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Hydro-Environmental Autonomous Cleaning System (HEACS)

Hydro-Environmental Autonomous Cleaning System (HEACS)

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2025 IEEE international Students' conference on Electrical, Electronics and computer Science, SCEECS 2025

作者： Ingale, Kiran Junghare, Rugved Jadhav, Atharva Jain, Rishi Jadhav, Digvijayy Jadhav, Tanaya Jasuja, Ishita Vishwakarma Institute of Technology Department of Multidisciplinary Engineering Pune India

ISBN: (纸本)9798331529833

The Hydro-Environmental Autonomous Cleaning System (HEACS) addresses the critical issue of water pollution by autonomously collecting waste from water bodies and monitoring water quality. This system integrates a conveyor belt mechanism powered by DC motors for efficient waste collection, including oil spills. Water quality is maintained using Total Dissolved Solids (TDS) sensors, which trigger the injection of purifying chemicals like 777 Bioconcentrate, chlorine dioxide, Copper Sulphate, or Aluminium Sulphate when necessary. Collected garbage weight is measured using load sensors, with real-time data displayed on an LCD connected to an Arduino Uno. Autonomous navigation and operation are managed via Rx/Tx modules, ensuring effective performance in various environmental conditions. HEACS offers a comprehensive solution for water pollution control, combining automation, effective waste management, and environmental monitoring to protect aquatic ecosystems. © 2025 IEEE.

关键词： Oil spills

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Integrated and Intelligent Elder-Friendly E-commerce Framework using NLP Techniques

Integrated and Intelligent Elder-Friendly E-commerce Framewo...

引用

2025 IEEE international Students' conference on Electrical, Electronics and computer Science, SCEECS 2025

作者： Sivasanjith, G. Mohan Prabhu, N. Hemaswathi, S. Rajkumar, P. Rajeshkannan, C. Dhivya, R. Kare Dept. of Information Technology Krishnankovil India Artificial Intelligence and Data Science Indra Ganesan College of Engineering Tiruchirappalli India Mount Zion College of Engg. and Tech. Dept. of Computer Science and Engg. Pudukottai India Suguna College of Engineering Dept. of Computer Science and Engg. Coimbatore India M.Kumarasamy College of Engineering Dept. of Information Technology Karur India

ISBN: (纸本)9798331529833

All over the world, the population of elderly people is increasing a lot. There needs to be special attention to the welfare of the elderly person to make them confident in their independent quality of living. In recent years, researchers have shown much interest in smart home automation for people who live alone without any human assistance. However, the purchase of medical drugs, diapers, etc., outside the house has to be fulfilled by their family members or caretakers. In most cases, it is not feasible, as the family members may stay long away from the elders. Purchasing online is easy;however, analyzing the best product requires knowledge in each e-commerce application for better quality at a low cost. This paper proposes an integrated and intelligent e-commerce framework to avoid the drawback of purchasing items online in a single window using the NLP technique. The proposed framework provides offers, discounts, star ratings, and product reviews by analyzing other customers' review data and purchase patterns. It provides interactive data analysis at a single window for the ease of elderly persons. The performance of the proposed framework was evaluated by 120 elderly persons using a simple questionnaire with a statistical analysis of a sample purchase. © 2025 IEEE.

关键词： Recommender systems

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Literature review on the implementation of Robotic Process automation in healthcare and its social influence 16

Literature review on the implementation of Robotic Process A...

引用

16th international conference on ENTERprise Information Systems, CENTERIS 2024 - 12th international conference on Project MANagement, ProjMAN 2024 - 14th international conference on Health and Social Care Information Systems and Technologies, HCist 2024

作者： Patrício, Leonel Costa, Carlos Varela, Leonilde Silveira, Zilda Cruz-Cunha, Maria Manuela Universidade Do Minho Department of Production and Systems Guimarães4804-533 Portugal ALGORITMI Research Centre Universidade Do Minho Guimarães4804-533 Portugal Bambuí Brazil Department of Mechanical Engineering Sao Carlos School of Engineering Sao Paulo Brazil 2Ai-Applied Artificial Intelligence Laboratory Polytechnic Institute of Cávado and Ave Portugal

This article presents a literature review on the implementation of Robotic Process automation (RPA) in healthcare and its social influence. RPA is an emerging technology that automates repetitive and rule-based processes, providing greater efficiency and cost reduction. In the healthcare sector, RPA has the potential to transform administrative operations, improve data accuracy, and free up professionals to focus on patient care. This systematic review examines recent studies on the benefits and challenges of adopting RPA in healthcare, with a particular focus on its sustainability and social impact. The findings indicate that while RPA can offer significant operational and economic improvements, its implementation also raises ethical and social issues, such as the potential replacement of jobs and the need for workforce reskilling. It is concluded that a balanced and well-planned approach is essential to maximize the benefits of RPA in healthcare while mitigating its potential adverse consequences. © 2025 The Author(s).

关键词： Cost reduction

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Artificial Intelligence Techniques for the Ransomware Detection: Current Methods and Challenges 1

Artificial Intelligence Techniques for the Ransomware Detect...

引用

1st international conference on AIML-Applications for engineering and Technology, ICAET 2025

作者： Rakibe, Priya Jawale, Madhuri Computer Engineering Research Centre Sanjivani College of Engineering Kopargaon Savitribai Phule Pune University Pune India Sanjivani College of Engineering Kopargaon Savitribai Phule Pune University Dept. of Information Technology Pune India

ISBN: (纸本)9798350355611

Recently, Artificial Intelligence (AI) Techniques have received significant interest across the different fields for data analysis and decision-making. Ransomware detection using AI has been a challenging research problem for the last decade in hybrid communication systems like blockchainintegrated Internet of Things (IoT) architectures. Ransomware is a form of malicious software that restricts access to a victim's resources by altering system login credentials or encrypting digital data. Consequently, typical approaches used to identify other types of threats are inadequate for recognizing ransomware. Different AI techniques recently have been used for the detection of such threats, but an appropriate level of accuracy and minimum false rate with automation are vital challenges. This study presents a systematic review of the current methods for ransomware detection using different AI techniques. The ransomware detection methods under categories such as rule-based, machine learning-based, and deep learning-based are reviewed in this study. The comparative analysis of these methods is provided quantitatively and qualitatively. As per the recent progress in the domain of ransomware detection, the current research problems are identified and discussed as the outcome of the study. The roadmap for future work is described as the research gap analysis output. © 2025 IEEE.

关键词： Adversarial machine learning

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Reinforcement Learning Based Optimization of Autonomous Aircraft Performance 11

Reinforcement Learning Based Optimization of Autonomous Airc...

引用

11th international conference on Mechatronics and Robotics engineering, ICMRE 2025

作者： Sari, Metin Caliskan, Fikret Istanbul Technical University Department of Mechatronics Engineering Istanbul Turkey Turkish Aerospace Industries Ankara Turkey Istanbul Technical University Department of Control and Automation Istanbul Turkey

ISBN: (纸本)9798331509293

This research introduces an advanced flight control system for optimizing autonomous aircraft performance, leveraging deep reinforcement learning (DRL) to address the complexities of nonlinear flight dynamics. Using a six-degree-of-freedom (6-DoF) rigid aircraft flight dynamics model, we develop a Deep Deterministic Policy Gradient (DDPG) controller tailored for waypoint navigation and attitude stabilization tasks. A custom reward framework and extensive hyperparameter tuning enable effective training within a high-fidelity MATLAB/Simulink environment, achieving high rewards and precise control. Although computationally intensive, the simulations demonstrate robust performance across diverse flight conditions, with potential for real-world applications and future extensions to multi-agent scenarios. © 2025 IEEE.

关键词： Deep reinforcement learning

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Research and Application of computer Vision and Predictive Maintenance in Health Management of Conveying Equipment 3rd

Research and Application of Computer Vision and Predictive M...

引用

3rd international conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

作者： Long, Zhongyi Gao, Fan Tang, Li Hunan Valin Xiangtan Iron and Steel Co. Ltd. Xiangtan China ChongQing ChuanYi Automation Co. Ltd. Chongqing China

ISBN: (纸本)9789819616930

As an indispensable part of realizing mechanization and automation of handling system in ports, metallurgy, chemical, thermal power, building materials and other fields, conveying equipment faults account for 50% of delivery system faults. In order to improve the maintenance mode of conveying equipment based on manual inspection and record, this paper deals with the research and application of computer vision and predictive maintenance in health management of conveying equipment. Firstly, based on the research of mechanical structure of conveying equipment drive unit, failure cause analysis of conveying equipment and overview of common detection techniques were introduced. Secondly, an health management system based on computer vision and predictive maintenance was designed, the computer vision model was built based on Pangu large-sized model and trained by artificial intelligence training platform, and StressWave analysis method was applied for predictive maintenance of conveying equipment driving unit. In the application case of main belt of blast furnace and the key belt of sintering in the iron making process, this health management system issue alarms accurately and timely, minimize the impact of unplanned downtime on the production process, resulting in significant economic and social benefits. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Predictive maintenance

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Automated execution algorithm for smart contracts in payment systems based on blockchain and big data 4

Automated execution algorithm for smart contracts in payment...

引用

4th international conference on computer Vision, Application, and Algorithm, CVAA 2024

作者： Lin, Shuhong Ruan, Juanping Chen, Lihong Lin, Yishan Zou, Limei Pan, Liumei Fu Jian Yi Li Dian Li Ke Ji Co. Ltd. Fuzhou350001 China State Grid Info & Telecom Group Fuzhou350001 China

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

Smart contracts, as one of the important applications of blockchain technology, provide the possibility for automated execution of payment systems. This article explores an automated execution algorithm for smart contracts in payment systems based on blockchain and big data technology to address the issues of low accuracy and efficiency in contract execution. This algorithm utilizes the immutability and decentralization features of blockchain to ensure the security and transparency of payment transactions. At the same time, combined with the powerful analytical capabilities of big data, deep mining of transaction data is carried out to achieve accurate prediction and risk management of transactions. The automated execution function of smart contracts further simplifies the transaction process, reduces human intervention, and improves the efficiency and reliability of payment systems. The experimental results show that through the proposed algorithm, the payment system can provide more secure, efficient, and personalized services, promoting the digital transformation and development of the financial transaction field. © 2025 SPIE.

关键词： Blockchain Data modeling Data processing automation computer security Data storage Transparency Data communications Statistical modeling Symmetric key encryption

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Cloud-Based AI Solutions for Personal Finance Management

Cloud-Based AI Solutions for Personal Finance Management

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2025 international conference on Pervasive Computational Technologies, ICPCT 2025

作者： Chhabra, Gurpreet Kaur Mishra, Ashutosh Kumar Tyagi, Varsha Mani, Chandra Tyagi, Vani Sagar, Pramod Kumar Management Education and Research Institute Department of Management Delhi India Srm Business School Department of Management UP Lucknow India Raj Kumar Goel Institute of Technology Computer Science & Engineering UP Ghaziabad India Mangalmay Institute of Engineering & Technology Computer Science & Engineering Greater Noida India

ISBN: (纸本)9798331508685

Cloud-based AI answers for private finance control are out-of-the-field tools that leverage synthetic intelligence and cloud computing technologies to manage people's money higher. In this article, I have described various solutions with features ranging from budgeting to personalized financial planning and investment suggestions. Utilizing superior system learning algorithms and cloud-based AI solutions can help understand an individual's fiscal information, including expenses, profits, or savings transactions, for generating personalized insights and advice. This lets people learn about their spending habits and make more informed financial choices. Through the power of the cloud, these solutions can securely store and access financial data from multiple devices, which helps individuals, manage their finances on the go easily. It also enables the client to get real-time updates and notifications, which offers him more comprehensive knowledge regarding his existing financial scenario. These offerings also come with more automation features like reminders to pay payments and computerized enough transfers for a price range, keeping customers from spending further effort and time on their funds. They also offer financial advisors, tax planning tools, and wealth management. © 2025 IEEE.

关键词： Decentralized finance

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Adapting Existing Industrial Machines to the Internet of Things Paradigm 5th

Adapting Existing Industrial Machines to the Internet of Thi...

引用

5th international conference on Data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Bargavi, Manju Bhatt, Rahul K, Rama Krishna Agarwal, Trapty Karnataka Bengaluru India Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

Adapting current business machines to the internet of things (Iota) paradigm offers many possibilities for commercial procedures to grow to be greater efficient, dependable, and cost-powerful. This paper offers a high-level review of ways existing business machines can be adapted to the Iota paradigm. by utilizing mounted communication protocols and rising technology which includes business net of things (Eliot) packages, commercial machines may be geared up with the potential to talk and interact with different gadgets within the network, creating a unified device of linked additives, which may be used to enhance procedure manage. Sooner or later, extending the scope of these structures via superior analytics and system getting to know can free up new possibilities in predictive preservation and wise automation that may further improve the adapted industrial machines. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Predictive analytics

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OTFS Technology for the Internet of Things in the Context of High-Speed Mobility 24

OTFS Technology for the Internet of Things in the Context of...

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8th international conference on Electronic Information Technology and computer engineering, EITCE 2024

作者： Liu, Mingming Wang, Guofu Jia, Xiaobo Ye, Jincai School of Automation Guangxi University of Science and Technology Guangxi Liuzhou China School of Electronic Engineering Guangxi University of Science and Technology Guangxi Liuzhou China School of Information and Communication Guilin University of Electronic Technology Guangxi Guilin China

ISBN: (纸本)9798400710094

This paper addresses the Doppler shift challenge inherent to Orthogonal Time-Frequency Space (OTFS) communication techniques in high-speed mobile scenarios of the Internet of Things (IoT). First, the performance of Quadrature Amplitude Modulation (QAM) technology is analyzed, and the Bit Error Rates (BER) of OTFS, Orthogonal Frequency Division Multiplexing (OFDM) under different QAM modulation modes are compared. It is concluded that when the OTFS transmits a large amount of data, the larger the QAM modulation order, the smaller the BER, and the better the transmission effect. Secondly, the BER trends of OTFS with OFDM at different speeds are compared. The results demonstrate that OTFS exhibits superior anti-Doppler performance compared with OFDM at high-speed moving speeds. Finally, the BER performances of the three detection methods, namely, MP, LMMSE, and MRC delay-Doppler, are investigated to analyse the performance of the BER under different QAM modulations. The results demonstrate that the MRC delay-Doppler detection method is more effective in reducing the BER for the DD domain, exhibiting a robust capacity to compensate for the Doppler frequency deviation and facilitate superior signal restoration. © 2024 Copyright held by the owner/author(s).

关键词： Quadrature amplitude modulation

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