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4th IEEE International Conference on Artificial Intelligence in Engineering and technology, IICAIET 2022

作者： Hang, Yii Sze Jali, Nurfauza Ping, Lau Sei Shiang, Cheah Wai Jali, Suriati Khartini Chin, Lim Phei Universiti Malaysia Sarawak Faculty of Computer Science and Information Technology Sarawak Kota Samarahan94300 Malaysia

ISBN: (数字)9781665468374

ISBN: (纸本)9781665468374

Today, vast amounts of energy are required to power streetlights. Also, the death caused by accidents due to the blockage of the vehicle on the road is increasing especially on the highway. Thus, this paper aims to assemble an intelligent system that implies an automatic switch for detecting vehicle passage with keeping the existing system. Besides, this system uses solar energy to generate free electric energy through the natural resource that our country has gifted sunlight. Besides building an energy-saving system, a safety feature is also one of the aspects considered. This is done by utilising the sensors inserted in the streetlight system and a collaboration between the hardware and coding. By having this safety feature, any blockage due to a car crash or vehicles' break happening at a certain distance in front will activate the hazard warning function in the system while sending a notification to the streetlight management department. This gives the drivers enough time to slow down the vehicles instead of on-the-spot emergency breaks. On the one hand, this system lowers the electricity consumption and increases the safety of the road system. © 2022 IEEE.

关键词： Energy conservation

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ASCON-Based Mutual Authentication and Secure Surveillance Video Data Management in Smart Cities Using Blockchain

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IEEE Transactions on Consumer Electronics 2025年

作者： Chaurasia, Mahesh Pal, Arup Kumar Islam, Sk Hafizul Pradhan, Jitesh Department of Computer Science and Engineering Jharkhand Dhanbad826004 India Indian Institute of Information Technology Kalyani Department of Computer Science and Engineering West Bengal 741235 India National Institute of Technology Jamshedpur Department of Computer Science and Engineering Jharkhand831014 India

In the current era, the deployment of video surveillance systems (VSSs) is becoming a common practice in society for properly maintaining laws and order in public and private places. The surveillance video data (SD) generated from such infrastructure is sensitive and must address the concerns about its security. To ensure the security of SD, there is a need for a mechanism that provides authenticity, confidentiality, and integrity, all at the same time while being lightweight. ASCON delivers all these capabilities. This paper presents a novel approach to enhance the security of the smart city surveillance system using ASCON and Blockchain. Due to its immutable storage property, the Blockchain detects hardware attacks by validating the cameras and local servers. In this paper, SD is stored in the cloud server due to limited local server storage, which can become a primary target for attackers. Therefore, this paper stores the encrypted SD into the cloud server. Formal security analysis using the Scyther tool and the Random Oracle Model (ROM) validates the system's robustness. Additionally, this paper evaluates and contrasts the proposed scheme's computational and transmission overheads with the other existing schemes. The results show that the proposed system significantly enhances the security of SD, offering a resilient solution for smart city surveillance infrastructures. © 2025 IEEE.

关键词： information management

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A new method for the Detection of Anomalies in Streaming Data Malicious URL Segmentation and Classification using Machine Learning Techniques

A new method for the Detection of Anomalies in Streaming Dat...

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2022 International Conference on Augmented Intelligence and Sustainable systems, ICAISS 2022

作者： Mantravadi, Ananya Indurkhya, Kushagra Buchi, Sai Mourya Ganda, Sai Yaaminie Kumar Reddy, Sai Kiran Kaveeshwar, Anuraag Raghuramchandra IIIT Department of Computer Science and Engineering Karnataka Raichur India IIT Hyderabad Department of MCES Hyderabad India TKR College of Engineering and Technology Department of Computer Science and Engineering Nerul India Pune Institute of Computer Technology Department of Information Technology Pune India

ISBN: (纸本)9781665489621

PC networks have created to present serious dangers since they are continually focused on by different attacks. New assaults and patterns are being passed along;these attacks focus on all open ports that are available on the organization. For this, various advancements are accessible, including network planning and weakness screening. Lately, AI (ML) has been a famous technique used to take care of the Intrusion Detection system's (IDS) capacity to distinguish malevolent network traffic. The nature of the dataset used to prepare the model is crucial for how well ML models recognize abnormalities. The aggressor in an organization attack should know about the dynamic locations, network construction, and administrations that are accessible. At the point when shared administrations are related with certain ports on a framework, network scanners might recognize open ports, whether they are TCP or UDP ports, and an assailant could send parcels to each port in the event that they decide. TCP fingerprinting capacities of different sellers' frameworks' reactions to unlawful parcel structures Different TCP/IP stack reactions are shipped off unlawful bundles. Thus, by sending an assortment of unlawful bundle blends, opening an association with a RST parcel, or blending other odd and unlawful TCP code bits, the assailant can find out the OS. The motive of the paper is for the detection and classification of the anomalies present in the URL along with segmentation of it with the help of machine learning techniques and a accurate comparison for the same. © 2022 IEEE.

关键词： Support vector machines

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Cost-Effective Resource Allocation in Underwater Fibre Optic Networks Using Bandwidth Optimization 15

Cost-Effective Resource Allocation in Underwater Fibre Optic...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Singh, Khushboo Singh, Akhilendra Pratap Janakiraman, V. Dhabliya, Dharmesh Rajendran, Naveen Kumar Singh, Jagtej Vivekananda Global University Department of Computer Science & Engineering Jaipur India Maharishi University of Information Technology Maharishi School of Engineering and Technology Uttar Pradesh India Prince Shri Venkateshwara Padmavathy Engineering College Department of Mechanical Engineering Chennai127 India Vishwakarma Institute of Technology Department of Information Technology Maharashtra Pune India Faculty of Engineering and Technology Department of Aerospace Engineering Karnataka Bangalore India Chitkara University Institute of Engineering and technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India

ISBN: (纸本)9798350370249

Underwater fiber optic networks have become increasingly widespread to facilitate underwater communique. However, due to their high installation and maintenance expenses, laying out green networks that maximize bandwidth usage is essential. This paper proposes a cost-powerful resource allocation method for underwater fiber optic networks using bandwidth optimization strategies. The proposed methodology consists of 3 most important steps: First, it fashions the network's topology with graph-theoretic algorithms, which optimizes the bandwidth usage to maximize hyperlink efficiency. Moreover, it presents methods to evaluate the effectiveness of the generated topology and decide the ideal network allocation based totally on price estimation. Furthermore, heuristic algorithms assign hyperlink weights to minimize the general price. Eventually, the cost-effectiveness of the proposed approach is evaluated by the usage of simulations done on underwater networks with numerous topologies. Results display that the proposed approach achieves widespread price financial savings over conventional methods. Consequently, the proposed technique may be used to successfully allocate assets in underwater fiber-optic networks. © 2024 IEEE.

关键词： Heuristic algorithms

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Fall Detection system for Depression Angle RGB Image based on Human Skeletonch

Fall Detection System for Depression Angle RGB Image based o...

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2022 IET International Conference on Engineering Technologies and Applications, IET-ICETA 2022

作者： Liu, Chia-Ming Huang, Zhi-Shan Chen, Yen-Lin National Taipei University of Technology Department of Computer Science & Information Engineering Taipei Taiwan

ISBN: (数字)9781665491389

ISBN: (纸本)9781665491389

In recent years, Taiwanese society is gradually aging, and the existence of fall detection systems is crucial to protect the health and safety of the elderly in their daily lives. In this paper, we used the Openpose human skeleton recognition algorithm to extract the 2D human skeleton information from RGB images and took actions to recognize the 2D human skeleton information by the LSTM. In order to solve the problem of incomplete and inaccurate human skeleton information extracted from the top angle camera, this paper proposes an algorithm that uses an object recognition model to assist in extracting human skeleton information to improve its skeleton recognition rate, and then enhance the accuracy of the subsequent LSTM model to obtain more accurate fall detection results. © 2022 IEEE.

关键词： Long short-term memory

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A Review on the Use of Smart Agriculture systems to Protect Crops

A Review on the Use of Smart Agriculture Systems to Protect ...

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Electronics and Renewable systems (ICEARS), International Conference on

作者： Gulshan Kumar Palash Gourshettiwar Saurabh Suman Shravan Kumar Dhiraj Kumar Rahul Raushan Department of Computer Science and Design Faculty of Engineering and Technology Wardha Maharashtra India Department of Computer Science and Medical Engineering Faculty of Engineering and Technology Wardha Maharashtra India

ISBN: (数字)9798331509675

ISBN: (纸本)9798331509682

Smart agriculture systems leverage the possibilities offered by cutting-edge technologies such as IoT, AI, and remote sensing to revolutionize conventional farming by enhancing resource utilization, production, and crop damage mitigation. Real-time monitoring of soil and crop health, predictive analytics, pest control, and precision irrigation measures are all enabled by these systems. They are able to address major Indian agriculture issues, consequently boosting yield and profitability and promoting environmental sustainability. The largescale deployment of intelligent agriculture systems will change the agriculture landscape in India and will assure long-term food security for an ever-growing population. Challenges include adequate research and future studies in order to better install and achieve smart agricultural systems to protect crops. Intelligent agriculture involves all advanced research, including science and innovations, in national development through space technologies to enhance soil quality, conserve water, and facilitate agriculture information. Space ventures will undergo improved modernization through the introduction of crop sprayers, precision gene editors, epigenetics, big data analytics, IoT, wind and photovoltaic smart energy, AI-enabled robotic applications, and wide-scale desalination technologies. Implementing digital farming systems in developing economies will help their sectors as 85 percent of the global population is set to live in developing countries by 2030. Automation will prove to be necessary since food scarcity is on the rise along with resource wastage. Control strategies such as the IoT, aerial imagery, machine learning, and artificial intelligence will boost production and prevent soil degradation. These advanced technologies are also able to alleviate such issues as plant disease detection, pesticide management, and water application. The introduction of the Internet of Things in the agricultural research world has started

关键词： Smart agriculture Technological innovation Space technology Crops Production Soil Communications technology Internet of Things Remote sensing Farming

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Advanced Real-Time IoMT system for Early Gastric Cancer Detection through Integrated Grid-Search Multimodal Gating Network and Robust Embedded technology

Advanced Real-Time IoMT System for Early Gastric Cancer Dete...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Liu, Xian-Xian Xu, Mingkun Wei, Yuanyuan Yin, Huifeng Fong, Simon Luo, Wei Gao, Juntao University of Macau The Department of Computer and Information Science China Guangdong Institute of Intelligence Science and Technology Zhuhai China The Chinese University of Hong Kong The Department of Biomedical Engineering Hong Kong Beijing China University of Macau The Department of Computer and Information Science China The First People's Hospital of Foshan The Institute of Clinical Medicine Guangzhou China Beijing China

ISBN: (纸本)9798350351255

Achieving real-time, remote control and precise localization of early gastric cancer (EGC) lesions in endoscopic capsules is a significant obstacle in biomedical imaging development. This work outlines an innovative integrated system that uses an effective combination of Zynq UltraScale+ and Gizwits IoT to overcome this challenge. Our work employs a fully convolutional neural network underpinning grid-search clustering-driven multi-modals gating information local patch learning (GS-MGIF-LPLs). This system, designed as an adaptive location computing acceleration platform (ACAP), elegantly marries a double threshold fast search strategy with patch-based FCNN, fueling efficient training, testing, and performance metrics with an accuracy of 99.53%, precision coefficient of 86.06%, and an IoU of 84.26%. Upon benchmarking against four EGC types, our GS-MGIF-LPLs model demonstrates exceptional superiority against five established methods, providing a significant stride in computational efficiency and diagnostic advancements for gastrointestinal diseases. © 2024 IEEE.

关键词： Edge computing

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An Integrated Agricultural Financial Inclusion system Leveraging Supervised Machine Learning & Data Analytics

An Integrated Agricultural Financial Inclusion System Levera...

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Mobile Computing and Sustainable Informatics (ICMCSI), International Conference on

作者： Snehal Rathi Vijayshri Khedkar Rutuja Jadhav Mugdha Kamate Apurva Potdar Prachi Kamble Computer Department Vishwakarma Institute of Information Technology Pune India Department of Computer Science & Engineering Symbiosis Institute of Technology Pune India

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522674

Agriculture is backbone of many economies but still farmers often face many challenges in accessing financial services or available resources for them, making informed crop choices and participating in government initiatives. Because of many farmers are not aware about all these things, to address these concerns, the proposed “Agricultural Financial Inclusion system” provides a comprehensive platform which integrates essential services with aim of improving farmers' production and their financial awareness. Our system has a crop recommendation feature that helps farmers to choose the best suitable crop for their soil in the farm by taking climate and soil type into account. In order to make sure that farmers are aware about various available services/resources or any government schemes and able to take advantage of them, the platform also offers essential information on a variety of government initiatives, saving plans etc. By combining all these features, the Agricultural Financial Inclusion system encourage farmers to make smart choices which help them to enhance agricultural productivity and financial stability. In order to create more successful and sustainable agriculture sector, this integrated approach hopes to fill the gap between farmers and technology & resources they need.

关键词： Productivity Data analysis Government Crops Machine learning Soil Stability analysis Agriculture Mobile computing Testing

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Means and Methods for Building-up the Linearity of Broadband Amplifiers

Means and Methods for Building-up the Linearity of Broadband...

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2022 International Siberian Conference on Control and Communications, SIBCON 2022

作者： Sak, Pavel V. Nikonova, Galina V. Nikonov, Aleksandr V. Omsk State Technical University Information Technology and Computer Science Department Omsk Russia

ISBN: (纸本)9781665476287

This article is devoted to the issues related to engineering implementation of methods for building-up the linearity of transmitters and mathematical methods for correcting the parametric non-linear distortions of power amplifiers. Methods for constructing broadband power amplifiers for short-wave transmitters with various types of modulation during information transmission. Possible ways of implementing the various methods of automatic system for monitoring the parameters of a power amplifier in accordance to a specified level of linearity and amplitude response. The problem of obtaining high linearity of a power amplifier and the possibility of its solution by various methods or their combination is determined. Methods of preemphasis of the signal fed to the input of a power amplifier and the precorrection of the modulus of transmission coefficient of a power amplifier are investigated. It is shown that the use of these methods makes it possible to obtain a high path linearity and high efficiency, however they are difficult to implement, and therefore are not currently suitable for use in portable equipment. The greatest attention is paid to the method of using reverse feedback between the signal envelopes at the power amplifier input and output. This method of building-up the linearity of a power amplifier turns out to be preferable for paths of small transmitters. © 2022 IEEE.

关键词： Power amplifiers

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Research and Application of Boundary Optimization Algorithm of Forest Resource Vector Data Based on Convolutional Neural Network 2

Research and Application of Boundary Optimization Algorithm ...

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2nd International Conference on Smart Technologies for Smart Nation, SmartTechCon 2023

作者： Thangarasan, T. Surendhiran, V. Keerthana, R. Moheshkumar, G. Namasivayam, M. Saratha, M. Department of Computer Science & Engineering Madanapalle Institute of Technology & Science Andhra Madanapalle India Department of Computer Science and Engineering Excel Engineering College Komarapalayam India Department of Computer Science and Engineering K.S.R.College of Engineering Tamilnadu Tiruchengode India Department of Information Technology KSR Institute for Engineering and Technology Tamilnadu Tiruchengode India Department of Computer Science and Engineering K.S.R. College of Engineering Tamilnadu Tiruchengode India M.Kumarasamy College of Engineering Thalavapalayam Tamilnadu Karur India

ISBN: (纸本)9798350305418

With the deepening of the research and application of GIS (Geographic information system), the boundary quality of GIS data is becoming more and more important for production and application, and the high accuracy of vector data is the trend of future development. The second-class survey results have the characteristics of accurate and reliable survey data, rich contents and diverse expressions, and can establish forest resources archives for local areas. Therefore, this study established a boundary optimization algorithm for vector data of forest resources based on CNN (Convolutional Neural Network). The network structure proposed in this paper consists of encoder and decoder, and the input dimension of source data is 64×64. The encoder consists of CL(Convolution layer), active layer and PL(Pool layer). The dimension of CL is 24×64×256, which respectively represents the width of convolution kernel, the number of input data columns and the number of convolution kernels. The results show that the vector data processed by the algorithm basically keeps the original shape unchanged, and reduces the redundancy of vector data. At the same time, from the test results, CNN has achieved the best results. Compared with GA (Genetic Algorithm), the accuracy of this method is 3.6% higher. The results verify the reliability of this algorithm. © 2023 IEEE.

关键词： Convolutional Neural Network Data updating Forest resources Source vector data

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