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SafeSync: A Comprehensive Safety and Monitoring System for Two-Wheeler Users Using Machine Learning, ESP32, GPS, and GSM 6

SafeSync: A Comprehensive Safety and Monitoring System for T...

引用

6th IEEE International Conference on Recent Advances in Intelligent Computational Systems, RAICS 2024

作者： Sunil, K.S. Adithyan, P. Krishnan, Anjana Hashim Sharaf, C.P. Paul, Jerin John, Salvi Hanna Government Engineering College Dept. of Computer Science & Engg. Kerala Idukki India

ISBN: (纸本)9798350381689

Our work, 'SafeSync' proposes a complete safety and monitoring system aimed to address the considerable hazards encountered by two-wheeler users, such as accidents and rash driving scenarios. Unlike other systems, SafeSync combines powerful technology such as ESP32, GPS, and GSM with an innovative application of machine learning methods. This system specializes in detecting and alerting to accidents, tracking vehicles in real time, and identifying risky driving behaviour. SafeSync goes beyond traditional safety measures by not only identifying ongoing accidents but also forecasting potential events. This predictive feature enables the system to proactively inform users or authorities in advance, assisting in the prevention of accidents. The Flutter-built dedicated mobile app serves as a user-friendly interface, offering real-time updates on the vehicle's status and location. The program also allows users to customise monitoring settings and add parental restrictions. By actively recognizing and warning users to dangerous practises, SafeSync strives to improve rider safety and promote responsible driving behaviour. Finally, the initiative helps overall road safety by providing a solid solution for two-wheeler users to monitor and enhance their road safety. © 2024 IEEE.

关键词： Accident Alert ESP32 GPRS GPS GSM MPU6050 Rash Driving

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Proposed Model for Prediction of Stock Market Price of Netflix

Proposed Model for Prediction of Stock Market Price of Netfl...

引用

2023 International Conference on Artificial Intelligence and Applications, ICAIA 2023 and Alliance Technology Conference, ATCON-1 2023

作者： Patwal, Pratap Singh Srivastava, Anoop Kumar Laxmi Devi Institute of Engineering & Technology Dept. of Computer Science & Engineering Rajasthan Alwar India Aced Alliance University Dept. of Computer Science & Engineering Karnataka Bengaluru India

ISBN: (纸本)9781665456272

Accurate prediction of stock market price is highly challenging. This paper presents a proposed model for prediction of stock market price of Netflix. We have considered a five-year data set (April, 2017 - April, 2022) of Netflix. An Exploratory Data Analysis (EDA) of Netflix's stock price data for predicting its stock market prices using time series is done. The implementation of the model is done using Python language. We imported five-years data and applied several techniques: importing libraries, calculating stock return, line plot, plot all, plot return year wise, plot histogram, plot kernel density, plot box plot, differencing method, resample daily to monthly data etc. EDA proved that using time series technique achieved better results in prediction of stock price and visualizing. © 2023 IEEE.

关键词： Forecasting

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Efficient Path Planning for Emergency Medical Services With Stable Connectivity Demands

Efficient Path Planning for Emergency Medical Services With ...

引用

2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Liu, Wen-Pin Hu, Xuan-Zhang Nguyen, Van-Linh Nguyen, Lan-Huong Hwang, Ren-Hung Dept. of Computer Science and Information Engineering Chiayi Taiwan College of Artificial Intelligence Taiwan

ISBN: (纸本)9798350351255

Currently, online map navigation applications are essential to our daily demands, such as route finding in a big city or booking a taxi trip. Further, the applications also play a pivotal role in finding access to the nearest medical aid in big cities with complex traffic networks. However, existing commercial map programs are unable to provide route suggestions in areas where a continuous network connection is assured, which is essential for distant emergency medical services. This study introduces a highly effective personalized shortest-path algorithm for finding the fastest path of an emergency vehicle (EV) while also ensuring stable network connections for potential remote robotic surgery. By using a customized A-star algorithm, the experimental findings demonstrate that this technique can outperform current search approaches with a 5% shorter path length per 5km. For rescue missions in a large city, the enhancement is remarkable and has the potential to save lives. Due to high compatibility with the existing search algorithms, this method can easily be included as a critical feature for existing commercial map apps. © 2024 IEEE.

关键词： Robotic surgery

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Accessing Visual Information for Divyangjan 4

Accessing Visual Information for Divyangjan

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4th IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2024

作者： Rani, M. S. Divya Ghodke, Hrishikesh Vivekanand Manikandan, M. Manaswini, R. Shivani, K. Dhara, Sri Sai Venkata Gayathri Shreya Presidency University Dept. of Electronics and Communication Engineering Bengaluru560064 India Presidency University Dept. of Computer Science Engineering Bengaluru560064 India

ISBN: (纸本)9798331518981

Approximately 1.3 billion people worldwide suffer from a visual impairment. Typically, they must use Braille to read printed materials. However, when the content is not printed in Braille, these individuals have difficulties. Even though there are a lot of electronic reading aids available, the costs remain prohibitive. Therefore, our work suggests a low-cost document reader that uses a webcam to take pictures of printed materials. The Optical Character Recognition (OCR) framework's image-to-text conversion is then used to turn the acquired image into text. Finally, the Text to Speech (TTS) framework's text-to-speech conversion will be used to read the text aloud in speech format. Consequently, a person with a visual impairment can use hearing rather than touch to comprehend printed materials that are not written in Braille. Users may view documents printed in five different languages. The choice of different document sizes is this work's greatest novelty. The system is equipped with a Raspberry Pi, Arduino Uno, NEMA 17 stepper motors, a web camera and speaker. The Raspberry Pi, Arduino Uno, NEMA 17 stepper motors, webcam, and speaker are all part of the system. © 2024 IEEE.

关键词： Stepping motors

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A Machine Learning Model for Predicting Internet Addiction in Teenage and Young Students 3

A Machine Learning Model for Predicting Internet Addiction i...

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3rd IEEE World Conference on Applied Intelligence and Computing, AIC 2024

作者： Johar, Geetika Patel, Ravindra University Institute of Technology Rgpv Dept. of Computer Science & Engineering Bhopal India University Institute of Technology Rgpv Dept. of Computer Applications Bhopal India

ISBN: (纸本)9798350384598

Internet addiction is becoming one of the critical issues among teenagers and young university students. This habit not only negatively impacts the student's learning performance, but also affects the student's physical and mental health. This paper is focusing on designing a Machine Learning (ML) model for accurately identifying internet addiction. The model incorporates data preprocessing and feature selection techniques for reducing the computational complexity. Next, five different ML algorithms have been implemented and compared to identify appropriate ML algorithms. The identified ML model has been trained using the behavioral features of the students for predicting internet addiction. The experiments have been carried out and the performance of the models has been measured. The results demonstrate that a random forest classifier provides 83% accurate detection for university students and 96% accurate results are provided by an SVM-based classifier for teenager internet addiction detection. Therefore, by using the entire observation of experiments it is found that the proposed model can successfully identify internet addiction in students by analyzing the student's behavioral features. © 2024 IEEE.

关键词： Contrastive Learning

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Machine Learning Approaches for Predictive Channel State Information in MIMO Systems Using LSTM 2

Machine Learning Approaches for Predictive Channel State Inf...

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2nd International Conference on Advanced Computing and Communication Technologies, ICACCTech 2024

作者： Upadhyay, Deepak Sharma, Amulya Gupta, Mridul Devgan, Divyansh Garg, Shobhit Upadhyay, Abhay Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Graphic Era Deemed to be University Dept. of Management Studies Dehradun India

ISBN: (纸本)9798331519056

In this paper, we analyse machine learning models, including Long Short-Term Memory networks, to predict the CSI and evaluate their impact on adaptive transmission in MIMO systems. To achieve this objective, we use simulation to generate CSI data in a MIMO environment and compare the performance of ML models to traditional methods. Our simulation reveals using our dataset that LSTM models improve the SNR values significantly, which means that their predictions are more accurate. At the same time, these models require greater computational and other resources. In contrast, despite its relative inefficiency in comparison with LSTM, Decision Trees improve the SNR moderately while consuming fewer resources but needing a substantial amount of time. Analysis of the source tries to examine the balance between performance and resource usage may validate the use of ML-based methods, and especially LSTM, to predict the CSI advancedly, but the actual application must take constraints into account. © 2024 IEEE.

关键词： Contrastive Learning

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Transformer based Compressed Data Recovery for Efficient Data Collection in Wireless Sensor Networks

Transformer based Compressed Data Recovery for Efficient Dat...

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2024 IEEE Students Conference on engineering and Systems, SCES 2024

作者： Balaji, V.S. Sekar, K. Devendar Rao, B. Dheepa, T. Rajalakshmi Engineering College Dept. of Artificial Intelligence and Machine Learning Chennai India Kongunadu College of Engineering and Technology Dept. of Computer Science and Engineering Tiruchirappalli India

ISBN: (数字)9798350374711

ISBN: (纸本)9798350374711

Data collection is challenging in wireless sensor networks (WSNs) since energy consumption remains a significant constraint. Although energy consumption has increased, most data collection methods incur excessive computation overhead. Compressive sensing is used to minimize the number of sensing samples with a suitable sparse basis. A novel Transformer neural network-based compressed data recovery (TCDR) method has been proposed for extracting temporal correlation structures from compressed signals and reconstructing them with high accuracy. The compressed signal is forwarded to the base station through multi-hop communication. The base station uses an attentionbased Transformer Neural Network (TNN) to recover the compressed signal. This model provides greater energy saving performance than the other baseline models considered for evaluation, which are 5.23 percent, 6.82 percent, 10.26 percent, and 11.47 percent, respectively. © 2024 IEEE.

关键词： Spatio-temporal data

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Experimental Validation of Blockchain Based Triple Branch MRC for Secured Communication in Adverse Fading Conditions

Experimental Validation of Blockchain Based Triple Branch MR...

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2024 IEEE Region 10 Symposium, TENSYMP 2024

作者： Upadhyay, Deepak Upadhyay, Abhay Gupta, Mridul Sharma, Kunj Bihari Maindola, Meenakshi Garg, Shobhit Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era Deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Graphic Era Deemed to be University Dept. of Management Studies Dehradun India

ISBN: (纸本)9798350364866

The investigation in this study entails integrating blockchain technology with maximal ratio combining in a triple branch configuration for secure communications under multipath fading conditions. The proposed combines blockchain's decentralized and immutable characteristics with MRC's communication outcomes and flaws, which are worsened by the multipath fading channels. To evaluate this, the team carried out various empirical tests with the key findings being the Signal-to-Noise Ratio performance. Since the blockchain integrated system is anticipated to exhibit a higher SNR, our results showed a substantial increase in SNR. This confirms the robust and secure communication capabilities of the integrated solution under study. Therefore, the researchers demonstrate how blockchain can greatly enhance security as well as the quality of the communication, presenting a better solution in challenging data transmission conditions. This study establishes the foundation for further research on blockchain technology applications in the communication field. © 2024 IEEE.

关键词： Blockchain

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Secured Release through an Agile Security Growth Framework 29

Secured Release through an Agile Security Growth Framework

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29th ISSAT International Conference on Reliability and Quality in Design, RQD 2024

作者： Bhattacharya, Saikath Williams, Laurie Singh, Munindar P. Electrical Engineering and Computer Science Milwaukee School of Engineering Milwaukee United States Dept. of Computer Science North Carolina State University Raleigh United States

ISBN: (纸本)9798986576138

Software development teams need to produce and assess secure software products so that they can perform critical functionality. Because no software product can ever be "perfectly secure, " development teams need to decide when a software product is "secure enough" to be released, that is, to make a decision on the product’s release readiness. The goal of this paper is to aid software practitioners in predicting whether a software product is "secure enough" to be released through the evolution and evaluation of software security growth models (SSGM). In this paper, we adapt and evolve software reliability growth models (SSGMs) for the purpose of SSGM using empirical software vulnerability analysis. We quantitatively compare the quality of agile software versions by comparing the security correction and detection process over testing time and software testing cost. The framework is generic to incorporate software vulnerability data into different time frames and multiple agile software versions. We evaluated our SSGM using data from Google Chromium, which uses an agile process with releases every 50 days. © Conference Proceedings of the 29th ISSAT International Conference on Reliability and Quality in Design, RQD 2024.

关键词： Software quality

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The Low-Complexity Timing Synchronization Circuits for IEEE 802.15.4a/z IR-UWB Systems 6

The Low-Complexity Timing Synchronization Circuits for IEEE ...

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6th IEEE Novel Intelligent and Leading Emerging sciences Conference, NILES 2024

作者： Wang, Kuan-Wei Shen, Chung-An Huang, Chin-Ya National Taiwan University of Science and Technology Electronic and Computer Engineering Dept. Taipei Taiwan

ISBN: (纸本)9798350378511

This paper presents the design and implementation of a low-complexity timing synchronization circuit for the IEEE 802.15.4a/z IR-UWB wireless communication standard. The circuit structure of a low-complexity correlator for complex ternary values is designed. Moreover, a two-stage synchronization approach is utilized for a more accurate sample alignment. Therefore, a balance between the performance of synchronization and hardware complexity is achieved. The proposed synchronization architecture is designed and implemented based on the Xilinx ZC706 FPGA platform. The experimental results show that the proposed design saves 74% of buffer and 87.4% of multiplier utilization. © 2024 IEEE.

关键词： Ultra-wideband (UWB)

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