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5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2024

作者： Murugesan, M. Arun Kumar, K. Karthikeyan, V.V. Sivaranjani, S. Nirvin Chandar, R. Kishore, P. M.Kumarasamy College of Engineering Department of Computer Science and Engineering Tamilnadu Thalavapalayam Karur639113 India M.Kumarasamy College of Engineering Department of Computer Science Engineering Thalavapalayam Tamilnadu Karur639113 India M.Kumarasamy College of Engineering Department of Electronics and Communication and Engineering Tamilnadu Thalavapalayam Karur639113 India M.Kumarasamy College of Engineering Department of Electronics and Communication Engineering Tamilnadu Thalavapalayam Karur639113 India

ISBN: (纸本)9798350385649

Real hazards to infrastructure, environmental systems, and human life come from forest fires. According to a survey, forest fire will damage the forest to a half by 2030. Forest fire can be prevented by taking actions by having fire detection devices. Most of the institutions and research development centers are attracted towards the fire detection systems. There are many sensors for detecting the fire but it also has many demerits like expensive, requires large space for installation and other problems. Due to the emergence of a digital camera, detection of fire has become easier. The use of sensors has many limitations but it is resolved by using image processing techniques. Because certain things share characteristics with fire, making accurate forest fire detection algorithms difficult, false alert rates may be significant. In this study, we may examine several ways for detecting forest fires and provide a brand-new, four-stage video-based method for detecting forest fires using image processing. To find moving areas, a background-subtraction technique is used first. Secondly, RGB color space is used to identify possible fire zones. Third, because candidate zone might have moving fire-like things, extraction of characteristics is employed to differentiate between the actual fire as well as fire-like items. The category of the fire can be determined by using the convolutional neural network method. Further incorporate devices for fire detection alerts into this system. © 2024 IEEE.

关键词： Fires

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MACPGANA: design of a highly efficient multimodal agriculture commodity price prediction model via generative adversarial networks & autoencoders

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International Journal of Information Technology (Singapore) 2025年第4期17卷 2355-2368页

作者： kambo, Rubi Pillai, Jyothi Soni, Sunita Urkude, Giridhar Department of Computer Science and Engineering Bhilai Institute Technology Chhattisgarh Durg India Department of Computer Science and Engineering Rungta College of Engineering and Technology Chhattisgarh Bhilai India Symbiosis Institute of Technology Nagpur Campus Symbiosis International(Deemed University) Pune India Department of Computer Applications Bhilai Institute of Technology Durg Chhattisgarh India

This paper presents MACPGANA, a novel multimodal agriculture commodity price prediction model leveraging Generative Adversarial Networks (GAN) and Autoencoders (AEs). The model integrates multimodal data to extract and represent features efficiently, employs GAN for feature selection, and uses predictive autoencoders to estimate inter-day price movements. A Q-Learning-based feedback loop ensures continuous optimization of prediction performance. MACPGANA achieves high accuracy, precision, and recall while maintaining low computational complexity, making it suitable for real-time and large-scale applications. The model’s effectiveness is demonstrated across diverse commodities, highlighting its potential for scalable and efficient agricultural price prediction. © Bharati Vidyapeeth's Institute of computer Applications and Management 2025.

关键词： Agriculture commodity price prediction Autoencoders (AE) Generative adversarial networks (GAN) Multimodal feature extraction Q-learning optimization Real-time price forecasting

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Doped low-density parity-check codes

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Digital Communications and Networks 2024年第1期10卷 217-226页

作者： Yong Li Rui Liu Xianlong Jiao Youqiang Hu Zhen Luo Francis C.M.Lau College of Computer Science Chongqing UniversityChongqing400044China School of Automation Chongqing UniversityChongqing400044China College of Electronic and Information Engineering Southwest UniversityChongqing400715China Future Wireless Networks and IoT Focusing Area Department of Electronic and Information EngineeringHong Kong Polytechnic UniversityHong KongChina

In this paper,we propose a doping approach to lower the error floor of Low-Density Parity-Check(LDPC)*** doping component is a short block code in which the information bits are selected from the coded bits of the dominant trapping sets of the LDPC ***,an algorithm for selecting the information bits of the short code is proposed,and a specific two-stage decoding algorithm is *** results demonstrate that the proposed doped LDPC code achieves up to 2.0 dB gain compared with the original LDPC code at a frame error rate of 10^(-6)Furthermore,the proposed design can lower the error floor of original LDPC Codes.

关键词： LDPC codes Doped LDPC codes Tanner graph Quadratic residue codes Trapping sets

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Automotive Visible-Light Communication: Alternative Devices and Systems

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Tsinghua science and Technology 2023年第4期28卷 719-728页

作者： Lin Cheng Yue Wu Chenren Xu Khadija Ashraf Ashwin Ashok Department of Engineering Trinity CollegeHartfordCT 06106USA Department of Computer Science Yale UniversityNew HavenCT 06520USA Department of Computer Science and Technology Peking UniversityBeijing 100084China Department of Computer Science Georgia State UniversityAtlantaGA 30302USA

Continuous advancements in visible-light communication(VLC)technology have paved the way for future high-capacity communication links that can simultaneously provide data transmission and *** is being accepted as a potential complementary technology in 5G networks,and standardization efforts through IEEE 802.15.7 are on their ***,vehicular networking applications have become increasingly complex with tight power and performance ***,devices and systems that can meet diverse vehicular networking applications are in great *** this article,we discuss three alternatives for vehicular networking applications in(1)LED–photodiode-based active VLC,(2)VLC with a multicamera array receiver,and(3)passive VLC based on decoding information from optical *** also present our recent experimental and modeling work using our camera-based and passive VLC prototype implementations.

关键词： visible-light communications automobile camera communications

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Condition Based Monitoring of Rolling Bearing by Naive Bayes Classifier 5th

Condition Based Monitoring of Rolling Bearing by Naive Bayes...

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5th International Conference on Electrical and Electronics engineering, ICEEE 2024

作者： Kumar, Sujit Kumari, Alka Nandani, Durgesh Kumar, Manish Electrical Engineering Department Government Engineering College Banka Bihar Engineering University Science Technology and Technical Education Department Bihar Patna India Electrical Engineering Department Government Engineering College Banka Bihar Banka India Computer Science and Engineering Department Government Engineering College Banka Bihar Banka India Electrical Engineering Department Indian Institute of Technology Patna Bihar Patna India

ISBN: (纸本)9789819791118

Rolling bearings are the main components of rotating machines which are mostly damaged. Therefore, correct and quick fault diagnosis of rolling bearings is very necessary for maintenance. Nowadays, machine learning has emerged as a very effective artificial intelligence technique for fault diagnosis. The Naive Bayes classifier is one of the machine learning techniques that effectively classifies faults. In this work, intelligent fault classification of bearing faults based on Naive Bayes is proposed. The proposed model correctly classifies the different types of fault conditions of rolling bearings. The proposed model has achieved the best results and has been compared with existing methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Condition based maintenance

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Hybrid Routing and Energy Management for Performance Optimization in Mobile Ad-hoc Networks 2

Hybrid Routing and Energy Management for Performance Optimiz...

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2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Nirmala, B. Vijaya Francis Raj, J. Relin Krishnan, R. Santhana Lavanya, V. Pitchirani, A. Kumar, V. Vinoth PSNA College of Engineering and Technology Department of Information Technology Dindigul India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Electronics and Communication Engineering Chennai India SCAD College of Engineering and Technology Department of Electronics and Communication Engineering Cheranmahadevi India Velammal College of Engineering and Technology Department of Computer Science and Engineering Madurai India SCAD College of Engineering and Technology Department of Computer Science and Engineering Cheranmahadevi India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331505745

Mobile Ad-hoc Networks (MANETs) encounter challenges related to dynamic topologies, energy constraints, and link instability. To enhance performance, a hybrid model integrates Ad-hoc On-demand Multipath Distance Vector (AOMDV), Power-Efficient Gathering in Sensor Information System (PEGASIS), and Deep Q-Network (DQN). OMNeT++, a discrete event simulation framework, facilitates comprehensive data collection, capturing key network parameters such as node density, signal strength, packet transmission rate, residual energy, routing paths, link breakage frequency, and packet delivery status. Stored in scalar and vector files, the dataset enables energy-efficient communication modeling and adaptive routing optimization. Data preprocessing involves cleaning, normalizing, and handling missing values using interpolation techniques while filtering noisy data through a sliding window averaging method. Feature extraction focuses on hop count, queue length, residual energy, and link expiration time, ensuring consistency and facilitating faster convergence. The hybrid model architecture integrates AOMDV for reliable multipath routing, PEGASIS for energy-efficient communication, and DQN for adaptive path optimization. Simulation results indicate a 15% improvement in throughput, a 10% rise in packet delivery ratio, a 20% reduction in end-to-end delay, and a 30% decrease in average energy consumption. Applications extend to military operations, disaster recovery, vehicular networks, IoT sensor networks, and smart city infrastructure, ensuring efficient and adaptive communication. © 2025 IEEE.

关键词： Vehicular ad hoc networks

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A Deep Learning Approach for Classification and Segmentation of Leafy Vegetables and Diseases

A Deep Learning Approach for Classification and Segmentation...

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2023 International Conference on Next-Generation Computing, IoT and Machine Learning, NCIM 2023

作者： Islam, Ashraful Sama Raisa, Syeda Rafiatus Khan, Nahiyan Habib Rifat, Ariful Islam Sylhet Engineering College Dept. of Computer Science and Engineering Sylhet Bangladesh American International University-Bangladesh Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350316001

Bangladesh's economy is heavily dependent on agriculture, making the region an exceedingly crucial sector that requires great vigilance. In comparison to other vegetables, leafy greens have yet to garner as much attention as other crops that this study's large-scale analysis comes up with, particularly when categorizing readily available leafy vegetables and identifying the affected area and whether they are affected or not. Plant diseases can cause substantial losses in agricultural productivity, and many researchers are working to address the difficulties farmers encounter in identifying and treating these conditions while diagnosing their diseases. The purpose of this study is to develop a dependable and effective approach for classifying seven varieties of leafy vegetables and detecting seven types of plant diseases precisely in Bangladesh using machine learning and deep learning CNN models. To this end, this paper analyzed and provided solutions using a total of eight models: five classification models (VGG16, VGG19, ResNet50, YOLOv5, and YOLOv8) and three instance segmentation models (YOLOv5, YOLOv7, and YOLOv8). Two distinct datasets, 'LeafyVclassify7BD' with 3306 images and 'LeafyVdisease7BD' with 4493 images, were developed to classify leaves, segment the diseased area, and classify and detect damaged leaves. The research outputs will help strengthen the region's ability to control plant diseases more effectively while also cutting diagnostic costs and enhancing disease detection accuracy in the country's agricultural surroundings. © 2023 IEEE.

关键词： Classification (of information)

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An IoT based Portable Sensory System for the Accurate Analysis of Soil Macronutrients using Photometry

An IoT based Portable Sensory System for the Accurate Analys...

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2023 Annual International Conference on Emerging Research Areas: International Conference on Intelligent Systems, AICERA/ICIS 2023

作者： Fred A, Lenin Lincy, C.T. Jalbin, J. Herlin, L.T. Mar Ephraem College of Engineering and Technology Computer Science and Engineering Marthandam India Mar Ephraem College of Engineering Electronics and Communication Engineering Marthandam India

ISBN: (纸本)9798350303452

Nitrogen, Phosphorus, and Potassium (NPK) as elemental macro nutrients are highly indispensable for augmenting agricultural productivity. The amalgamation of NPK sensors with Internet of Things (IoT) technology within the domain of precision agriculture has garnered substantial scholarly interest. This integration facilitates the contemporaneous and meticulous monitoring of soil nutrient levels, thereby allowing farmers to discerningly optimize Fertilizer Use Efficiency (FUE). Such precision not only engenders heightened crop yields but also serves as a bastion against soil pollution, thereby reinforcing environmental stewardship to bolster the economic sustainability of farmers. In the multifaceted context of varying nutrient exigencies across diverse crop species at different testing intervals within agro-ecosystems, rapid development is highly necessitated. In response to this constraint, the current scholarly discourse expounds upon the pioneering development of an innovative NPK sensor, rooted in the venerable photometric principle. The crux of this method lies in the detection and quantification of light refraction in the resultant solution, meticulously orchestrated through the perceptive deployment of a Light Dependent Resistor (LDR) and a sophisticated ARM microcontroller. The efficacy and precision of this system are corroborated through the rigorous application of statistical models, thereby substantiating its operational linearity to mark a significant step toward sustainable and efficient agricultural practices. © 2023 IEEE.

关键词： Soils

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Secure Splitting of Bills and Managing Expenditure Using Blockchain 3

Secure Splitting of Bills and Managing Expenditure Using Blo...

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3rd IEEE International Conference on Technology, engineering, Management for Societal Impact using Marketing, Entrepreneurship and Talent, TEMSMET 2023

作者： Mahindre, Swaraj Gupta, Stuti Rambhad, Vaishnavi Koppisetti, Shreyasi Thakur, Shruti Computer Science and Engineering G H Raisoni College of Engineering Nagpur India G H Raisoni College of Engineering Nagpur India

ISBN: (纸本)9798350397819

After its introduction in Web 3.0, blockchain has become the dominant technology for securely transferring data through decentralized peer-to-peer systems. Blockchain is an unchangeable ledger that enables safe, decentralized transaction execution. This paper proposes a system for dividing group expenses and managing expenses that employs blockchain technology for data security. In this project, we will integrate Blockchain technology with a web client so that users can easily access the application. This application will save all of the user's transaction data in a secure manner, ensuring that the data is not tampered by anyone. Also, options for dividing the bill equally and unequally are also available. This application will also keep a track of user's expenses, this feature will help them to manage their expenses accordingly. © 2023 IEEE.

关键词： Blockchain

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Enhancing Face Mask Detection Using Data Augmentation Techniques

Enhancing Face Mask Detection Using Data Augmentation Techni...

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2023 International Conference on Recent Advances in science and engineering Technology, ICRASET 2023

作者： Kumar, P. Vinodh Kumar, S. Priya, L. Senthilpandi, S. Rajalakshmi Engineering College Department of Computer Science and Engineering Chennai India Rajalakshmi Engineering College Department of Information Technology Chennai India

ISBN: (纸本)9798350306927

In the ongoing pandemic that we are in general confronting, a cover has turned into a significant extra that we want to wear at whatever point we step out to safeguard ourselves and everyone around us. People who wear masks are to blame for the success of every nation that escaped the pandemic and resumed normalcy. Great reconnaissance estimates that guarantee that the general population is wearing covers consistently can assist us in beating this pandemic. Our existing camera systems can be used by computer vision systems to examine enclosed spaces and recognise individuals without masks. Best-in-class Item Recognition calculations can run at high derivation speeds, which will make this framework basically deployable progressively. Subsequently, further developing the acknowledgment execution of the current face acknowledgment innovation on the veiled faces is exceptionally critical. The latest high-level face acknowledgment approaches are planned in view of profound realisations, which rely upon countless face tests. The training of object detection models that are capable of locating both the unmasked and masked faces in an image is the objective of this paper. These indicators will likewise be hearty to commotion and give as little room as conceivable to oblige bogus up-sides for veils because of the possibly desperate results that they would prompt. © 2023 IEEE.

关键词： Object detection

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