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

作者： Dalal, Riya Randhawa, Simrat Kaur Modi, Shrey Vishwakarma, Rahul Adani Institute of Infrastructure Engineering Department of Information and Communication Technology Ahmedabad India California State University Long Beach Department of Computer Engineering and Computer Science Long Beach United States California State Uni. Long Beach Department of Computer Engineering and Computer Science Long BeachCA United States

ISBN: (纸本)9798350393415

Geolocation refers to the identification of the geographic location of a user or computing device via a variety of data collection mechanisms. The proposed system aims to enable accurate and efficient localization of objects within a given environment. Traditional positioning systems often rely on GPS or other sensor-based technologies, which may face limitations in indoor or highly cluttered environments. To overcome these challenges, our approach leverages the power of CBIR, which involves matching query images with a pre-existing database of reference images. By extracting key features from images and employing Annoy, a fast approximate nearest neighbor library, we achieve efficient retrieval and comparison of images. The extracted features act as robust descriptors, enabling accurate positioning of objects based on visual similarities. This research contributes to the advancement of positioning systems by introducing a novel methodology that combines CBIR, Annoy, and feature extraction techniques, offering a promising solution for accurate object localization in challenging *** dataset that has been is used is gathered by the authors and the dataset plays a crucial role in position mapping, enabling accurate and context-Aware positioning within a given *** results demonstrate the effectiveness of the proposed position system, as it achieves high accuracy and real-Time performance. This research contributes to the advancement of positioning systems by introducing a novel methodology that combines CBIR, Annoy, and feature extraction techniques, offering a promising solution for accurate object localization in challenging environments. © 2023 IEEE.

关键词： Nearest neighbor search

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Energy efficient indoor localisation for narrowband internet of things

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CAAI Transactions on Intelligence technology 2023年第4期8卷 1150-1163页

作者： Ismail Keshta Mukesh Soni Mohammed Wasim Bhatt Azeem Irshad Ali Rizwan Shakir Khan Renato RMaaliw III Arsalan Muhammad Soomar Mohammad Shabaz Computer Science and Information Systems Department College of Applied SciencesAlMaarefa UniversityRiyadhSaudi Arabia Department of CSE University Centre for Research and Development Chandigarh UniversityMohaliPunjabIndia Department of Computer Science and Engineering National Institute of TechnologySrinagarIndia Asghar Mall College Rawalpindi Higher Education Department(HED)Govt.of the PunjabRawalpindiPakistan Department of Industrial Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddahSaudi Arabia College of Computer and Information Sciences Imam Mohammad Ibn Saud Islamic University(IMSIU)RiyadhSaudi Arabia College of Engineering Southern Luzon State UniversityLucbanQuezonPhilippines Department of Automation Electronics and Electrical EngineeringGdansk University of TechnologyGdańskPoland Arba Minch University Arba MinchEthiopia

There are an increasing number of Narrow Band IoT devices being manufactured as the technology behind them develops *** high co‐channel interference and signal attenuation seen in edge Narrow Band IoT devices make it challenging to guarantee the service quality of these *** maximise the data rate fairness of Narrow Band IoT devices,a multi‐dimensional indoor localisation model is devised,consisting of transmission power,data scheduling,and time slot scheduling,based on a network model that employs non‐orthogonal multiple access via a *** on this network model,the optimisation goal of Narrow Band IoT device data rate ratio fairness is first established by the authors,while taking into account the Narrow Band IoT network:The multidimensional indoor localisation optimisation model of equipment tends to minimize data rate,energy constraints and EH relay energy and data buffer constraints,data scheduling and time slot *** a result,each Narrow Band IoT device's data rate needs are met while the network's overall performance is *** investigate the model's potential for convex optimisation and offer an algorithm for optimising the distribution of multiple resources using the KKT *** current work primarily considers the NOMA Narrow Band IoT network under a single EH ***,the growth of Narrow Band IoT devices also leads to a rise in co‐channel interference,which impacts NOMA's performance *** simulation,the proposed approach is successfully *** improvements have boosted the network's energy efficiency by 44.1%,data rate proportional fairness by 11.9%,and spectrum efficiency by 55.4%.

关键词： artificial inteligence detection of moving objects internet of things

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Political Optimizer with Deep Learning-Enabled Tongue Color Image Analysis Model

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computer systems science & Engineering 2023年第5期45卷 1129-1143页

作者： Anwer Mustafa Hilal Eatedal Alabdulkreem Jaber S.Alzahrani Majdy M.Eltahir Mohamed I.Eldesouki Ishfaq Yaseen Abdelwahed Motwakel Radwa Marzouk Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMecca24382Saudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversityAbha62529Saudi Arabia Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Mathematics Faculty of ScienceCairo UniversityGiza12613Egypt

Biomedical image processing is widely utilized for disease detection and classification of biomedical *** color image analysis is an effective and non-invasive tool for carrying out secondary detection at anytime and *** removing the qualitative aspect,tongue images are quantitatively inspected,proposing a novel disease classification model in an automated way is *** article introduces a novel political optimizer with deep learning enabled tongue color image analysis(PODL-TCIA)*** presented PODL-TCIA model purposes to detect the occurrence of the disease by examining the color of the *** attain this,the PODL-TCIA model initially performs image pre-processing to enhance medical image *** by,Inception with ResNet-v2 model is employed for feature ***,political optimizer(PO)with twin support vector machine(TSVM)model is exploited for image classification process,shows the novelty of the *** design of PO algorithm assists in the optimal parameter selection of the TSVM *** ensuring the enhanced outcomes of the PODL-TCIA model,a wide-ranging experimental analysis was applied and the outcomes reported the betterment of the PODL-TCIA model over the recent approaches.

关键词： Tongue color image analysis political optimizer twin support vector machine inception model deep learning

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Design of Control system for Simulation Training Device of Urban Rail Trains 5

Design of Control System for Simulation Training Device of U...

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5th Asia-Pacific Conference on Image Processing, Electronics and computers, IPEC 2024

作者： Chen, Xiaoxia Xue, Xu Wang, Lin Chaudhry, Shehzad Ashraf School of Automation and Electrical Engineering Dalian Jiaotong University Dalian China Department of Computer Science and Information Technology College of Engineering Abu Dhabi University United Arab Emirates

ISBN: (纸本)9781643685243

With the rapid development of urban rail transit across the country, the industry has put forward higher requirements for quickly cultivating high-quality train drivers, maintenance personnel, and drivers. Therefore, the development of a highly simulated urban rail train simulation training device is of great significance. Compared to traditional dedicated industrial networks, industrial Ethernet has larger bandwidth, lower cost, and better scalability. This has made industrial Ethernet widely used in various industrial fields, further improving production efficiency and reducing operating costs. This article uses industrial Ethernet PROFINET to replace the twisted train bus WTB and multi-functional vehicle bus MVB communication of actual trains, and designs a cost-effective control system for urban rail train simulation training equipment. Detailed introduction was provided on equipment selection, hardware configuration, PROFINET master slave station control program, Ethernet communication program between master station and other CPUs, human-machine interaction interface, etc. Provide efficient and economical solutions for training and simulation operations of rail vehicles. © 2024 The Authors.

关键词： Operating costs

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Multi Face Detection Based Attendance system 23th

Multi Face Detection Based Attendance System

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23rd International Conference on Intelligent systems Design and Applications, ISDA 2023

作者： Prasanna Kumar, K.R. Madhumitha, S. Madhushree, S. Vijiishwarya, M. Logeswaran, K. Devendran, K. Department of Information Technology Kongu Engineering College Perundurai India Department of Artificial Intelligence Kongu Engineering College Perundurai India Department of Computer Science and Engineering Kongu Engineering College Perundurai India

ISBN: (纸本)9783031646492

Face recognition-based data driven solutions are used to solve many real-time problems in day-to-day life. At present some of the known methods like physical presence verification, Id card scanning system and single face system are used in attendance marking purpose. The existing system often focuses on single face detection which consumes more time. Moreover, they do not address the challenges like bulk entry of individuals at a point of time. This limitation hinders their effectiveness in scenarios where multiple faces need to be detected simultaneously in crowded entry and exits like hostels, library, and apartment and so on. This proposed system is designed to detect and track multiple faces simultaneously from the live video streams. Additionally, it includes a time stamping mechanism that records the exact time when each face is captured. Also, it records the unknown faces with entry and exit time details which helpful to trace the people at later point of time. The proposed solution is applied to track the movements in entry and exit points of the Hostel also supports to monitor the unauthorized movements inside the hostel. The unauthorized person movement records help to enhance their security. So, it eliminates the manual attendance marking and speed up the overall process. The proposed real-time multiple face detection system fills this gap by introducing advanced algorithms like haarcascade and innovative features. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Face recognition

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Modeling and Verification for CPS Space- Time Safety 4

Modeling and Verification for CPS Space- Time Safety

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4th International Conference on Frontiers technology of information and computer, ICFTIC 2022

作者： Ye, Zhen Zhu, Yi Wang, JinYong Chen, Xiao Ying College of Computer Science and Technology Jiangsu Normal University Xuzhou China School of Information Engineering Xuzhou University of Technology Xuzhou China Nanjing University Department of Computer Science and Technology Nanjing China

ISBN: (纸本)9798350321951

Cyber-physical systems (CPS) operate in open and uncertain physical spaces. In space-time related safety-critical software, how to quantify system performance and safety, model and verify the credibility of CPS has become a hot topic. Aiming at this problem, a Modeling and verification method for CPS space-time safety is proposed. Firstly, extend the space-time attributes and probability attributes of Architecture Analysis & Design Language (AADL) behavior annex, and propose the Safety Probability Architecture Analysis & Design Language (SP-AADL), which is used to model the space-time behavior of CPS systems with safety probabilities;Secondly, extend the space and probability properties of the process algebra-Time Communicating Sequential Process (TCSP), and propose Space Probability Time Communicating Sequential Process (SP- TCSP);Thirdly, the probability parameters are obtained by quantifying the state safety of the system through the statistical model test;Finally, by defining the model transformation rules, the SP-AADL model is transformed into the SP- TCSP model for formal verification, which proves the effectiveness of the method. © 2022 IEEE.

关键词： Formal verification

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Exploring the Capabilities of Graph Convolutional Networks for Cardiac Arrest Prediction 5th

Exploring the Capabilities of Graph Convolutional Networks f...

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Rahman, J. Riyazulla Agarwal, Trapty Nachappa, M.N. Mehra, Ritika School of Information Science Presidency University Karnataka Bengaluru India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India Department of Computer Science & Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India

ISBN: (纸本)9789819780426

Graph convolutional networks (GCNs) had been advanced to study representations of graph-based records. This paper presents a novel approach to predicting cardiac arrest the use of GCNs on observational information from a nationwide clinical registry. The model combines demographic records (age, intercourse, comorbidities, and many others.), previous admissions to hospitals, and historic essential signs and symptoms. The resulting model’s performance became as compared towards conventional system-learning techniques the usage of receiver running characteristics and go-validation. Outcomes reveal that the GCN correctly predicts cardiac arrest occasions with a place below & the curve of zero. Seventy seven. Moreover, the GCN outperforms traditional device-mastering methods inclusive of logistic regression, random woodland, and gradient boosting. This has potential implications for actionable interventions for danger-discount and aid-allocation planning for healthcare systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Decision trees

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Anomaly-Based Intrusion Detection system in WSN using DNN Algorithm 1

Anomaly-Based Intrusion Detection System in WSN using DNN Al...

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1st International Conference on Emerging Technologies for Dependable Internet of Things, ICETI 2024

作者： Al-Fuhaidi, Belal Farae, Zainab Al-Sorori, Wedad Maqtary, Naseebah Al-Ashmoery, Yahya Al-Fuhaidy, Farouk Al-Taweel, Sadik Faculty of Computing and IT University of Science and Technology Sana’a Yemen Department of IT Al-Razi University Sana’a Yemen Dept. Mathematics & Computer Faculty of Science Sana’a University Sana’a Yemen Department of Electrical Engineering Faculty of Engineering Ibb University Ibb Yemen

ISBN: (纸本)9798331533557

Intrusion detection systems (IDSs) are a necessary principle in WSN security, which can successfully prevent various hackers' and intruders' attempts to hack the network. In this research, we address the problem of achieving high accuracy in detecting intrusions in WSNs due to specific characteristics of WSN data, including the appropriate dataset, the drawbacks of feature selection, and choosing the proper algorithms for the classification process. In this paper, we proposed the anomaly-based IDS model using the DNN algorithm and mutual information (MI) technology to select features. The proposed model has been implemented using the Python language used in the Anaconda platform and relying on the standard NSL-KDD dataset. The experimental results showed the capability of the proposed model to achieve high-performance accuracy in intrusion detection using the DNN algorithm compared to the state-of-the-art. The proposed model outperforms other previous relevant works by 3.65% enhancement in terms of accuracy. © 2024 IEEE.

关键词： Network intrusion

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AI based Real-Time Traffic Signal Control system using Machine Learning 4

AI based Real-Time Traffic Signal Control System using Machi...

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4th International Conference on Electronics and Sustainable Communication systems, ICESC 2023

作者： Heltin Genitha, C. Abishek Danny, S. Hepsi Ajibah, A.S. Aravint, S. Angeline Valentina Sweety, A. St. Joseph's College of Engineering Department of Information Technology Chennai India St. Joseph's Institute of Technology Department of Computer Science and Engineering Chennai Chennai India

ISBN: (纸本)9798350300093

This study presents a novel system that utilizes computer vision and machine learning approaches to address the problem of traffic congestion in urban areas. The proposed system leverages the advanced object detection algorithm, You Only Look Once (YOLO), to detect and track vehicles in live camera footage from traffic junctions. The system then calculates the traffic density in real-time by analyzing the number and speed of vehicles passing through the intersection. The proposed system utilizes an intelligent algorithm that optimizes traffic flow by switching traffic lights based on the calculated traffic density. This approach reduces congestion and minimizes delays, resulting in faster transit times and reduced fuel consumption and air pollution. To assess the performance of the proposed system, experiments are carried on real-world traffic data. The results demonstrate that the system can accurately detect and track vehicles with high precision and recall rates. The real-time traffic density calculations produced by the system were found to be highly reliable, and the traffic light switching algorithm led to a significant reduction in traffic congestion and improved traffic flow. The proposed system has several advantages over traditional traffic management systems, including lower implementation and maintenance costs, improved accuracy and efficiency, and the ability to adapt to changing traffic conditions in real-time. © 2023 IEEE.

关键词： Object detection

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Enabling Robust Security in MQTT-Based IoT Networks with Dynamic Resource-Aware Key Sharing

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Procedia computer science 2025年 252卷 633-642页

作者： Sharadadevi Kaganurmath Nagaraj Cholli Department of Computer Science Engineering Global Academy of Technology Bengaluru India Department of Information Science Engineering RV College of Engineering Bengaluru

This paper presents a novel approach aimed at developing a secure secret key-sharing system optimized for resource-constrained Internet of Things (IoT) devices. Focusing on the MQTT protocol, the research endeavors to establish secure communication channels between IoT devices and brokers, thereby enhancing the overall security of MQTT-based IoT deployments. This research introduces a novel Dynamic Lightweight Authentication for MQTT (DLA-MQTT) mechanism designed to the unique needs of IoT devices operating under the MQTT protocol. The DLA-MQTT mechanism leverages an innovative lightweight Generalized Feedback Shift Register (GFSR)-based Pseudo-Random Number Generator (PRNG) to generate ephemeral keys, ensuring secure communication while addressing the limitations of computational power and energy resources. Through a detailed comparative analysis with existing cryptographic solutions, the DLA-MQTT mechanism demonstrates superior performance in terms of computational overhead, energy consumption, and execution time, while maintaining robust security against common attacks such as Man-in-the-Middle (MitM) and Denial of Service (DoS). he proposed algorithm’s adaptability and scalability are validated using the Cooja simulator, where simulated IoT networks are subjected to various threat scenarios. The results confirm the DLA-MQTT mechanism’s efficacy, showcasing a significant reduction in resource utilization without compromising the strength of the security provided.

关键词： Internet of Things(IoT) Message Queuing Telemetry Transport (MQTT) Lightweight Cryptography Resource-Constrained Devices Security Pseudo-Random Number Generator Generalised feedback Shift Register (GFSR) Ephemeral Key Generation

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