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Military Vehicle Object Detection Based on Feature Representation and Refined Localization Using Inception Recurrent Convolutional Neural Network 2

Military Vehicle Object Detection Based on Feature Represent...

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2nd International Conference on Distributed Computing and Optimization Techniques, ICDCOT 2024

作者： Almusawi, Muntather Yadav, S. G. Shivaprasad Rahim, Abdul Aluvala, Srinivas Ramachandra, A.C. The Islamic University Najaf Iraq Electronics and Telecommunication Engineering Ramaiah Institute of Technology Bangalore India Electronics and Communication Engineering Department Telangana Hyderabad India School of Computer Science and Artificial Intelligence Sr University Warangal India Nitte Meenakshi Institute of Technology Department of Ece Bengaluru India

ISBN: (纸本)9798350382952

Advanced reconnaissance technologies for military vehicle components form basis for weapons and equipment reconnaissance and tracking operations in complex environments, which is crucial to allow intelligent warfare using information. Addressing limitations of conventional detection algorithms in this domain, a novel approach termed as Military Vehicle Object Detection Method based on Inception Recurrent Convolutional Neural Network (MVODM-IRCNN) and Hierarchical Feature Representation is proposed for detecting military vehicle object. first is a comprehensive data set specially designed for military vehicles. Then it is two system improvements: hierarchical feature representation and state-of-the-art localization, using Inception Recurrent Convolutional Neural Network (IRCNN), aimed at improving detection performance. Hierarchical feature representation techniques make it easier to find good feature representation levels for different object shapes, improving accuracy of these techniques boxes. combination of materials provides a significant gain in detector performance. Finally, an exploratory study conducted on own dataset shows that MVODM-IRCNN has exceptional recognition capabilities, which proves its usefulness in military vehicle recognition applications. © 2024 IEEE.

关键词： Object detection

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A Novel Blockchain-Based Strategy for Energy Conservation in Cognitive Wireless Sensor Networks 4

A Novel Blockchain-Based Strategy for Energy Conservation in...

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4th International Conference on Blockchain Technology and Information Security, ICBCTIS 2024

作者： Sharma, Khemraj Goyal, Rohit Bhagat, Sukesh Kumar Agarwal, Sheenu Bisht, Girish Singh Hussien, Mohemmed Nanhua University Department of Business Administration Doctoral Program in Management Sciences Dalin62248 Taiwan School of Engineering and Computing Dev Bhoomi Uttarakhand University Dehradun India Uttaranchal University Department of Computer Science & Engineering Dehradun India Uttarakhand Technical University Department of Electronics and Communication Engineering Dehradun India Tula's Institute Dehradun India Department of Computer Science and Engineering Dehradun248001 India The Islamic University Najaf Iraq

ISBN: (纸本)9798331528324

Internet of Things (IoT) industrial applications have increased in internet-connected devices. As a result, accessibility, scalability, connectivity, and adaptability have become major challenges. It is possible to create connections between loT devices over the wireless medium, but efficiently utilizing scarce spectrum is the biggest concern. The paper proposes a novel method for selecting sensing nodes with the goal of reducing energy usage and increasing sensing efficiency. In order to ensure that node trust values conform to each other without any ambiguity, cryptography encrypts all information that relates to a node in a central node (CN). Nodes participating in CSS are selected based on their performance. Based on a comparison of various algorithms using varying numbers of nodes, the proposed algorithm achieves a 10% sensing efficiency. © 2024 IEEE.

关键词： Blockchain Network Network Communication security Wireless Sensor

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An Enhanced Routing Protocol Design to Perform Cost Efficient Data Communication over Wireless Sensor Networks 3

An Enhanced Routing Protocol Design to Perform Cost Efficien...

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3rd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Jadhav, Dattatraya Arun Suneel, Sajja Begum, M. Amina Ghogare, Meghana Harsh Murri, Madhan Sekhar Vadar, Parashuram Shankar Keystone School of Engineering Electronic and Telecommunication Department pune India Telangana Hyderabad500043 India Oxford College of Engineering Department of Ece Tamilnadu Venmani India Parul University ByteXL-Department of Computer Science and Engineering Vadodara India Department of Management Studies AP India Shivaji University Yashwantrao Chavan School of Rural Development Maharashtra Kolhapur India

ISBN: (纸本)9798350375190

This research introduces a groundbreaking approach to address the challenges of cost-efficient data communication in Wireless Sensor Networks (WSNs) through the development of a novel routing protocol named Cost-Efficient Enhanced Routing Protocol (CEERP). WSNs, characterized by resource-constrained sensor nodes and dynamic environmental conditions, necessitate innovative routing strategies to optimize energy consumption and enhance overall network performance. CEERP leverages a sophisticated methodology that integrates Energy Consumption Modeling, Adaptive Routing Decisions, alongside Optimization and Fine-Tuning. The Energy Consumption Modeling method systematically analyzes various factors influencing energy dynamics in sensor nodes, facilitating the creation of accurate mathematical models. These models inform CEERP's routing algorithm, enabling intelligent decisions based on predicted energy consumption patterns. The protocol adapts dynamically to real-time variations in network conditions, ensuring responsiveness to changing environmental factors. Implementation and Simulation validate CEERP's performance in diverse scenarios, while Optimization and Fine-Tuning finetune parameters for optimal efficiency. Security and reliability measures are integrated to safeguard data integrity. The research concludes with a comprehensive evaluation of CEERP's effectiveness, positioning it as a promising solution for achieving cost-efficient and reliable data communication in WSNs. The proposed methodology and CEERP contribute to the advancement of routing protocols for WSNs, offering a holistic and adaptive approach to address the unique challenges posed by resource-constrained environments. © 2024 IEEE.

关键词： Routing protocols

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Meal Image Recognition and Healthy Meal Combination Recommendation System Integrated with Generative Artificial Intelligence 6

Meal Image Recognition and Healthy Meal Combination Recommen...

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6th IEEE Eurasia Conference on Biomedical engineering, Healthcare and Sustainability, ECBIOS 2024

作者： Chang, Chin-Chih Wei, Chi-Hung Hsiao, Sean Yang, Chyuan-Huei Thomas Chung Hua University Department of Computer Science and Information Engineering Hsinchu Taiwan Chung Hua University Ph.D. Program in Engineering Science Hsinchu Taiwan Chung Hua University Program in Applied Foreign Language and Smart Commerce Hsinchu Taiwan School of Information Engineering Shandong Vocational and Technical University of International Studies Shandong China

ISBN: (纸本)9798350396133

People increasingly prioritize a balanced diet to enhance well-being, yet making informed dietary choices remains challenging amidst the abundance of options. To address this, we developed a meal image recognition and healthy meal combination recommender system, integrating generative artificial intelligence (AI). Convolutional neural networks were used for precise meal image recognition to identify diverse food items. The generative AI-augmented recommendation engine offers personalized meal suggestions aligned with nutritional goals and dietary preferences, utilizing a nutrition knowledge base to ensure overall well-being. The system's feasibility was validated, illustrating its excellence in meal recognition accuracy, recommendation diversity, and user engagement. By integrating generative AI, the system shows its potential to enhance dietary recommendations and public health. © 2024 IEEE.

关键词： Generative adversarial networks

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Prediction of Cardiovascular Disease Risk in the General Population: A GSA-ELM Approach 1

Prediction of Cardiovascular Disease Risk in the General Pop...

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1st IEEE International Conference on Electronics, Computing, Communication and Control Technology, ICECCC 2024

作者： Lohbare, Sonali Pakhmode Noor Alleema, N. Praveena, S. Patil, Harshal Rajalakshmi, S. Lakineni, Prasanna Kumar Raisoni University Amravati VPPCOE & VA Department of Electronics and Telecommunication Soin Mumbai India Thandalam Department of CSE Chennai India Mahatma Gandhi Institute of Technology Gandipet Department of ECE Telangana Hyderabad India Department of CSE Maharashtra Pune India RMK College of Engineering and Technology Department of Electronics and Communication Engineering Chennai India Sri Venkateswara College of Engineering Department of Computer Science & Engineering Tirupathi India

ISBN: (纸本)9798350371802

Medical treatment is a need since it ensures our continued existence as a species. Conditions affecting the heart and blood arteries are collectively known as cardiovascular disease. Decisions regarding the appropriate medicines for people at high risk for cardiovascular disease were informed by early methods of illness prediction. Machine learning algorithms are crucial for creating reliable forecasts of cardiac problems because of the abundance of available health care data. The proposed method is based on three primary phases: preprocessing, feature extraction, and model training. To lessen the impact of distracting noise, HD statistics use filtering and de-noising during the preprocessing phase. In order to extract features, the gray-level Co-Occurrence Matrix is employed. Next, GSA-ELM models are trained based on the retrieved characteristics. Compared to GSA and ELM, the two most popular alternatives, the suggested technique is better. They were able to reach a maximum accuracy of 95.74% by implementing the suggested technique. © 2024 IEEE.

关键词： Forecasting

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Morse Code Based Two-Way Communication Device for Visually Impaired and Mute 3

Morse Code Based Two-Way Communication Device for Visually I...

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3rd IEEE International Conference on Device Intelligence, Computing and Communication Technologies, DICCT 2025

作者： Marathe, Abha Bawanthade, Snehal Bele, Rohit Bhagwat, Nidhi Bhurke, Avinash Vishwakarma Institute of Technology Department of Electronics and Telecommunication Engineering Pune India Vishwakarma Institute of Technology Department of Computer Science Engineering Pune India

ISBN: (纸本)9798331543358

People with disabilities like visual and speech impairments face significant challenges in interacting and communicating with others because conventional tools like smartphones are predominantly visual and verbal based. Consequently, such individuals depend on others even to convey simple messages. These problems restrict their ability to express themselves freely. Moreover, existing assistive technologies are complex and expensive making them impractical choice for widespread use. This project presents an innovative solution to overcome these obstacles: a Morse-code-based device that operates on a single-button interface thus making it extremely useful for people who can't see. This IOT-based device translates Morse code signals into text which is further displayed on mobile devices. Additionally, the message logs are preserved on cloud storage thus ensuring convenience and accessibility to the users. The morse code inputs are captured by the push button presses and then converted to readable text with the help of the microcontroller ESP8266, which further gives visual outputs through LCD and audio outputs through the buzzer. The device also supports two-way communication, that is two similar devices can send and receive messages from each other easily, thus even if two disabled people have to communicate with each other, they can do so without any difficulty. This function enables interaction between individuals with similar kinds of disabilities and fosters inclusivity and mutual understanding. It aims to promote independence and social engagement. The service is highly practical, cost-effective, and most importantly, easy to use. © 2025 IEEE.

关键词： Visual communication

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Morse Code Based Two-Way Communication Device for Visually Impaired and Mute

Morse Code Based Two-Way Communication Device for Visually I...

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Device Intelligence, Computing and Communication Technologies, (DICCT), International Conference on

作者： Abha Marathe Snehal Bawanthade Rohit Bele Nidhi Bhagwat Avinash Bhurke Department of Electronics and Telecommunication Engineering Vishwakarma Institute of Technology Pune India Department of Computer Science Engineering Vishwakarma Institute of Technology Pune India

ISBN: (数字)9798331543358

ISBN: (纸本)9798331543365

关键词： Visualization Presses Codes Translation Speech coding Microcontrollers Visual impairment Assistive technologies People with disabilities Smart phones

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A Scientometric Review and Research Trends of Internet of Things in Application of Smart City 11

A Scientometric Review and Research Trends of Internet of Th...

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11th International Conference on ICT for Smart Society, ICISS 2024

作者： Maulana, Fairuz Iqbal Prasetyo Adi, Puput Dani Pramono, Andi Rahayu, Anita Persada, Satria Fadil Nadlifatin, Reny School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Research Center for Telecommunication National Research and Innovation Agency Bandung Indonesia School of Design Bina Nusantara University Interior Design Department Jakarta11480 Indonesia Binus Business School Undergraduate Program Bina Nusantara University Entrepreneurship Department Jakarta Indonesia Institut Teknologi Sepuluh Nopember Department of Information System Surabaya Indonesia

ISBN: (纸本)9798350389654

The Internet of Things (IoT) has revolutionized the concept of Smart Cities by enabling the seamless integration of various technologies and devices to enhance urban living. This abstract presents a comprehensive overview of the research trends and advancements in IoT applications within Smart Cities from 2019 to 2023. By conducting a scientometric review and bibliometric analysis using R studio and VOSviewer software, this study aims to identify key focus areas, challenges, and opportunities in the implementation of IoT technologies in urban environments. Data selection from the Scopus database yielded a total of 3849 documents from 1515 sources. The most cited article from 2021 is 166 citations. Average citations per doc is 18.56. China, India, and Korea appear to dominate in terms of the number of published documents. Future research directions include exploring innovative solutions leveraging technologies like blockchain, edge computing, and artificial intelligence to improve the efficiency, sustainability, and resilience of Smart City initiatives. By synthesizing insights from existing literature and exploring emerging trends, this study contributes to the advancement of Smart Cities and the development of a more connected and intelligent urban future. © 2024 IEEE.

关键词： Sustainable city

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Revolutionizing UAV: Experimental Evaluation of IoT-Enabled Unmanned Aerial Vehicle-Based Agricultural Field Monitoring Using Remote Sensing Strategy

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Remote Sensing in Earth Systems sciences 2024年第4期7卷 411-425页

作者： Narayanappa, Gireesh Babu Chandanadur Abbas, Syed Hauider Annamalai, Lavanya Meenakshi, Ramakrishnan Singh, Mangal Yadav, Tumikipalli Nagaraju Kumar, Aarthi Ramesh Department of CSE/ISE BMS Institute of Technology and Management Bengaluru India Department of Computer Science & amp Engineering Integral University Lucknow India Department of ECE Dr. MGR Educational and Research Institute Chennai India Department of CSE Chennai Institute of Technology Chennai India Department of Electronics and Telecommunication Engg Symbiosis International (Deemed University) Symbiosis Institute of Technology Pune India Department of Computer Science and Engineering Koneru Lakshmaih Education Foundation AP Vaddeswaram India Department of ECE R.M.D Engineering College R. S. M Nagar Gummidipoondi India

Agricultural monitoring has evolved significantly with the advent of unmanned aerial vehicles (UAVs), which offer innovative solutions for precision farming. Traditional agricultural practices often rely on manual inspection and limited ground-based sensors, which can be time-consuming and prone to inaccuracies. This paper explores the integration of UAV and ground-based IoT sensor data through advanced data fusion techniques to enhance data reliability and precision. Our hybrid machine learning model (HMLM), combining random forest and support vector machine algorithms, is employed for accurate crop health assessment, disease detection, and yield prediction. The implementation of UAV-based agricultural monitoring systems leverages the unique capabilities of quadcopters and fixed-wing UAVs. Quadcopters are utilized for detailed field surveys and spot checks, offering high-resolution imaging for precise inspections, while fixed-wing UAVs are deployed for large-scale monitoring, providing extensive coverage and long-flight endurance. Equipped with advanced IoT devices and sensors, including multispectral and hyperspectral cameras, GPS modules, and real-time communication systems, these UAVs enable comprehensive data collection and analysis. Our hybrid machine learning model (HMLM) improves classification accuracy and predictive power, achieving an impressive accuracy of 98.74%, leading to precise crop management and higher yields. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Agricultural monitoring Artificial intelligence (AI) Deep learning GPS modules Hybrid machine learning model (HMLM) Internet of things (IoT) Precision agriculture Sustainable farming Unmanned aerial vehicles (UAVs)

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Cancer Prediction using Clinical and Genomic Data Fusion: A Systematic Review 6

Cancer Prediction using Clinical and Genomic Data Fusion: A ...

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6th International Conference on Cybernetics and Intelligent System, ICORIS 2024

作者： Julian, Kelvin Nugroho, Kuncahyo Setyo Nirwantono, Rudi Pardamean, Bens Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Biotechnology Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9798331539603

This systematic review provides a comprehensive overview of the methods used to integrate genomic and clinical data in cancer prediction. The review includes 19 studies across various cancers, including breast, colorectal, melanoma, lung, pancreatic, and thyroid. The studies employed different methods to combine genomic and clinical data, including weighted polygenic risk scores, genetic and non-genetic risk scores, and different machine learning algorithms. The results show significant improvements in model prediction performance accuracy across multiple studies. The review highlights the potential benefits of integrating genetic and phenotypic information to improve disease risk prediction models and inform personalized healthcare strategies. © 2024 IEEE.

关键词： Lung cancer

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