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Decentralized Cab Booking Application Utilizing Blockchain, Smart Contracts and Oracle Networks

Decentralized Cab Booking Application Utilizing Blockchain, ...

引用

2024 International conference on Knowledge Engineering and Communication Systems, ICKECS 2024

作者： Kaviraj, J. Jebaraj, Joesh R. Sabaresan, V. St. Joseph's Institute of Technology Dept. of Computer Science Chennai India

ISBN: (纸本)9798350359688

Traditional cab booking applications suffer from many issues, including centralized control, data vulnerabilities, and high operational costs paid to companies. These limitations necessitate a transition towards decentralized alternatives to address the growing need for more efficient, cost-effective, and secure transportation services. This paper presents an idea that uses blockchain technology to improve the cab booking system. In the proposed system, the aim is to eliminate central authorities, offering an array of benefits such as enhanced security, reduced costs, and increased transparency throughout the booking process. To achieve this, smart contracts are employed to automate and secure transactions. The client-side page is deployed to the InterPlanetary File System (IPFS) for improved accessibility and redundancy. Additionally, the creation and utilization of oracle networks for real-time, trustworthy location data are suggested. The approach represents a paradigm shift in the transportation industry, ensuring data privacy, cost-efficiency, and transparency while eliminating the need for centralized intermediaries. Through the integration of smart contracts, IPFS, and oracle networks, a promising path towards a decentralized and secure cab booking ecosystem is offered. © 2024 ieee.

关键词： Smart contract

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Playing Cards Classification and Detection Using Sequential CNN Model Through Machine Learning Techniques Using Artificial Intelligence

Playing Cards Classification and Detection Using Sequential ...

引用

2024 International conference on E-Mobility, Power control and Smart Systems, ICEMPS 2024

作者： Mittal, Khushi Gill, Kanwarpartap Singh Chauhan, Rahul Sharma, Manish Sunil, G. Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Graphic Era Hill University Computer Science and Engineering Uttarakhand Dehradun India Graphic Era Deemed To Be University Computer Science & Engineering Uttarakhand Dehradun248002 India School of Computer Science & Artificial Intelligence SR University Warangal India

ISBN: (纸本)9798350394399

The task of identifying and classifying playing cards within images or video streams in computer vision involves employing a Sequential Convolutional Neural Network (CNN) model. This process combines image categorization and object recognition, presenting a sophisticated and engaging implementation of machine learning techniques. The significance of classifying and detecting playing cards extends to artificial intelligence and computer vision, with numerous practical applications. Systems for classifying and detecting playing cards utilizing artificial intelligence (AI) rely on computer vision methods and deep learning algorithms to achieve precise identification and categorization. These technological solutions not only enhance automation and efficiency across various tasks but also open up new possibilities for interaction and enjoyment in the domain of playing card games, making them accessible and engaging in diverse industries and user experiences. The primary objective of this research is to categorize playing cards and predict their expected accuracy, targeting a result of 75 percent. The high level of accuracy demonstrated in this study holds potential benefits for future researchers exploring this technology and subject matter. © 2024 ieee.

关键词： Computer vision

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State of Charge Estimation for Lithium Batteries Based on the Square Root Cubature Kalman Filter Algorithm 4

State of Charge Estimation for Lithium Batteries Based on th...

引用

4th International conference on Energy Engineering and Power Systems, EEPS 2024

作者： Liu, Hanhan Su, Jun School of Electrical Engineering and Automation Xiamen University of Technology Xiamen China Xiamen University of Technology Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control Xiamen China

ISBN: (纸本)9798350366914

The State of Charge of lithium batteries is a crucial parameter for the battery management system in electric vehicles and energy storage applications. Accurate estimation of the State of Charge is of significant importance for the design of the battery management system. To address the problem of accurately estimating the State of Charge, this paper employs the square root cubature Kalman filter algorithm in conjunction with a second-order resistance-capacitance equivalent circuit model of lithium batteries for precise State of Charge estimation. This study utilizes the open-source experimental dataset of the Panasonic NCR18650PF lithium battery and identifies the parameters of the second-order resistance-capacitance equivalent circuit model through the forgetting factor recursive least squares method. To verify the estimation accuracy of the Square Root Cubature Kalman Filter algorithm, the algorithm is simulated and tested using the Urban Dynamometer Driving Schedule conditions within the experimental dataset. The estimation accuracy of the Square Root Cubature Kalman Filter algorithm is compared with that of the Extended Kalman Filter algorithm and the Unscented Kalman Filter algorithm under the same conditions. Simulation test results indicate that the Square Root Cubature Kalman Filter algorithm achieves higher accuracy in estimating the State of Charge of lithium batteries. © 2024 ieee.

关键词： State of charge

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Ultra-wideband Non-line-of-sight Recognition Method Based on MTF-CNN 21

Ultra-wideband Non-line-of-sight Recognition Method Based on...

引用

21st International conference on Networking, Sensing and control, ICNSC 2024

作者： Wang, Yipeng Zhou, Jinglong Yang, Anning Li, Wenfeng School of Transportation and Logistics Engineering Wuhan University of Technology Wuhan China

ISBN: (纸本)9798350365221

Ultra-wideband (UWB) technology has been extensively researched due to its promising potential in indoor positioning applications. However, the complexity of indoor environment inevitably leads to obstruction of UWB signals by various objects, including walls, metal doors, and wooden panels, during transmission. This results in a non-line-of-sight (NLOS) effect in UWB signals, which in turn reduces positioning accuracy. Therefore, recognizing NLOS is crucial for enhancing the positioning accuracy of UWB systems. This paper proposes a straightforward method to identify NLOS conditions caused by various obstacles obstructing UWB signals. Firstly, the channel impulse response (CIR) of UWB signals is extracted and analyzed. Further, the CIR data are transformed into a two-dimensional feature image using a method of Markov transition field (MTF), which is then recognized by a convolutional neural network (CNN) model. Finally, experiments are conducted to validate the reliability of the proposed method in both dynamic and static scenarios. The results demonstrate that the recognition accuracy of the MTF-CNN model proposed in this paper is 98.67% in the static scenario, and 92.5% in the dynamic scenario. © 2024 ieee.

关键词： Ultra-wideband (UWB)

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Secured and Transparent Transactions Using IOTA Tangle Distributed Ledger technology in Dairy Supply Chains

Secured and Transparent Transactions Using IOTA Tangle Distr...

引用

2024 International conference on E-Mobility, Power control and Smart Systems, ICEMPS 2024

作者： Raman, Sajeesh Eringotkavil Venkatramaraju, D. School of Management and Commerce Bharath Institute of Higher Education and Research Tamil Nadu Chennai India

ISBN: (纸本)9798350394399

In order to improve the safety and openness of transactions, particularly in the context of dairy supply chains, this study incorporates cutting-edge cryptographic and consensus techniques into the IOTA Tangle. The major objective is to improve upon the Tangle agreement method, the method used to reach agreement on the IOTA Tangle, by including novel techniques such MCMC (Markov Chain Monte Carlo) Tip Selection. The purpose of this enhancement is to improve the speed and accuracy of validating Tangle transactions. IOTA Proof of Work (PoW) and the Curl-P Hash Function are being investigated for their potential to strengthen the Tangle's cryptographic underpinnings and hence make it a more secure distributed ledger. The primary goal of this study is to develop a protocol for honest dealings that can be used to safeguard and track the origin of dairy products all along their supply chains. This study is unusual since it is the first to do such a thorough analysis of these cryptographic and consensus components, providing insights into their synergistic ability to solve security issues and guarantee transaction integrity in real-world applications. © 2024 ieee.

关键词： Supply chains

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Design and Prototyping of Queuing Conveyer Belt System Based on Low-Cost Open-Source Microcontroller 10

Design and Prototyping of Queuing Conveyer Belt System Based...

引用

10th International conference on Smart Computing and Communication, ICSCC 2024

作者： Abiyasa, Agus Putu Sugara Yasa, I Wayan Asna, I Made Gede Adrama, I Nyoman Riko, I Made Universitas Pendidikan Nasional Department of Electrical Engineering Denpasar Indonesia Institute of Material Research and Engineering Agency for Science Technology and Research Singapore Singapore

ISBN: (纸本)9798350363104

This study presents the design, implementation, and testing of a conveyor belt system aimed at queuing passenger luggage in airport terminals, with a focus on optimizing efficiency and passenger experience during pre-flight procedures. The system comprises three conveyors equipped with sensors and control mechanisms to automate luggage sorting and positioning. An Arduino Uno microcontroller and infrared sensors are utilized to prototype the model. Testing is conducted under various scenario conditions to assess the system's performance, including different passenger traffic volumes and environmental factors. Additionally, the system is designed to operate under normal and emergency conditions, with manual override functionality activated by an emergency button. Results demonstrate the system's ability to adapt to dynamic operational environments, enhancing operational efficiency and passenger satisfaction in airport terminals. Overall, this study contributes to the advancement of airport baggage handling technology, with potential applications for improving airport operations worldwide. © 2024 ieee.

关键词： Microcontrollers

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Design, Manufacturing, Modelling, and control of a Cable-Driven Parallel Robot for Additive Manufacturing 19

Design, Manufacturing, Modelling, and Control of a Cable-Dri...

引用

19th ieee International conference on Automation Science and Engineering, CASE 2023

作者： Duan, Molong Feng, Jiaquan Liu, Shuai Hong Kong University of Science and Technology Hong Kong Hkust Shenzhen-Hong Kong Collaborative Innovation Research Institute Futian Shenzhen China

ISBN: (纸本)9798350320695

The cable-driven parallel robots are desirable for the manufacturing of large-scale structures due to their enhanced level of flexibility. This is particularly appealing in future construction industry additive manufacturing, where the system can be conveniently deployed at different locations with minimum setup change. This paper proposed a cable-driven parallel robot prototype design for additive manufacturing applications. The cable-driven parallel robot has 6 degrees of freedom and is thus capable of performing translational and rotational manipulation. To address the tension-induced inaccuracies in actuating the cable-driven robot, this paper presents a compensation method to consider the tension force and positioning error by modifying the trajectory and its geometrical relationships. Enhanced positioning performances and the 3D printing results are verified through experiments. © 2023 ieee.

关键词： 3D printing

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AR GuideX: Indoor Wayfinder 4

AR GuideX: Indoor Wayfinder

引用

4th International conference on Power, Energy, control and Transmission Systems, ICPECTS 2024

作者： Kamala, B. Sankar, Shiva Sujay, R. Ranjani, J. Sri Sairam Engineering College Department of Information Technology Chennai India

ISBN: (纸本)9798331508845

Indoor navigation systems using augmented reality (AR) aim to help users navigate through indoor spaces such as buildings, airports, malls, and exhibition centers. These systems can use various technologies, including GPS, Bluetooth, and Wi-Fi, to determine the user's location and provide them with visual and auditory directions to their destination. AR-based indoor navigation systems can also be tailored to the needs of specific users or environments. One of the main benefits of AR-based indoor navigation systems is that they can provide users with a more intuitive and immersive experience compared to traditional methods such as paper maps or visual displays. By overlaying digital information onto the user's physical environment, AR systems can make it easier for users to understand their surroundings and find their way around. Overall, AR-based indoor navigation systems have the potential to improve the user experience and efficiency of navigating indoor spaces and may have a variety of applications in different settings. © 2024 ieee.

关键词： Indoor positioning systems

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Performance Optimization of Inverted-T SSOI FinFET for RF applications 9

Performance Optimization of Inverted-T SSOI FinFET for RF Ap...

引用

9th International conference on Integrated Circuits and Microsystems, ICICM 2024

作者： Zhang, Bo Zheng, Siying Zhou, Jiuren Liang, Jie The School of Micro-Electronics Shanghai University Shanghai China Xidian University Emerging Device and Chip Laboratory Chip Laboratory Hangzhou China

ISBN: (纸本)9798331509453

In this paper, the analog and RF performance of inverted-T FinFET (IT-FinFET) transistor are investigated using TCAD simulation. Compared with 14 nm FinFET, the device increases the channel width under a given layout area, so that the on-current increases by about 300%. The electrostatic control capability is optimized by adjusting the device structure. The work functions of SOI region and fin region of the device are respectivelyset to make threshold voltages of horizontal and vertical channels consistent. reduces the subthreshold slope (SS) to 73.3 mV/decade. We have used strained Siicon as material for the device to further increase the on-current (Ion and trans-conductance (Gm). The Gm is increasd to 0.35 mSum. Thanks to the Inverted-T structure, the cut-off frequency (fT) increases 10%, mainly due to increase in transconductance and decrease parasitic capacitance. Without the backgate bias, the fT achieves 389 GHz. Additionally, as the backgate voltage is incremented to 2 V, the fT increases to 397 GHz. © 2024 ieee.

关键词： FinFET

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Detecting Plant Leaf Diseases with Convolutional Neural Networks (CNN) and Deployment via Hugging Face 4

Detecting Plant Leaf Diseases with Convolutional Neural Netw...

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4th International conference on Power, Energy, control and Transmission Systems, ICPECTS 2024

作者： James, T. Prabahar Godwin Pathmanaban, J. Vivekanandan, G. Anantha Karthigeyan, M.S. Deepak, R. Abdul Kalam, J. Sri Sai Ram Institute of Technology Computer Science and Engineering Chennai India

ISBN: (纸本)9798331508845

Ensuring food security relies heavily on agriculture, and any threat to crop health can significantly impact local economies and populations. Detecting and addressing plant diseases early poses a challenge for farmers. This study presents a novel approach for identifying leaf diseases in plants, focusing specifically on tomato and potato leaves. A deep learning model using Convolutional Neural Networks (CNN) was developed with 91% accuracy to recognize up to 13 different diseases affecting these plants. The dataset used includes high-resolution images of both healthy and diseased leaves, enabling precise classification. The model is deployed on Hugging Face, making it accessible and scalable for real-time applications in assisting farmers and agricultural specialists with disease detection and prevention. This solution enhances crop health monitoring, leading to improved agricultural productivity and reduced pesticide usage, contributing to precision agriculture and sustainable farming practices. © 2024 ieee.

关键词： Agricultural technology Convolutional Neural Network Deep Learning Hugging Face Image Classification Plant Disease Detection Precision Agriculture Sustainable Farming Practices Tomato Leaf Disease

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