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Advising and Scheduling Tool Based on Electrical Power engineering Concepts

Advising and Scheduling Tool Based on Electrical Power Engin...

引用

2025 international conference on Control, automation, and Instrumentation, IC2AI 2025

作者： Nehme, Bechara Al Ahmar, Elie Zalaket, Joseph Electrical Telecommunication and Computer Engineering Department Jounieh Lebanon University Furn El Chebbak Faculty of Engineering Sagesse Baabda Lebanon

ISBN: (纸本)9798331529604

University administrations are always in need for tools to optimize their operation decreasing operational costs and ensuring a good learning experience for students. Advising and course offering are two main tasks that require knowledge in the field and expertise. The tasks need also data and its related analytics. This paper presents an innovative advising tool based on data mining leveraging from electrical power concepts. The tool uses Python and Excel to automate advising sheets and electrical power engineering by applying simultaneity and the factor of utilization to students records and courses to predict future course enrollment with a RMSE=0.75. The research proposed is unique since it helps administration and advisors. With the reduction of resources and disruption of the classical educational system new tools should be elaborated to reduce costs and secure on time graduation of students. © 2025 ieee.

关键词： Students

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Towards Reliable Navigation for Intelligent Unmanned Surface Vehicles

Towards Reliable Navigation for Intelligent Unmanned Surface...

引用

2025 international conference on Electrical automation and Artificial Intelligence, ICEAAI 2025

作者： Liu, Wenwen Zhao, Zhuoli Ye, Yujian Xu, Dezhi School of Automation Nanjing University of Information Science and Technology Nanjing China School of Automation Guangdong University of Technology Guangdong China School of Electrical Engineering Southeast University Nanjing China

ISBN: (纸本)9798331506797

This paper presents a novel navigation system developed to tackle the challenge of unreliable navigation data during unmanned surface vehicles (USVs) operation. The system incorporates a method to determine the reliability index of the navigation system, which helps identify system uncertainties, and an Unscented Kalman Filter (UKF) based algorithm for USV trajectory recovery from the unreliable sensor data. Based on the determined reliability index, the system can quickly identify unreliable data, accurately assess risks associated with imprecise data, which enables it to generate a more dependable guidance route. The effectiveness and capabilities of this reliable navigation system have been validated through simulations and practical trials, highlighting its practical value and significance. © 2025 ieee.

关键词： autonomous navigation reliability index USV

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Building Resilient Supply Chains with IoT and Advanced Analytics: A Path to Operational Excellence 3

Building Resilient Supply Chains with IoT and Advanced Analy...

引用

3rd ieee international conference on automation and Computation, AUTOCOM 2025

作者： Sanaboina, S.V.S.V. Prasad Josh Kumar, J.P. Balassem, Zaid Ajzan Saxena, Anil Kumar Mohanraj, T. Rajaram, Gnanajeyaraman Department of Cse CMR Technical Campus Telangana Hyderabad India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Electronics and Communication Engineering Chennai India College of Technical Engineering The Islamic University Department of Computers Techniques Engineering Najaf Iraq Uttaranchal University Dehradun248007 India Karpagam Academy of Higher Education Department of Computer Science Engineering Coimbatore India Simats Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Cse Chennai India

ISBN: (纸本)9798331542375

Recent global supply chain challenges have revealed that resilience has become crucial to the operational success of supply chains. Presenting the findings of this study, this research looks at how the advent of the Internet of Things (IoT) and analytical tools have gone a long way towards strengthening the supply chain. A large number of devices like sensors, RFID tags, and smart machinery connected to the supply chain help the organizations to track and monitor the process in order to make the right decisions, identify problems which may occur in the future and thus optimize the potential of supply chains. Combined with other related technologies including machine learning, artificial intelligence, big data analytics, the supply chain managers can process abundance of data to look for threats, compare the changing demand patterns and respond in advance. This paper presents several industrial applications of IoT and advanced analytics in supply chain and illustrates how the integration of the two technologies improve flexibility, avoid risk and increases the supply chain performance. The work also looks at the problems that accompany adoption of these technologies such as security, integration as well as the workforce skills required to support the implementations. In sum, this work articulates a conceptual model for managing IoT and Big Data in the pursuit of business productivity and economic viability in a complex and volatile global environment. © 2025 ieee.

关键词： Predictive maintenance

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A Comprehensive Analysis on Severity Estimation of Plant Diseases by Deep Learning Models

A Comprehensive Analysis on Severity Estimation of Plant Dis...

引用

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

作者： Sonu Varghese, K. Kumar, R. Satheesh Sahrdaya College of Engineering and Technology APJ Abdul Kalam Technological University Kerala Department of Computer Science and Engineering India Jawaharlal College of Engineering and Technology APJ Abdul Kalam Technological University Department of Computer Science and Engineering Kerala India

ISBN: (纸本)9798331512965

The rapid spread of diseases and pest infestations has a detrimental effect on plant health. Methods for disease classification and detection have gained new insights from the developments in computer vision and deep learning approaches. However, there has been relatively limited work in the area of severity estimation and disease progression rate since it requires more detailed information such as the percentage of affected leaf area, symptoms intensity, and environmental factors that lead to the disease progression over time. Thus the modern agricultural sector faces a significant difficulty in the assessment of plant disease severity and tracking of disease development. The purpose of this study is to perform a thorough review of various deep learning methods for plant disease severity assessment, taking into account factors like accuracy, severity level measurement, and dataset employed. The article also suggests ways to address the shortcomings of the current approach. © 2025 ieee.

关键词： Adversarial machine learning

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Automatic Pesticide Spraying Drone

Automatic Pesticide Spraying Drone

引用

2025 ieee international Students' conference on Electrical, Electronics and computer science, SCEECS 2025

作者： Kumar, J. Sam Jeba Yuvaraj, S. Gothavari, V. Anantharaj, R. Srm Institute of Science and Technology Electronics and Instrumentation Engineering Faculty Chennai India Srm Institute of Science and Technology Electronics and Instrumentation Engineering Student Chennai India

ISBN: (纸本)9798331529833

Drones are emerging technologies in agriculture, replacing manual pesticide spraying due to harmful side effects on personnel. It is designed to reduce time and labor costs for farmers. This paper aims to develop a software system that finds and classifies plant diseases using image processing techniques for effective disease detection in agricultural applications. Using the software simulation, this drone assists the farmer in choosing the land's coordinates for accurate use of pesticides on land. Additionally, it facilitates the drone's automated takeoff and landing. © 2025 ieee.

关键词： Pesticide effects

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VR Cybersickness Classification using Machine Learning Models on Open-Access EEG Datasets from the Human Vestibular Network 7

VR Cybersickness Classification using Machine Learning Model...

引用

7th ieee international conference on Artificial Intelligence and eXtended and Virtual Reality, AIxVR 2025

作者： Li, Gang Byeon, Hae-Rin Cho, Sung-Bae Pollick, Frank University of Bath Department of Computer Science Bath United Kingdom Yonsei University Department of Computer Science and Engineering Seoul Korea Republic of School of Pscyhology and Neuroscience University of Glasgow Glasgow United Kingdom

ISBN: (纸本)9798331521578

This paper addresses key challenges in EEG-based cybersickness classification using machine learning (ML) models. Despite significant research in this area four critical issues remain unresolved: 1) the availability of open-access EEG datasets;2) imbalanced data distribution;3) limited generalizability testing, and 4) insufficient exploration of personalized EEG data. © 2025 ieee.

关键词： Adversarial machine learning

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Hybrid Optical-Electrical Transceiver Architecture for High-Speed Data Communications 3

Hybrid Optical-Electrical Transceiver Architecture for High-...

引用

3rd ieee international conference on automation and Computation, AUTOCOM 2025

作者： Panda, Suryakanta Vashisht, Nitish Srinivasa Rao, K.S. Rajasekar, B. Acharjya, Kalyan Vashisht, Nitish Department of Computer Science and Engineering Odisha Bhubaneswar India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh Baddi174103 India Karnataka Bangalore India Sathyabama Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Punjab Rajpura140417 India

ISBN: (纸本)9798331542375

Evaluating Design Tradeoffs in MMW Wave Arrays for High-Speed Wireless Data Communication and its Optimization over Fiber If you tear open your cloud, you will find a stream of is and Os at the heart of all this, with shrill screams from demanding applications like video, virtual reality, etc. pushing I believe close to their limits bandwidth comments here up purely optical links. We are reporting on highresolution computational imaging optimized for 3D surface reconstruction with tight constraints on operational uncertainty. Traditional electronic-only transceiver architecture is approaching its physical limits regarding data speed and power efficiency spurring the critical demand for more advanced approaches. Novel hybrid optical-electrical transceiver architecture has been discussed to overcome these limitations. It blends the fast speeds and broad bandwidths made possible by optical communication with the flexibility and scale of electrical circuits. The heart of this architecture is an electro-optic interface that converts electrical signals to optical. Enabling this interface is advanced materials like silicon photonics that permit optical and electronic components to be integrated into a single chip. This hybrid architecture combines optical communication for high-speed data transmission and enables data rates that are multiple orders of magnitude faster than traditional electronic-only architectures. Moreover, optical interconnects directly benefit the transceiver by lowering its power consumption, reducing total energy use and improving system performance. © 2025 ieee.

关键词： Silicon photonics

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Towards Reliable and Energy-Efficient Communication Protocols for Wireless Body Area Networks in Medical Applications 3

Towards Reliable and Energy-Efficient Communication Protocol...

引用

3rd ieee international conference on automation and Computation, AUTOCOM 2025

作者： Jayaprakash, B. Premkumar, J. Das, Neeraj Punia, Ankit Nayak, Subrat Kumar Ojha, Varun Karnataka Bangalore India Sathyabama Institute of Science and Technology Department of Biomedical Engineering Tamil Nadu Chennai India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Department of Computer Science and Engineering Odisha Bhubaneswar India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh Baddi174103 India

ISBN: (纸本)9798331542375

Wireless body area networks are an attractive technology for measuring health data in medical applications. Several challenges exist in designing and implementing such reliable, energy-efficient communication protocols for these networks. This new strategy solution strategy is based on a hybrid communication protocol that simultaneously obtains the positive aspects of centralized and distributed structures. By centralizing network maintenance and control functions such as health monitoring of nodes and transmission control, the proposed protocol supports reliable data transmission with minimal energy consumption in WBANs. This reduces the overhead and collisions, giving the network better reliability. Unlike other protocols mentioned where the data flow from the sensor node to the central node is at least distributed, in our case, a few nodes send their data at a time to the Central Node. It enables low-power communication since nodes only need to wake up during their allotted transmission time slot. Through simulations, we demonstrate that the new protocol surpasses existing protocols in reliability and energy consumption performance. It can also help to minimize the energy consumption of WBAN nodes, which makes it an appropriate candidate for long-time medical monitoring applications. All in all, this work helps to pave the way for the efficient use of WBANs in a wide range of medical applications that require robustness and low-energy communications. © 2025 ieee.

关键词： Signaling

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Novel Antenna Designs for High Data Rate Body-Centric Communications in Wearable Devices 3

Novel Antenna Designs for High Data Rate Body-Centric Commun...

引用

3rd ieee international conference on automation and Computation, AUTOCOM 2025

作者： Soni, Ishika Manjunatha, R. Baskar, V. Vijaya Singh, Daljeet Pal Parashar, Komal Panda, Niranjan Chitkara Centre for Research and Development Chitkara University Himachal Pradesh Baddi174103 India Karnataka Bangalore India Sathyabama Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Department of Computer Science and Engineering Odisha Bhubaneswar India

ISBN: (纸本)9798331542375

There is an ever-increasing demand for high data rate communication embedded in wearable devices owing to the exponential growth of smart devices and related technology. The human body is always around, which means that traditional antenna designs will not work well with body-centric communications operations, as signal loss and interference from the presence of the human body must be addressed. This project addresses this limitation by designing new body-centric communications antenna designs for incorporation into wearable devices. Antennas proposed in the literature can use novel techniques that reach high data rates while providing reliable communication links and features like compactness, low power consumption, and multi-band functionalities. The designs are optimized to ensure that the human body has a minimal effect on the signal enhancing performance and stability. The antennas are designed and simulated using advanced simulation tools and validated in the lab. These findings demonstrate the remarkable advantages of high-speed data transmission and link quality compared to traditional antennas. It contributes to developing novel antenna designs that wearable device manufacturers can incorporate into high data rate body-centric communications, enabling dramatically improved performance within tight space constraints. This will make it possible to create next-generation wearable devices with communication functions for applications ranging from healthcare and sports to virtual reality. © 2025 ieee.

关键词： Signaling

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Research on Distributed Management and Early Warning Technology of Food science Laboratory Based on Multi Information Fusion

Research on Distributed Management and Early Warning Technol...

引用

2025 international conference on Electrical automation and Artificial Intelligence, ICEAAI 2025

作者： Tong, Yao Wang, Hong Ma, Gaoxing Nanjing University of Finance and Economics College of Food Science and Engineering of NUFE Nanjing China

ISBN: (纸本)9798331506797

Regarding the safety hazards in food science laboratories resulting from a multitude of instruments and equipment, as well as numerous flammable and explosive chemicals, by drawing upon advanced technologies such as the Internet of Things and multi-information fusion, a technology for distributed management, comprehensive health status assessment, and risk early warning of laboratories is proposed. By applying the D-S evidence theory to integrate and analyze information on personnel, environment, and instruments. Not only can this technology promptly detect temporary trigger faults and safety incidents such as fires, waterlogging, and gas leakage, but it can also promptly identify potential safety hazards caused by aging lines and excessive electricity consumption and issue early warnings in the first place. Compared with traditional laboratory monitoring methods, it features higher assessment accuracy and stronger risk control capabilities. © 2025 ieee.

关键词： fault alarm Introduction Laboratory safety monitoring multiple information fusion status assessment

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