gathered data is displayed on a liquid crystal display (LCD) and transmitted online via a Wi-Fi module to the Blynk cloud database for storage and further analysis. © 2024 IEEE.

关键词： Liquid crystal displays

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Cybersecurity and Smart Cities: Current Status and Future

Cybersecurity and Smart Cities: Current Status and Future

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2023 IEEE International Conference on Emerging Trends in engineering, Sciences and Technology, ICES and T 2023

作者： Habib, Muhammad Yasir Qureshi, Haseeb Ahmad Khan, Shujahat Ali Mansoor, Zara Chishti, Abdul Rehman The Islamia University of Bahawalpur Faculty of Engineering Dept. of Electronic Engineering Pakistan Bournemouth University Faculty of Computing Dept. of Computing and Informatics Bournemouth United Kingdom Charles Darwin University College of Engineering IT and Environment Darwin Australia

ISBN: (纸本)9781665455602

A Smart city implements the latest IoT and information and communication technologies (ICT) to improve the quality of urban city administrations, decrease expenditures, asset management and interconnect citizens of a Smart city. Smart cities offer numerous advantages like improved energy productivity, management, healthcare facilities, efficient transport systems, proper waste and water management, and individual security. Nonetheless, this reliance on ICT and IoT technologies makes a Smart city prone to digital cyber assaults. These technologies are vulnerable to many security issues like Information theft, Eaves-dropping attack, Denial of service, Communication delays, Data manipulation, IoT security attacks, Communication interception, Jamming, Sensor failure, insecure API, and Remote exploitation. This research study intends to address opinions on cybersecurity technologies, vulnerabilities, and cybercrime awareness based on the systematic literature review 'PRISMA Model' as our research method and help researchers and practitioners to look for innovative Smart City solutions. Our research endeavors to momentarily depict the central ideas of digital security and protection issues related to Smart city areas and uncover digital cyber-Attacks that focus on Smart city communities in the literature. In brief, the focus of this research is to explore and review the aspects of Smart city cybersecurity issues, Smart city vulnerabilities related to information security, and provide a comprehensive research framework that will help the researchers and practitioners explore this area of research. © 2023 IEEE.

关键词： Cybersecurity

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