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Features enhancement of micro-service based cab booking system using block-chain 4th

Features enhancement of micro-service based cab booking syst...

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4th international conference on Computational Methods in Science and Technology, ICCMST 2024

作者： Rohit Singh, Neelaksh Shukla, Riya Singh, Ashutosh Kumar Department of Computer Science and Engineering Institute of Engineering and Rural Technology Prayagraj India Department of Computer Science and Engineering United College of Engineering and Research Prayagraj India

ISBN: (纸本)9781032911571

Cab booking services help people order taxis. Existing cab booking services use client server-based architecture. The paper gives a study of the architecture and workings of the Uber cab booking website (Dissanayake, March 18, 2021). It has a micro-service based architecture (Li et al. 2021). Load balancing (Al-Jaroodi et al. 2012) and stream processing (Besnard et al. 2013) are used to handle a large number of requests. The workload is divided among servers using Dispatch Optimization (Abid et al. 2022). It ensures fast responses, easy connection minimal downtime, and efficient use of resources. However, the use of servers increases the cost of service. Rider and driver depend on the server to connect. They don’t know if the system is charging them fairly. It reduces transparency and trust. The paper proposes a blockchain-based cab booking application to solve some of the problems. Trust, transparency, and decentralization can be ensured using blockchain. Transparent and immutable ledgers of blockchain ensure trust and reduce reliance on intermediaries. Smart contracts govern ride management, optimizing efficiency. Blockchain capabilities are used to ensure fair rides, direct interaction of passengers with drivers, and automated payments. The proposed system aims at combining existing technology with blockchain solution to ensure security and transparency along with scalability and quick response time. © 2025 the Author(s).

关键词： Reservation systems

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Sustainable Drone Surveillance system Using Eternal Vertex Cover and Periodic Charging 17

Sustainable Drone Surveillance System Using Eternal Vertex C...

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17th international conference on COMmunication systems and NETworkS, COMSNETS 2025

作者： Dhawde, Navya Chakraborty, Nilotpal Husain Baig, Mirza Galib Anwarul Indian Institute of Information Technology Department of Computer Science and Engineering Guwahati India Indian Institute of Technology School of Mathematical and Statistical Sciences Mandi India

ISBN: (纸本)9798331531195

Unmanned aerial vehicles (UAVs), or drones, are transforming surveillance strategies in various fields, including border security and wildlife conservation. Their ability to monitor large, challenging areas in real time has established them as a valuable tool, particularly in scenarios where traditional surveillance methods face operational and logistical limitations. This research focuses on optimizing drone-based surveillance along the international borders, and in wildlife conservation areas, where challenges like illegal crossings, cattle smuggling, and poaching present serious security and economic threats. Leveraging UAVs provides a cost-effective, flexible, and highly deployable solution that overcomes the limitations of static surveillance systems and limited human patrols. We propose an optimized drone-based system designed to enhance operational efficiency, coverage, and adaptability in these complex environments, with potential applications in various sectors requiring comprehensive, real-time surveillance. We propose modeling the problem using the Eternal Vertex Cover problem, a dynamic extension of the classical Vertex Cover problem. Given the NP-hard nature of determining this cover number, our research explores heuristic and algorithmic approaches to achieve an efficient and scalable solution. We also propose an intelligent charging mechanism for the drones for their continuous operation. All proposed approaches are evaluated using randomly generated datasets as long as benchmark datasets. © 2025 IEEE.

关键词： Drones

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Real Time Monitoring of Bridge by Using Sensor Technology with Concentration on Deflection Identification 1

Real Time Monitoring of Bridge by Using Sensor Technology wi...

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1st international conference on AIML-applications for Engineering and Technology, ICAET 2025

作者： Kokane, Sayali. R. Jadhav, Pramod Bharati VIdyapeeth College of Engineering Department of Computer Engineering Pune India Bharati Vidyapeeth College of Engineering and Research Department of Computer Engineering Pune India

ISBN: (纸本)9798350355611

This research paper inscribes an alarming need for effective bridge health monitoring and controlling amid growing concerns over structural integrity and safety. India has been inherited by n number of rail bridges and roadway bridges over valleys, rivers, hills etc. since british era. Many bridges in urban India near rivers face deterioration over time despite remaining operational. This poses risks to users due to factors like heavy vehicles, rising water levels, pressure variations, and heavy rainfall all potentially leading to collapses and disasters. Apart from these usual factors, earthquake is also one of the most disastrous factor which poses a great risk to the safety and structural integrity of bridges. Hence, it is of an utmost importance that periodic audits of structural integrity and safety of these bridges is critically evaluated. In this study we put forward development of a smart bridge system equipped with a network of sensors controlled using IoT system. We have developed a model prototype of a smart bridge wherein, sensors monitor and responds to variables such as water levels and structural deflections, vibrations, object detection etc. on a real time basis. The sensors we used included flex sensors which monitor deflections, IR sensors to detect objects, water sensors monitoring water level and vibration sensors. In addition to the conventional parameter evaluation, application of the modern sensor based techniques in combination with IoT controlling provide an enhanced system for monitoring of structural integrity and safety of the bridges. Should any monitored parameter exceed its safe threshold signifying a risk of collapse, the system triggers alerts via a monitoring system and activates automatic barriers. Additionally, the controlling system codes provide multidimensional approach of monitoring. This proactive approach aims to enhance safety and prevent potential disasters caused by bridge failures. Daily analysis carried out on the data

关键词： Structural health monitoring

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AI for Smart Farming: Machine Learning Models for Precision Crop Yield Prediction

AI for Smart Farming: Machine Learning Models for Precision ...

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2025 IEEE international conference on Computational, Communication and Information Technology, ICCCIT 2025

作者： Praveen, R.V.S. Maindola, Meenakshi Bhavana, Munugapati Nijhawan, Ginni Raju, Hemanth Bansal, Saloni LTIMindtree Limited Digital Engineering and Assurance Telangana Hyderabad India Graphic Era Deemed to Be University Department of Computer Science & Engineering Dehradun India MLR Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India Lovely Professional University Dept. of Comp. Sc. & Engg. Phagwara India New Horizon College of Engineering Department of Mechanical Engineering Bangalore India GLA University Department of Computer Engineering and Applications Mathura India

ISBN: (纸本)9798331512965

AI and other advanced technologies are gradually beginning to invade the agriculture sector to serve the increasing demand of the consumers for better methods of food production. A key component of precision agriculture, this work focuses on how to use machine learning models to predict crop yields with high accuracy. Specifically, the nature and volatility of the environmental context - such as the nature and quality of soils, as well as the climatic and water conditions - present a major challenge to the application of the conventional modeling approaches aimed at forecasting productive capacity in agriculture. Still, when comparing, the AI-driven models will allow sorting through much information gathered from different sources, including sensors, satellite imagery, and yield history. This work examines the differences of several machine learning models. Such models are the Random Forests, SVMs, and CNNs and other Deep Learning methodologies respectively. A quality model is evaluated based on scalability, computational performance, and prediction accuracy. Also in scope of the study, there is an opportunity to employ IoT together with data collected with remote sensing to make and provide realtime forecasts and evaluations. By the utilization of the results attained, it is established that the yields expected by the machine learning models are much more precise, which aids in enhancing agricultural decision-making concerning resource utilizing, crop handling, and risk minimization. The purpose of this study is focused on the promotion of the agricultural sustainability and production through the development of the innovative data driven farming practices. © 2025 IEEE.

关键词： Smart agriculture

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Design of National Smart Public Health Emergency Management system 24

Design of National Smart Public Health Emergency Management ...

引用

5th international conference on computer Science and Management Technology, ICCSMT 2024

作者： Hu, Hongpu Chen, Qingkun Wan, Yanli He, Qile Gao, Xing Qin, Panpan Yao, Jianhong School of Marxism School of Humanities and Social Sciences Institute of Medical Information Chinese Academy of Medical Sciences Peking Union Medical College Beijing China Institute of Medical Information Chinese Academy of Medical Sciences Peking Union Medical College Beijing China Chinese Academy of Medical Sciences Peking Union Medical College Beijing China

ISBN: (纸本)9798400709999

In order to solve the issues/problems existing in the current public health emergency management system in China, such as imperfect cross-sectoral collaborative management model, incomplete emergency response mechanism caused by long-term medical care and prevention fragmentation, difficulty in early screening, discovery, timely warning and continuous dynamic monitoring of major infectious diseases, ineffective information support, and unformed intelligent emergency management model, we integrated emerging information technologies such as big data (BD) and artificial intelligence (AI) into public health emergency management, designed a new intelligent public health emergency management model, and established an early identification and early risk warning model of public health *** knowledge base and model base of infectious disease prevention and control were built, the intelligent pre-hospital emergency treatment and emergency disposal system were studied, the intelligent public health emergency management platform was developed and pilot application was carried out in order to make up for the shortcomings of traditional emergency management work, realize intelligent public health risk identification, disease prevention and control and emergency handling, and improve public health emergency management service capacity. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Electronic health record

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Cost optimization for computer Numerical Control machining workshop: A queueing modeling approach using the meta-heuristic techniques

Cost optimization for Computer Numerical Control machining w...

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作者： Chahal, Parmeet Kaur Kumar, Kamlesh Department Of Mathematics Central University of Jammu Samba Jammu & Kashmir 181143 India

This research paper introduces an innovative approach to optimize repair of failed computer Numerical Control (CNC) machines within CNC machining workshops by leveraging queueing theory. The proposed model addresses a spectrum of real-world scenarios encountered in manufacturing environments, including CNC machine failures, robotic server breakdowns, reneging behavior of failed CNC machines, and mechanisms to handle unsatisfactory repairs. In this system, failed CNC machines are attended by a single robotic server following a first come first served protocol, while also accounting for potential breakdowns of the robotic server during servicing. The arrival of failed CNC machines is regulated using the F-policy, and repairs to the robotic server are conducted following Bernoulli's p-phases under a threshold recovery (Q) policy. Through the development of steady-state equations of a system and their solutions through matrix-analytic techniques, the distribution of queue sizes within the system is derived. Numerical results are presented graphically to illustrate the influence of various parameters on overall system performance. Additionally, sensitivity analysis on total expected costs are conducted to assess the impact of parameter variations. To optimize system costs, three meta-heuristic approaches are employed: Particle Swarm Optimization(PSO), Ant Colony Optimization(ACO), and Flower Pollination Algorithm(FPA). Comparative analysis of these techniques’ performances is conducted using data generated through their application. This novel combination of theoretical modeling, numerical analysis, and meta-heuristic optimization offers a comprehensive framework for enhancing efficiency and cost-effectiveness in CNC machining workshops. © 2025 international Society of Automation

关键词： Particle swarm optimization (PSO)

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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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AI-Assisted Data modeling and High-Resolution Image Synthesis: An Interactive Framework with Latent Diffusion Model Visualization

AI-Assisted Data Modeling and High-Resolution Image Synthesi...

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2025 international conference on Intelligent Control, Computing and Communications, IC3 2025

作者： Borah, Asha Rani Archana Rani, K. Pushpa Ziara, Sajjad Lakhanpal, Sorabh Vidyadhari, Chalasanvi New Horizon College of Engineering Department of Computer Science Engineering Bangalore India Galgotias university Department of Electrical Electronics & Communication Engineering Uttar Pradesh Gerater Noida203201 India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India College of Medical Technology The Islamic University Radiology Techniques Department Najaf Iraq Lovely Professional University Punjab Phagwara India Griet Department of Information Technology Bachupally Telangana Hyderabad India

ISBN: (纸本)9798331527495

In this research paper, we present the design and implementation of an AI assisted interactive framework for data modeling and high resolution image synthesis that leverages both state of the art latent diffusion models and visualisation of the real-time algorithm. The system proposed enables user to be able to better understand complex data modeling processes and creates high resolution images in the latent space using diffusion. The framework is both interactive, allowing modifications in parameters and real time visualization of change, making it a useful tool both for educational and for advanced AI research. In this paper, we also discuss the underpinning AI-assisted data modeling algorithms, and why they enable efficient data manipulation as well as high quality image synthesis then provide simulation results and practical applications to illustrate the capabilities of the framework of visualizing the latent diffusion process and generating high resolution images. © 2025 IEEE.

关键词： Flow visualization

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A Hybrid GRU-Transformer Model for Financial Forecasting and Risk Management 3

A Hybrid GRU-Transformer Model for Financial Forecasting and...

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3rd international conference on Integrated Circuits and Communication systems, ICICACS 2025

作者： Pradhan, Rahul Alazzam, Malik Bader Keswani, Sarika Bhasin, Narinder Kumar Jaff, Nadhema Ahmed Muthuperumal, S. Gla University Department of Computer Engineering & Applications Mathura India Jadara University Faculty of Information Technology Irbid Jordan Pune India Indian Institute of Banking and Finance Mumbai India College of Administrative and Financial Sciences Knowledge University Department of Business Administration Erbil Iraq K.Ramakrishnan College of Engineering Department of Mathematics Trichy India

ISBN: (纸本)9798331508456

Financial sector demands precise forecasting models to mitigate risk and optimize asset management. This study presents a novel Hybrid GRU-Transformer Model that integrates Gated Recurrent Units (GRUs) for capturing local temporal patterns and the Transformer T5 architecture for modeling global dependencies. Financial datasets sourced from Kaggle, including stock prices and trading volumes, were preprocessed through normalization and categorical encoding, followed by an 80:20 dataset split for training and testing. The proposed model outperformed existing methods such as ARFIMA-LSTM and EMD-CNN-LSTM, achieving superior metrics, including a Mean Squared Error of 0.08 and an R2 of 0.95. Results underline the model's accuracy and robustness in predicting financial risks and trends. By enhancing predictive performance and risk management strategies, this model addresses the dynamic complexities of financial markets. Future research will explore its adaptability across diverse instruments and markets to further its application in real-time forecasting scenarios. The system is implemented using Python integrated with MATLAB. © 2025 IEEE.

关键词： Risk management

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Research and application of Configurable Massive Heterogeneous Data Management system

Research and Application of Configurable Massive Heterogeneo...

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international conference on computer and Automation Engineering, ICCAE

作者： Yunqi Chen CCTEG Chongqing Research Institute Chongqing China

ISBN: (数字)9798331533816

ISBN: (纸本)9798331533823

Effective management and integration of data from multi-source heterogeneous automation subsystems in mines is a current industry problem. Problems such as inconsistent equipment models and inconvenient collection and configuration need to be solved urgently. Analyze the mine's main electromechanical equipment and its attribute information, establish a unified equipment object model and data object model, and develop an Internet of Things equipment sensor monitoring data configuration management system for PLC, OPC, TCP and other protocols. The system has functions such as online visual configuration of equipment object attribute information, autonomous selection of collection protocols, and adaptive configuration of distributed parsing services. Field application shows that the system improves the collection efficiency of massive heterogeneous data, reduces the difficulty of operation and maintenance, and accelerates the construction of intelligent mines, which has certain reference value.

关键词： Visualization Protocols Computational modeling Data integration Configuration management Data collection Data models Maintenance Personnel Monitoring

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