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An Efficient and Secure Cluster-Based Cooperative Data Transmission for Wireless Ad Hoc Networks IOT Environment

An Efficient and Secure Cluster-Based Cooperative Data Trans...

引用

International Conference on Machine Vision and Augmented Intelligence, MAI 2022

作者： Mahapatra, Surya Narayan Singh, Binod Kumar Department of Computer Science and Engineering National Institute of Technology Jamshedpur831014 India

ISBN: (纸本)9789819901883

In current scenario, we have multiple technologies are available to transmit the data in wireless ad hoc network (WANET).But, compare to other existing models, we have proposed a new model where not only this model helps to reduce the energy consumption of nodes while transmitting the data but also our model focus on security aspect where it will help to solve some of the common attacks such as collusion attack, Dos attack, etc., our model consist of 3 stages/phases, namely as (i) registration, (ii) clustering, and (iii) transmission. In registration phase, each node in the network will identified by unique id, and nodes will registered themselves to the network, and in second phase, nearby nodes will form clustered based on the threshold value and transmitting power. By using multi-hop transmission after finding the route with the help of relay node search optimization (RESO), where appropriate relay node will be selected based on the parameters which will reduce the energy computation by the node and by the blockchain-based transaction from node of one cluster to another cluster. This will deminise the security threat in the network. However, in our model, we expecting the result better than existing models based on the theoretical knowledge. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Blockchain

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LiDAR Sensor for Self-Driving Cars 8

LiDAR Sensor for Self-Driving Cars

引用

8th International Conference on Communication and Electronics Systems, ICCES 2023

作者： Tummala, Manoj Pravin, A. Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350396638

Progressive technological development results in modern automotive technology such as self-driving automobiles. These require sensors to collect data about nearby objects and the surroundings in order to identify lanes and make decisions. Instead of LiDAR sensors (Light Detection and Ranging), Tesla, Waymo, and other successful businesses have employed cameras for developing autonomous vehicles. The disadvantage of camera performance changing with lighting conditions can be solved by using LiDAR. The LiDAR sensor aids in 3D mapping, allowing cars to travel in a predictable environment. The use of cameras for monitoring normal driving circumstances might be difficult because of the large range of features they include, but LiDAR contains infrared light, which is a solution for concerns such as fog, rainy weather, and varied textures. Developing sensors driven by computer vision can lead to more environmental sensing for self-driving automobiles in the future. This study discusses the use of LiDAR sensors in autonomous cars. © 2023 IEEE.

关键词： Autonomous vehicles

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A Review of Intelligent Traffic Management Systems 7

A Review of Intelligent Traffic Management Systems

引用

7th International Conference on Trends in Electronics and informatics, ICOEI 2023

作者： Ramanathan, R Ashwath BalaMurugan, R. Bama Krishna, R Sathya Selvan, Mercy Paul Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350397284

Traffic congestion is a significant issue that is becoming increasingly prevalent in modern society, particularly in major metropolitan areas. The negative impacts of traffic congestion include increased air and noise pollution, heightened risks of accidents, and longer travel times for residents. The traditional method of managing traffic, through the use of pre-determined traffic lights, is no longer adequate for the demands of a rapidly growing urban population. In response to this issue, various efforts have been made to develop an automated, intelligent traffic management system that utilizes sensors or video cameras to detect the density of vehicles on the road and adjust traffic signals accordingly. This study provides a comprehensive review of the different methods that have been proposed for intelligent traffic management, including a comparison of their pros and cons. © 2023 IEEE.

关键词： Object detection

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Optimal cloudlet movement and placement in a dynamic environment using cluster based technique 4

Optimal cloudlet movement and placement in a dynamic environ...

引用

4th International Conference on Computing and Communication Systems, I3CS 2023

作者： Sahkhar, Lizia Balabantaray, Bunil Kumar National Institute of Technology Meghalaya Department of Computer Science and Engineering Shillong India

ISBN: (纸本)9798350323771

User's mobility in a dynamic environment, such as a wireless metropolitan area network (WMAN), poses a challenge in finding the best position to place the cloudlet as the devices are always on the move and disrupt proper utilization of cloudlet resources. With more resource rich applications using cloudlet framework for immediate processing and computation, finding the best position to place the cloudlet in this vast and dynamic environment is an important study. This work focus on how movement of user devices defined the placement of a cloudlet at a particular position, which in turn determine the number of mobile devices coverage. To project this scenario, this paper uses a clustering method to study the movement of five hundred (500) mobile devices in a dynamic environment and how these devices are assigned to the three (3) cloudlets when they are positioned at various interval of time by considering a threshold value and capacity of the cloudlet. Through the cloudlet movement, the experiment are able to generate the initial, feasible and optimal placement position. It is also observe that mobile device coverage increases by 28.53% when cloudlets are moved from initial to the optimal position. Furthermore, through this technique, the distribution of mobile devices at various interval of time become more compact, organized and balanced with 307 to 179 to 147 for the first cloudlet, 189 to 198 to 163 for the second cloudlet and from 4 to 123 to 190 for the third cloudlet when cloudlets are moved from the initial to the feasible to the optimal position respectively. © 2023 IEEE.

关键词： K-means clustering

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AutoML - Learning, Understanding and Applying Machine Learning to Datasets 9

AutoML - Learning, Understanding and Applying Machine Learni...

引用

9th International Conference on Advanced Computing and Communication Systems, ICACCS 2023

作者： Patankar, Shreya Prajapati, Hitesh Shah, Jeet Upadhyay, Ankit K J Somaiya Institute of Technology Department of Computer Engineering Mumbai India

ISBN: (纸本)9798350397376

Current scenario of the digital world is loaded with sample amounts of data and to smartly analyze this data requires researching an interesting machine learning model to suit a dataset which is a topic of research and is more focused upon. Various state of art machine learning models like supervised, unsupervised and reinforcement models along with deep learning models are available to analyze varied datasets and for a given machine learning task, selecting one model from a large pool of options is a surprisingly challenging problem, particularly if there is a lack of evaluation data to distinguish between models and this requires for a thorough understanding of the dataset which you are using to solve the task. Dataset plays an important role in the performance of any machine learning model and not always you will get a clean / well balanced dataset to directly apply the model on. The key contribution of this paper is focused on the challenge of picking a good model which can be reformulated by doing a proper analysis and cleaning of the dataset, with the objective of recommending a suitable model for a given task based on the performance of a small set of probe models under the domain of classification and regression. © 2023 IEEE.

关键词： Classification (of information)

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A Delaunay triangulation-based improved energy-aware clustering algorithm for WSNs

A Delaunay triangulation-based improved energy-aware cluster...

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2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Sivadasan, Sreeram Nagarajan, Govindan Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India

ISBN: (纸本)9798350305708

Energy efficiency is an important constraint in Wireless Sensor Networks (WSNs). In this paper, we propose a Delaunay triangulation-based approach for the efficient participation of nodes. Following a Delaunay triangulation-based mobile node placement, we introduce an Equi-Quadrant Division-based Clustering for shortest path routing to the base station (BS). The proposed method not only allows us to address issues like coverage holes and sensing range identification of a node in a random distribution but also improves node participation. Our experiments on a simulated environment show that the proposed simple algorithm is capable of giving competitive results compared to traditional clustering algorithms like FL-LEACH [11] and GA-APTEEN [12]. © 2023 IEEE.

关键词： Clustering Coverage hole Delaunay triangulation Wireless sensor network

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Fish Species Classifier for Allergic People using CNN Algorithm 7

Fish Species Classifier for Allergic People using CNN Algori...

引用

7th International Conference on Computing Methodologies and Communication, ICCMC 2023

作者： Reddy, Puchalapalli Surya Vradhan Krishna, Mannepalli Vamsi Aishwarya, R. Yogitha, R. Kumar, K. Ashok Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India

ISBN: (纸本)9781665464086

Some people may be allergic to a variety of crustaceans, including prawns, crab, and lobster, or they may be sensitive to some types of fish. Cross-reactivity is the term for this kind of condition. This approach is useful because it is challenging to predict which fish will cause an allergic reaction in you. It is challenging to determine which fish may cause an allergic reaction. Deep learning has been a huge help in recent years in solving numerous issues. Real-time datasets are not implemented in the current systems, and they additionally the current systems are not very accurate. The proposed system utilizes CNN algorithm for detecting and classifying fish that cause allergies. The implemented system aims to help people with seafood allergies, clinical immunology, or allergies. specialist in image analysis of caught fish, detection, and species classification of fish from images. © 2023 IEEE.

关键词： Deep learning

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Detection of Non Helmet Riders and Extraction of Licence Plate Number

Detection of Non Helmet Riders and Extraction of Licence Pla...

引用

2023 International Conference on Innovations in engineering and technology, ICIET 2023

作者： Kumar, K. Ashok Dharshan Sekhar, Chandra Manikanta, S.D. Sathyabama Institute of Scienceand Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350309980

The current scenario of India's traffic laws poses a number of challenges, each of which may be addressed in a variety of ways. An increasing incidence of motorbike and moped-related fatalities have been linked to the common practice of driving without a headgear in India. The current system relies heavily on CCTV records to keep tabs on traffic offences, forcing cops to manually examine individual frames and, if the rider isn't wearing a helmet, focus in on their numberplate. However, this calls for a significant investment of time and resources, since traffic offences are common and the number of motorcyclists grows daily. What if there were a technology that could detect whether or not a motorcyclist was breaking the law by failing to wear a helmet and, if so, get the vehicle's registration number from the database? This study has been accomplished with recent success using HaaR, HoG, LBP, R-CNN, CNN features, etc. However, the pace, precision, and effectiveness of object identification and categorization are severely constrained by these works. In an effort to automate the process of finding instances of the traffic offense of not donning a headgear and retrieving the numberplate of vehicles, this study develops a Non-Helmet Driver identification method. The core idea is to use three tiers of DL for Image Classification. Individual, motor bike, headgear, and licence plate are all recognisedutilising YOLOv2's increasing levels of sophistication. Then, OCR is used to get the licence plate number. Particularly for the extraction of licence plate numbers, all of these methods are governed by a set of predetermined parameters and limits. Since moving images are used as input, the processing time is critical. By combining the aforementioned methods, we have developed a comprehensive system for identifying helmets and extracting licence plate numbers. © 2023 IEEE.

关键词： Extraction

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Unbreakable Security in a Quantum Age: A Systematic Literature Review on Post-Quantum Lattice-Based Standards 4

Unbreakable Security in a Quantum Age: A Systematic Literatu...

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4th IEEE International Conference on Quantum Computing and engineering, QCE 2023

作者： Wahlang, Roisan Chandrasekaran, K. National Institute of Technology Karnataka Computer Science and Engineering Department Surathkal India

ISBN: (纸本)9798350343236

The rapid advances in the field of quan-tum computing have led to a concern in the cryp-tographic security implemented in already existing systems. This has led to an increasing interest in the search for post quantum alternatives which are capable of withstanding attacks in the future era of quantum computers. Out of the many approaches that have been put forward, the most promising candidates belong to the class of lattice based cryptography due to their efficient parameter sizes and performances. The robustness of these post quantum schemes have been tested by considering the evaluation criteria which have been put forward by NIST to ensure that the security guarantee provided by these proposed systems are absolute. This paper provides an overview of the various lattice based cryptosystems that have been selected as candidates for standardization by NIST and a comparison between them has been provided demonstrating the differences in their performances on various platforms. © 2023 IEEE.

关键词： Quantum cryptography

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Digital Assets Fair Estimation Using Artificial Intelligence 2

Digital Assets Fair Estimation Using Artificial Intelligence

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2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, ViTECoN 2023

作者： Mavuri, Shobitha Kathirvel, A. Karunya Institute of Technology and Sciences Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350347982

The prediction of digital asset prices is a challenging task, as the value of digital assets is influenced by a multitude of factors, including market sentiment, technological advancements, and macroeconomic events. Despite these challenges, various approaches to digital asset price prediction have been proposed, including time-series analysis, machine learning (ML) algorithms, and Deep Learning (DL) algorithms. These algorithms involve using historical price data to make estimation about future price movements. It is important to note that digital asset price predictions are inherently uncertain and should be viewed as a guide rather than a definitive forecast. This proposed system can estimate the price for Non-Fungible Token(NFTs) collection as it can provide an accurate and reliable estimate of the value of these NFTs in the market. This information can help inform investment decisions, support market analysis, and improve the buying and selling experience for collections NFTs. © 2023 IEEE.

关键词： Long short-term memory

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