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Efficient Smart Public Transit System Using RFID and IoT integration with MERN web applications

Efficient Smart Public Transit System Using RFID and IoT int...

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International conference on computer, Electrical & Communication engineering (ICCECE)

作者： Kartik Madasanal Anand Gudnavar Sreedevi Nagarmunoli Basavaraj Madagouda Keerti Naregal Department of Computer Science and Engineering Jain College of Engineering and Research Visvesaraya Technological University Belagavi India Department of Computer Science and Engineering Graphic Era University Dehradun India Department of Computer Science and Engineering S.G.Balekundri Institute of Technology Visvesaraya Technological University Belagavi India

ISBN: (数字)9798331513894

ISBN: (纸本)9798331513900

This paper develops a Smart Public Transportation System using RFID technology, IoT integration, and a MERN-based web application for increasing the efficiency, accessibility, and user experience of urban transit systems. It addresses problems such as unreliable bus tracking, lack of support for multilingualism, and ineffective communication between operators and passengers. The key hardware components include RFID tags for bus identification, and IoT-enabled bus stations with RFID scanners, speakers, GSM modules for data transmission, and LCD displays. These ensure accurate real-time updates about the bus locations. On the software side, it is supported by a MERN stack, including MongoDB, ***, ***, and ***, providing a responsive web interface that’s complemented by *** for dynamic route visualization and WebSockets for live updates. Multilingual support through i18next makes it inclusive for various user groups. The system is efficient in that it only updates when RFID scanners capture bus tags at certain checkpoints, thereby reducing server load much more than GPS-based systems. Additional features include route tracking, interactive maps, ticket pricing, and anonymous passenger chats. Crowd-sourced feedback mechanisms and an admin panel for bus management ensure the reliability and scalability of the system. This work shows the feasibility of cost-effective, scalable, and user-centric modernization of public transportation systems, paving the way for further enhancements such as integrated payment systems and AI-based route optimization.

关键词： GSM Real-time systems User experience software Multilingual Internet of Things Servers Reliability Public transportation Radiofrequency identification

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2nd International conference on Bridging the Gap Between AI and Reality, AISoLA 2024

2nd International Conference on Bridging the Gap Between AI ...

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2nd International conference on Bridging the Gap Between AI and Reality, AISoLA 2024

ISBN: (纸本)9783031754333

The proceedings contain 28 papers. The special focus in this conference is on Bridging the Gap Between AI and Reality. The topics include: Responsible and Trusted AI: An Interdisciplinary Perspective;team Design Patterns for Meaningful Human Control in Responsible Military Artificial Intelligence;transparent Transparency Developing a Scheme for Understanding Transparency Requirements;AI Act for the Working Programmer;AI Assisted Programming: (AISoLA 2024 Track Introduction);SEGym: Optimizing Large Language Model Assisted software engineering Agents with Reinforcement Learning;Towards Specification-Driven LLM-Based Generation of Embedded Automotive software;proof Repair Utilizing Large Language Models: A Case Study on the Copland Remote Attestation Proofbase;LLM-Based Scheme for Synthesis of Formal Verification Algorithms;verification and Learning for Assured Autonomy;a Comparison of Monitoring Techniques for Deep Neural Networks;efficient Shield Synthesis via State-Space Transformation;Runtime Verification and AI: Addressing Pragmatic Regulatory Challenges;A Game-Based Semantics for the Probabilistic Intermediate Verification Language HeyVL;Systematic Translation from Natural Language Robot Task Descriptions to STL;it’s Safe to Play While Driving: From a Spatial Traffic Logic Towards Traffic Games;monitoring Safety and Reliability of Underwater Robots: A Case Study;statistical Model Checking the 2024 Edition!;Reinforcement Learning for Discretized Euclidean MDPs;adaptive Stopping Algorithms Based on Concentration Inequalities;digging for Decision Trees: A Case Study in Strategy Sampling and Learning;statistical Analysis of the Impact of Bit-Flips in Security Critical Code;statistical Model Checking of Python Agent-Based Models: An Integration of MultiVeStA and Mesa;On SMC-Based Dependability Analysis in LoLiPoP-IoT Project;Towards Verifying Robotic systems Using Statistical Model Checking in STORM.

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Advancements in Order Independent Transparency: A Survey for Real-Time Rendering Practitioners

Advancements in Order Independent Transparency: A Survey for...

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software engineering and computer Science (CSECS), International conference on

作者： Preetish Kakkar Supreeth Krishna Rao Mauricio Maurer Vijay Mane Electric Sheep Robotics San Jose USA Vishwakarma Institute of Technology Pune India

ISBN: (数字)9798331522216

ISBN: (纸本)9798331522223

Order Independent Transparency (OIT) remains a pivotal challenge in real-time rendering, with applications spanning gaming, simulations, and AR/VR experiences. Traditional techniques, such as Depth Peeling and K-Buffer OIT, have provided foundational solutions to this challenge, while modern approaches like Stochastic Alpha Blending, Weighted OIT with Multi-Frustum, and Deep Learning-Based OIT have introduced innovative pathways to achieve high-quality transparency with improved performance. This survey presents a comprehensive review of these techniques, highlighting their underlying principles, implementation nuances, and trade-offs in terms of performance, memory overhead, and visual fidelity. In addition, this survey examines advanced concepts that push the boundaries of OIT, addressing the growing demands of real-time applications. By providing a detailed analysis of these methods and their suitability for various rendering contexts, this paper aims to serve as a practical guide for researchers and practitioners striving for advancements in real-time transparency solutions.

关键词： Surveys computer science Visualization Reviews Neural networks Rendering (computer graphics) Real-time systems Sorting software engineering

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A Framework for Requirements Modeling of Safety Critical systems: A Continuous Glucose Monitoring System Case Study 22nd

A Framework for Requirements Modeling of Safety Critical S...

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22nd International conference on software engineering Research and Practice, SERP 2024, and 23rd International conference on e-Learning, e-Business, Enterprise Information systems, and e-Government, EEE 2024, held as part of the World Congress in computer Science, computer engineering and Applied Computing, CSCE 2024

作者： Gannous, Aiman Abdunabi, Ramadan Elbarsha, Abdelfattah University of Benghazi Benghazi Libya Colorado State University Fort Collins United States

ISBN: (纸本)9783031866432

Developing safe and reliable systems goes beyond simply specifying what they should do but also understand how they might fail. This paper proposes a framework for capturing both, functional requirements safety requirements of safety-critical systems. Our framework uses Extended Finite State Machines to formally model both types of requirements. We introduce the concept of a "failing state," which is integrated into the normal behavior model, providing a comprehensive view of component operations. To demonstrate the practicality of our framework, we apply it to a safety critical healthcare device: the Continuous Glucose Monitoring System. This case study will show how our approach can enhance the design and analysis of safety-critical systems and ensuring their operation reliability. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： software design

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Industrial Energy Forecasting Using Machine Learning and Plant Activity Metrics

Industrial Energy Forecasting Using Machine Learning and Pla...

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software engineering and computer Science (CSECS), International conference on

作者： Andrew Kidd Michael Short Lindsey Williams Alan Williamson Centre for Sustainable Engineering Teesside University Middlesbrough U.K. Tascomp Ltd. Stockton-upon-Tees U.K.

ISBN: (数字)9798331522216

ISBN: (纸本)9798331522223

This paper reports the development of a prototype AI-driven energy forecasting tool for industrial applications, designed to operate with energy metering systems and plant activity metrics. A time history of real-time plant activity data, which is typically available from SCADA-based asset activity indicators and operational parameters, is utilised along with energy timeseries data within a model regressed to correlate energy consumption with high accuracy. Prototype software was developed as a Windows Forms application and applied to an industrial case study: provision of real-time energy forecasts and optimization insights for a working sawmill are discussed. The application has been designed for future integration with existing SCADA systems, enabling seamless, automated energy monitoring, forecasting and decision support. Future enhancements of the model include incorporating specific production types and more granular operational data to further refine prediction accuracy, and application to profiling energy efficiency of process design options. The work highlights the potential for practical and low-cost AI-powered tools to enhance energy efficiency in modern manufacturing environments and process industries, including small/medium enterprises (SMEs).

关键词： Energy consumption Accuracy Prototypes SCADA systems Machine learning Energy efficiency Data models Real-time systems Manufacturing Forecasting

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Data Frequency Coverage Impact on AI Performance 18

Data Frequency Coverage Impact on AI Performance

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18th IEEE International conference on software Testing, Verification and Validation Workshops, ICSTW 2025

作者： Lanus, Erin Lee, Brian Chandrasekaran, Jaganmohan Freeman, Laura J. Raunak, M.S. Kacker, Raghu N. Richard Kuhn, D. Virginia Tech National Security Institute ArlingtonVA United States Virginia Tech Sanghani Center for Artificial Intelligence & Data Analytics ArlingtonVA United States National Institute of Standards and Technology Information Technology Lab MD United States

ISBN: (纸本)9798331534677

Artificial Intelligence (AI) models use statistical learning over data to solve complex problems for which straightforward rules or algorithms may be difficult or impossible to design;however, a side effect is that models that are complex enough to sufficiently represent the function may be uninterpretable. Combinatorial testing, a black-box approach arising from software testing, has been applied to test AI models. A key differentiator between traditional software and AI is that many traditional software faults are deterministic, requiring a failureinducing combination of inputs to appear only once in the test set for it to be discovered. On the other hand, AI models learn statistically by reinforcing weights through repeated appearances in the training dataset, and the frequency of input combinations plays a significant role in influencing the model's behavior. Thus, a single occurrence of a combination of feature values may not be sufficient to influence the model's behavior. Consequently, measures like simple combinatorial coverage that are applicable to software testing do not capture the frequency with which interactions are covered in the AI model's input space. This work develops methods to characterize the data frequency coverage of feature interactions in training datasets and analyze the impact of imbalance, or skew, in the combinatorial frequency coverage of the training data on model performance. We demonstrate our methods with experiments on an open-source dataset using several classical machine learning algorithms. This pilot study makes three observations: performance may increase or decrease with data skew, feature importance methods do not predict skew impact, and adding more data may not mitigate skew effects. © 2025 IEEE.

关键词： software testing

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Research on the Application of Embedded Real-Time software in computer

Research on the Application of Embedded Real-Time Software i...

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Cybersecurity, Internet of Things and Soft Computing (CITSC), Asia-Europe conference on

作者： Yemei Qi Tianjin University of Technology Tianjin China

ISBN: (数字)9798331504205

ISBN: (纸本)9798331504212

The wide application of computer technology has been deeply integrated into the field of scientific research, engineering design, and across the military technology, diversified industries, and even business, culture, art and entertainment industry. While profoundly affecting People's Daily life, it shows strong vitality and broad application prospects. Therefore, this paper will deeply discuss the embedded real-time software testing, energy consumption research and application practice in the field of computing software design, and reveal its specific advantages in the application process through systematic analysis.

关键词： software testing Energy consumption Technological innovation Systematics Real-time systems User experience Stability analysis Thermal stability System analysis and design Embedded software

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Container Performance in Space systems 25th

Container Performance in Space Systems

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25th International conference on Internet Computing and IoT, ICOMP 2024, and 22nd International conference on Embedded systems, Cyber-physical systems, and Applications, ESCS 2024, held as part of the World Congress in computer Science, computer engineering and Applied Computing, CSCE 2024

作者： Alamgir, Shariar M. Bohra, Dhruv L. Nguyen, Elisabeth A. Embedded and Specialized Computing Department The Aerospace Corporation El SegundoCA United States Software Architecture and Engineering Department The Aerospace Corporation El SegundoCA United States

ISBN: (纸本)9783031859229

Critical embedded software, such as spacecraft flight software, requires high reliability, efficiency, and real-time performance while being capable enough to meet application needs. The increasing prevalence of Linux, and in particular Linux containers, presents opportunities for space systems but also poses potential risks since Linux was not designed to be a real-time operating system. In this study, we conducted a variety of experiments to look at both the overhead imposed by containers and the latency experienced in Linux using various combinations of patched OS and containers running on a Raspberry Pi 4. We found that containers have little impact on CPU utilization but do incur penalties in RAM, disk storage, and startup time. We also found the unpatched Linux kernel performs well for real time;and that, while the real-time kernel patch reduces both overall and maximum latency, it can negatively impact performance, particularly on single-core systems running non-real-time tasks. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Linux

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Real-Time Freeway Traffic Anomalous Event Detection System via Radar Detector Sensors 25

Real-Time Freeway Traffic Anomalous Event Detection System v...

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Proceedings of the ACM/IEEE 16th International conference on Cyber-Physical systems (with CPS-IoT Week 2025)

作者： Austin Coursey Junyi Ji Zhiyao Zhang William Barbour Marcos Quinones-Grueiro Tyler Derr Gautam Biswas Daniel B. Work Institute for Software Integrated Systems Vanderbilt University Nashville TN USA and Department of Computer Science Vanderbilt University Nashville TN USA Institute for Software Integrated Systems Vanderbilt University Nashville TN USA and Department of Civil and Environmental Engineering Vanderbilt University Nashville TN USA Institute for Software Integrated Systems Vanderbilt University Nashville TN USA Department of Computer Science Vanderbilt University Nashville TN USA Institute for Software Integrated Systems Vanderbilt University Nashville TN USA Department of Computer Science Vanderbilt University Nashville TN USA and Department of Civil and Environmental Engineering Vanderbilt University Nashville TN USA

ISBN: (纸本)9798400714986

Undetected anomalous incidents on the freeway, such as crashes, can cause increased congestion and secondary crashes. To address this problem, we recently released a real freeway traffic anomalous event detection dataset. However, our evaluation was limited to a static week of traffic data. This demo presents a live anomaly detection dashboard, processing sensor data with a 1-minute delay. It has interactive components to adjust the anomaly detection performance, providing a realistic evaluation of graph anomaly detection methods for long-term analysis and method improvements.

关键词： anomaly detection

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7th International Russian Automation conference, RusAutoCon 2024

7th International Russian Automation Conference, RusAutoCon ...

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7th International Russian Automation conference, RusAutoCon 2024

ISBN: (纸本)9783031824937

The proceedings contain 37 papers. The special focus in this conference is on Russian Automation. The topics include: Mapping and Path Planning Methods for Highly Automated Vehicles in Agriculture;morphological Analysis and Synthesis Features of Technological Processes;a Modern Method of Wireless Control of Unguarded Railway Crossings;duties and Obligations of the Railway Staff Concerned When the Microprocessorized Contactless Controlling Gauge Device Signal Is Triggered;integration of Automated Management systems for Enterprises’ Transport and Technical Services;development of an Automation Module for Planning Trajectories for Painting Aircraft Fuselage Elements;identification of Metal Sheets in the Flow, Based on the Marking Imprint, Using Neural Networks;study of the Performance of Adaptive Sensor Networks for Collecting and Processing Thermoelectric Data;development and Research of a Cartographic Model for Municipal Planning as the Basis of an Intelligent Geoinformation System;BIM Visual Programming of Bionic Architecture Construction Using Dynamo and Revit;development of a Model and Algorithms for Trigger Control of Technological Processes of Resource Provision;system for Statistical Assessment of Means of Controlling Engineers’ Qualification for Information Support to Manage the Recruiting Process in Industry;smart Enumeration Technology;comparative Analysis of C-Band Conical Horn Antenna Sparse Structures Characteristics at Different Frequencies;software Implementation of Heuristic Methods of Optimization and Integration into a Cloud Service;computer System for Modeling Fluid Flow Around Bodies and Its Potential in Industry;the Effect of Regular and Irregular Segmentations on Characteristics and Charge Distribution Densities of Microstrip Lines;reinforcement Learning with External Teacher for Building Energy Management.

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