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2023 IEEE Global Conference on Information Technologies and Communications, GCITC 2023

作者： Ravichandran, M. Laxmikant, Kumar Muthu, Annamalai Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Chennai India University of Technology & Applied Science Department of Electrical and Electronics Engineering Nizwa Oman

ISBN: (纸本)9798350308167

In the realm of real-time applications such as autonomous driving and surveillance, efficient vehicle detection stands as a paramount concern. The revolutionary You Only Look Once (YOLO) framework, renowned for its rapid object recognition, has reshaped this landscape. This study delves into the fusion of real-time vehicle detection and YOLO v8, optimizing its architecture for swift and precise identification. Empirical validation underscores the model's prowess, achieving a remarkable accuracy of 97.9% on mAP50 and 91.3% on mAP50-95. This achievement not only attests to the model's accuracy but also reaffirms its real-time processing capabilities. The implications resonate across transportation safety and urban planning, promising transformative potential. This research underscores the power of YOLO v8 in intelligent object detection, poised to reshape and enhance various domains. © 2023 IEEE.

关键词： mAP50 mAP50-95 Object Detection Vehicle Detection YOLO Framework

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Crop Disease Detection and Classification using Transfer Learning and Deep Convolutional Neural Networks

Crop Disease Detection and Classification using Transfer Lea...

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2023 IEEE International Conference on Modelling, Simulation and Intelligent Computing, MoSICom 2023

作者： Suchir Vangaveeti, V.N. Kalaichelvi, V. Jha, Anurag Kumar John Joseph, Alok Birla Institute of Technology and Science Department of Computer Science Engineering Dubai United Arab Emirates Birla Institute of Technology and Science Department of Electrical and Electronics Engineering Dubai United Arab Emirates

ISBN: (纸本)9798350393415

Crop diseases pose a significant threat to global food security, affecting the livelihoods of millions of smallholder farmers. Identifying these diseases is crucial yet challenging due to lack of proper infrastructure. Leveraging the widespread adoption of smartphones and with the advancements in computer vision, this paper proposes a solution through smartphone-Assisted disease diagnosis. Utilizing a publicly available dataset comprising of 54,306 images which include both healthy and diseased plants, we introduce a deep convolutional neural network which can identify 14 crop species and 38 diseases. Our final solution achieves an accuracy of 99.2% in training and 95.62% in testing, hence demonstrating the feasibility of the proposed method. Further improvement is possible with the help of a more diverse dataset. Overall, the paper outlines a clear pathway for global crop disease detection through smartphones. © 2023 IEEE.

关键词： Smartphones

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ReRobo Walker: Robotic Walker with Fall Detection and Active Safety 18

ReRobo Walker: Robotic Walker with Fall Detection and Active...

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18th IEEE Conference on Industrial electronics and Applications, ICIEA 2023

作者： Ding, Damin Wang, Yagang Zhang, Houji Meng, Qiaoling Yu, Hongliu Lin, Yanzhao Chen, Qiu University of Shanghai for Science and Technology Rehabilitation Engineering and Technology Institute School of Optical-Electrical and Computer Engineering Shanghai China Rehabilitation Engineering and Technology Institute School of Optical-Electrical School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai China Guangzhou Foreign Language School Guangzhou China University of Shanghai for Science and Technology Rehabilitation Engineering and Technology Institute Shanghai China University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai China Kogakuin University Major of Electrical Engineering and Electronics Graduate School of Engineering Tokyo Japan

ISBN: (纸本)9798350312201

In recent years, Chinese society has become increasingly ageing while the fertility rate continues to decline. This situation has led to a growing public demand for rehabilitation devices such as walking aids. A novel intelligent robotic walker named ReRobo Walker is proposed which can assist groups of elderly people with dysfunctional legs with rehabilitation training and indoor and outdoor walking. We design robust mechanical structures for robotic walker, install special 3D force sensor, 2D LIDAR and other sensors, and design new algorithms to enable intelligent functionality while guaranteeing the safety of robotic walker.(1) Real-time monitoring of the user's physical status, such as falls, through laser range sensors and 3D force sensor;(2) Modelling of the scene through 2D LIDAR for path planning, obstacle avoidance and navigation functions;(3) Precise control through LADRC-based algorithm for uphill assistance, downhill control and prevention of sharp shifts of the robotic walker. Experiment results demonstrate the solid mechanical structure, stable reliability and the effectiveness of intelligent control algorithms of the intelligent robotic walker. © 2023 IEEE.

关键词： Walking aids

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Ultra-wideband Frequency Selective Surface for Communication Applications

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computers, Materials & Continua 2022年第3期70卷 6177-6187页

作者： Shahid Habib Ghaffer Iqbal Kiani Muhammad Fasih Uddin Butt Syed Muzahir Abbas Abdulah Jeza Aljohani Soon Xin Ng Department of Electrical and Computer Engineering COMSATS University IslamabadIslamabad45550Pakistan Department of Electrical and Computer Engineering King Abdulaziz UniversityJeddahKingdom of Saudi Arabia School of Electronics and Computer Science University of SouthamptonSouthamptonSO171BJUK School of Engineering Faculty of Science and EngineeringMacquarie UniversitySydneyNSW2109Australia BENELEC BotanySydneyNSW2019Australia

A low-profile ultra-wideband(UWB)band-stop frequency selective surface(FSS)is designed for S-,C-,X-and Ku-bands communication *** FSS is constructed by using square and circular loop elements printed on the top and bottom sides of the RO3210 *** FSS has been designed to reduce the electromagnetic interference(EMI)as well as to mitigate the harmful effects of electromagnetic radiation on the human body caused by different radio *** dimension and size of the UWB FSS have been reduced to 0.12λ×0.12λand 90%,respectively,as compared to the reported *** other advantages of the proposed FSS are that it is low profile,it has a simplified geometry and it ensures better angular and polarization stability of up to 85◦.The-10 and-20 dB bandwidths of the proposed FSS are 146%(2.0-13.0 GHz)and 80%(4.87-11.42 GHz),*** results have been obtained using ANSYS HFSS and verified through measured results.

关键词： Electromagnetic radiation fractional bandwidth polarization transverse electric transverse magnetic

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Performance Estimation of Pattern Matching Algorithms Employing DNA Sequence

Performance Estimation of Pattern Matching Algorithms Employ...

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2024 IEEE International Conference on Signal Processing and Advance Research in Computing, SPARC 2024

作者： Khanna, Pooja Neelam Manohar Pragya Tiwari, Kumud Amity University Lucknow Department of Computer Science & Engineering Lucknow India Chaudhary Devi Lal University Department of Computer Science & Engineering Sirsa India Amity University Lucknow Amity School of Engineering & Technology Department of Computer Science & Engineering Lucknow India University of Lucknow M VD College Department of Chemistry Lucknow India Lovely Professional University School of Electronics and Electrical Engineering India

ISBN: (纸本)9798350385199

The Internet is evolving, with huge amounts of data being generated and stored in terabytes and petabytes. These data contain enormous amounts of information if processed accordingly. In today's era Information is the oil of the 21st century and analytics is the combustion engine. Analytics on data can be stored in the form of strings. Any string generated has a pattern, analyzing these patterns is the most important thing in this era of information. The information that is stored in a genome database that has been collected over the years from all over the world can be brought to some good use if there is proper analysis done on it. This information can be utilized by a thorough analysis on the sequencing of DNA (De-Oxy-Ribonucleic Acids). DNA is a molecule which stores all the information regarding the development, growth and reproduction of all known living organisms. This simple information can be used to our advantage. The work here compares some of the string pattern-based Algorithms for a real-life application of DNA Sequencing, this pattern matching will be done through the genome database. KMP, Naïve search, BM algorithm, Rabin Karp, Z-Algorithm are few algorithms compared. As the conclusion of work, it is being analyzed comparing the searching complexity of these algorithms that, Algorithms have distinct advantages depending upon the use. The choice of the algorithm could depend upon various other factors including length of the string and the pattern, the type of data, and kind of operations that must be performed. By understating the performance requirements, availability of data, the researcher or the user must make smart choices to choose an appropriate algorithm for their pattern matching tasks. The study here also concludes that KMP is better in terms of matching time for a DNA sequencing application. © 2024 IEEE.

关键词： Gene encoding

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IoT Based Smart Framework Monitoring System for Power Station

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computers, Materials & Continua 2023年第3期74卷 6019-6037页

作者： Arodh Lal Karn Panneer Selvam Manickam R.Saravanan Roobaea Alroobaea Jasem Almotiri Sudhakar Sengan Department of Financial and Actuarial Mathematics School of ScienceXi’an Jiaotong-Liverpool UniversityChina Department of Electrical and Electronics Engineering Sona College of TechnologySalem636005Tamil NaduIndia Department of Computer Science and Engineering Vel Tech Multi Tech Dr RR Dr SR Engineering CollegeChennai600062Tamil NaduIndia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Computer Science and Engineering PSN College of Engineering and TechnologyTirunelveli627152Tamil NaduIndia

Power Station(PS)monitoring systems are becoming critical,ensuring electrical safety through early warning,and in the event of a PS fault,the power supply is quickly *** technologies are based on relays and don’t have a way to capture and store user data when there is a *** proposed framework is designed with the goal of providing smart environments for protecting electrical types of *** paper proposes an Internet of Things(IoT)-based Smart Framework(SF)for monitoring the Power Devices(PD)which are being used in power substations.A Real-Time Monitoring(RTM)system is proposed,and it uses a state-of-the-art smart IoT-based System on Chip(SoC)sensors,a Hybrid Prediction Model(HPM),and it is being used in Big Data Processing(BDP).The Cloud Server(CS)processes the data and does the data analytics by comparing it with the historical data already stored in the ***-Structural Query Language Mongo Data Base(MDB)is used to store Sensor Data(SD)from the *** proposed HPM combines the Density-Based Spatial Clustering of Applications with Noise(DBSCAN)-algorithm for Outlier Detection(OD)and the Random Forest(RF)classification algorithm for removing the outlier SD and providing Fault Detection(FD)when the PD isn’t *** suggested work is assessed and tested under various fault circumstances that happened in *** simulation outcome proves that the proposed model is effective in monitoring the smooth functioning of the ***,the suggested HPM has a higher Fault Prediction(FP)*** means that faults can be found earlier,early warning signals can be sent,and the power supply can be turned off quickly to ensure electrical safety.A powerful RTM and event warning system can also be built into the system before faults happen.

关键词： System-on-chip cloud server apache kafka apache strom NoSQL MongoDB

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Development of Area-Based Explosive Trace Detection Using Deep Transfer Learning 1

Development of Area-Based Explosive Trace Detection Using De...

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1st International Conference on Innovative engineering sciences and Technological Research, ICIESTR 2024

作者： Ohemu, Monday F. Azeta, Ambrose A. Adeyanju, Ibrahim A. Obasi, Chukwuemeka C. Airforce Institute of Technology Department of Electrical/Electronics Engineering Kaduna Nigeria Namibia University of Science and Technology Department of Software Engineering Namibia Federal University Department of Computer Engineering Oye-Ekiti Nigeria Edo State University Department of Computer Engineering Uzairue Nigeria

ISBN: (纸本)9798350348637

Terrorism poses a significant global threat, necessitating comprehensive security measures to protect people and critical infrastructure. With the increasing frequency of explosive-based attacks, there is a pressing need for advanced detection systems to mitigate potential devastation. This paper presents the development of an area-based explosive trace detection system using deep transfer learning. Leveraging deep learning technology trained on a substantial dataset collected from sensor networks, the proposed model, named Deep Transfer Learning for Explosive Trace Detection (DTLETD), demonstrates remarkable capabilities in classifying explosive gases based on concentrations of Carbon (C), Hydrogen (H), Oxygen (O), and Nitrogen (N). The methodology involves converting the dataset into 2D data using a serial data to image generator, followed by the adaptation of a pre-trained model for transfer learning. The DTLETD model outperformed conventional Convolutional Neural Network (CNN) models, achieving a training time reduction of about 92 seconds compared to 1287 seconds for the CNN model. Additionally, the transfer learning model exhibits faster convergence with nearly zero losses during training and validation, yielding an impressive accuracy of 99.7% and an average AUC value of approximately 0.89. This research significantly advances the field of explosive trace detection by integrating machine learning-based approaches with deep transfer learning techniques, thereby enhancing security protocols and mitigating potential threats. © 2024 IEEE.

关键词： Convolutional neural networks

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A Comprehensive Evaluaion of Solar Powered Electric Vehicle Charging Station Design Using Internet of Things 1

A Comprehensive Evaluaion of Solar Powered Electric Vehicle ...

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1st International Conference on electronics, Communication and Signal Processing, ICECSP 2024

作者： Chitra, K. Gnanasekar, A. Ravi, C.N. Jaisudha, J. Ramya, R. Jithendar, P. CMR Institute of Technology Department of Electrical and Electronics Engineering Karnataka Bengaluru India R.M.D. Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India CMR Engineering College Department of Computer Science and Engineering Hyderabad Medchal India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Nano Electronics Materials and Sensors Tamil Nadu Chennai India MLR Institute of Technology Department of Electrical and Electronics Engineering Hyderabad India

ISBN: (纸本)9798350364590

More than 1.3 million electric vehicles have been installed throughout the globe, and public charging networks for these vehicles are becoming increasingly common. It has been an area of interest to establish a plan for prioritizing the charging of electric vehicles (EVs) from a single network. This is particularly important in situations when the power source is restricted, such as with renewable energy, and for economic reasons (a higher price per KWh for quicker charging). When used in conjunction with electric vehicle (EV) charging, solar energy significantly decreases our reliance on fossil fuels. An electric car solar charger is created and constructed inside this system. In order to maximize the output from the solar panels, a dc-dc boost converter is used to transfer the voltage from the panels to the station's batteries. Maximum Power Point Tracking (MPPT) is also included. Power the charging station with energy from the solar panels so that the vehicle's rechargeable battery may be charged. The charging station's status can be monitored at any time via the Internet of Things. We have created a solar-powered charging station to provide simple accessibility. Solar power is both a sustainable and accessible renewable energy source. Arduino controller for light-dependent resistor (LDR) light intensity monitoring, solar cell energy observation, battery charging, and cloud storage. The core idea behind the article is the IoT Solar Charging Station (IoTSCS), and it is tested by comparing it to the Classical Solar Charging Station (CSCS), a more traditional scheme, in order to see how well the new scheme works. © 2024 IEEE.

关键词： Charging stations

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Characteristic Mode Analysis of Wideband Patch Antenna Using Dual-Mode Resonance 5

Characteristic Mode Analysis of Wideband Patch Antenna Using...

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5th IEEE Global Conference for Advancement in Technology, GCAT 2024

作者： Vinaya Kumar, S.R. Venkatesh, T. Rajanna, Puneeth Kumar Tharehalli Ghousia College of Engineering Dept. of Electrical and Electronics Engineering Karnataka Ramanagara India Ghousia College of Engineering Dept. of Computer Science Engineering Karnataka Ramanagara India Siddaganga Institute of Technology Dept. of Electronics and Telecommunication Engg Karnataka Tumkur India

ISBN: (纸本)9798350376685

This paper presents the characteristic mode analysis(CMA) of wideband patch antenna using dual-mode resonances. CMA is used to analyze the fundamental resonance modes of square patch antenna. It has two fundamental modes of TM01 and TM10 modes. The patch is excited using aperture coupling to excite both horizontal and vertical mode. The slot aperture length and width is optimized for better coupling. The vertical mode resonance frequency is slightly reduced by introducing the slot. These two modes combined together gives the wide bandwidth. An impedance bandwidth of 47.12%(1.93GHz-3.12GHz) is obtained. The antenna is well radiated with both modes being radiation efficiency of above 90%. The realized peak gain of 5.72dBi and 4.62dBi is obtained at 2.12GHz and 2.83GHz and good radiation pattern in the broadside direction. The cross polarization level of more than -10dB is achieved with respect to co-polarization level at resonance frequency of 2.12GHz and 2.83GHz respectively and it is suitable for WiFi and Bluetooth applications. © 2024 IEEE.

关键词： Slot antennas

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engineering Framework for Smart Poultry Farming Using Internet of Things

Engineering Framework for Smart Poultry Farming Using Intern...

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2024 International Conference on Intelligent and Innovative Practices in engineering and Management, IIPEM 2024

作者： Manju, K. Dinesh, P.M. Deepa, K. Kathan, Karthik Lakshmi, G. Prasanna Alagarsamy, Manjunathan Sona College of Technology Department of Electronics and Communication Engineering Tamil Nadu Salem India SRM Institute of Science and Technology Faculty of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Tiruchirapalli India Kongunadu College of Engineering and Technology Department of Electrical and Electronics Engineering Tamil Nadu Trichy621215 India Sandip University School of Computer Science and Engineering Maharashtra Nashik India K.Ramakrishnan College of Technology Department of Electronics and Communication Engineering Tamil Nadu Trichy621112 India

ISBN: (纸本)9798350390049

Automation is more important now. This article focuses on automating chicken farms using mobile communication devices and wireless sensor networks. Chicken is the world's most popular food because it contains more protein, less fat, and less cholesterol than other poultry. Chicken's nutrition is another benefit. This project utilizes the Internet of Things to monitor and adjust chicken farm environmental conditions. Temperature, moisture, water level, ammonia gas, and waste level were considered. This research aimed to improve chicken farm chick growth. The individual also monitors chicken behavior and feeding. Another usage for the sensor module is water level management and monitoring. If all sensors are connected to the microcontroller, all sensor data may be gathered. After that, a Wi-Fi module uploads the data to a website. A computer or mobile device connected to the internet allows the poultry farm owner to examine its interior surroundings. This informs the owner on agricultural conditions. This system will maintain temperature, humidity, and water level without human intervention using a DC motor, ventilation window, and co-exhaust fan. This will be done without human intervention. Devices will activate as needed when threshold values are attained. Our method allows semi-automated chicken product production and bird behavior monitoring. This allows us to deliver nutritious chicken meat while reducing bird killing. © 2024 IEEE.

关键词： Humidity sensors

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