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Smart irrigation for soil moisture prediction using hybrid AI and fog computing 14

Smart irrigation for soil moisture prediction using hybrid A...

引用

14th IEEE international conference on communication Systems and Network Technologies, CSNT 2025

作者： Bindal, Ruchika Kaur, Mandeep Tandon, Righa Department of Computer Science and Engineering Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798331531935

Irrigation control is essential for optimizing water usage in smart agricultural systems, especially where there is water scarcity. The fast development of IoT and fog computing brings up new opportunities for developing new and advanced systems that are both efficient and flexible. Further integration of fog computing with machine learning will bring more developments to smart agriculture systems. This paper has framed an irrigation supervision algorithm to predict irrigation needs in the smart agriculture system. The methodology uses a hybrid algorithm that incorporates Gradient Boosting (GB), Logistic Regression (LR) and Random Forest (RF). The system accurately forecasts the irrigation requirement by processing ecological information such as humidity, temperature, and time-based factors. 97.78% of accuracy illustrates the reliability of the resultant model, and initial processing of the data illustrates that information is concise and accurate. Recall, precision and F1- score are computed as metrics for the performance. The system is integrated into fog computing and machine learning to manage real-time data processing to achieve faster and more accurate predictions. © 2025 IEEE.

关键词： Random forests

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Design of Wide Neural Network Model for controlling Tunable LED Luminaire: (Neural Network based Luminaire control) 5

Design of Wide Neural Network Model for Controlling Tunable ...

引用

5th IEEE international conference on Advances in Electrical, computing, communication and Sustainable Technologies, ICAECT 2025

作者： Aranha, Ancy Princia George, Anna Merine Kamath, Vedavyasa Kurian, Ciji Pearl Padmashree, K.S. Manipal Institute of Technology Manipal Academy of Higher Education Department of Electrical and Electronics Engineering Manipal India Bms Institute of Technology & Management Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350356236

This paper explores machine learning models to design adjustable light spectra for supporting circadian entrainment using LED luminaires. The approach combines practical experimental work with sophisticated machine learning methods to enhance lighting solutions. There is a growing demand for adjustable sources to improve efficiency and reduce costs, leading to the development of multichannel LED drivers capable of operating at different brightness levels and spectra for each LED channel. The multichannel LED driving circuitry is a critical component of human-centric lighting, which aims to enhance the well-being and health of occupants. The experiment utilized a four-channel warm white and cool white combination LED luminaire under dimming and Correlated Colour Temperature (CCT) variation. Current-controllable LEDs for different CCTs and intensities were tested with the help of DMX 512 Decoder and master control. The Wide Neural Network model designed outperforms other models in performance, helping to determine the current requirement of the lighting control system to set the desired circadian entrainment conditions. © 2025 IEEE.

关键词： controllability

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Scalable Brain Stroke Prediction Using PySpark: A Big Data Approach 5

Scalable Brain Stroke Prediction Using PySpark: A Big Data A...

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5th IEEE international conference on Advances in Electrical, computing, communication and Sustainable Technologies, ICAECT 2025

作者： Nair, Rohit S. Varma, Kallepalli Rahul Raj, Kalagara Venkata Sampath Ramu Keerthana, P. Ramesh, T.K. Amrita School of Engineering Amrita Vishwa Vidyapeetham Department of Electronics & Communication Engineering Bengaluru India

ISBN: (纸本)9798350356236

Brain stroke affects a large number of the population and is one of the primary causes of death and permanent disability, therefore the identification of risk factors is paramount for timely prevention. These interactions are difficult to capture because stroke risk factors are demographics, life style and medical history all of which cannot be modeled using statistical solution. To tackle these and similar issues, the present paper employs PySpark, a distributed computing system, for the formulation of small-scale and big data with various machine learning algorithms including, Logistic Regression, Gradient Boosting, Decision Trees, Naive Bayes, and Random Forests, for predicting brain stroke. The used models were derived from a great amount of healthcare data, though the hyperparameter optimization was applied to improve the results. Among those algorithms, Gradient Boosting showed the best result with the accuracy of 92.2, Random Forest is 90.5, which indicates that these algorithms can give good results at the time of risk assessment of stroke. Measuring techniques like precision, recall and F1 score were employed to measure model accuracy and test ability to control between False Positives and False Negatives. This multiple model approach recognizes the most efficient algorithms for possible implementation in real-life, mass, clinical practice for early detection, patient control, and individual prevention. © 2025 IEEE.

关键词： Distributed computer systems

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Enhanced Coffee Bean Defect Detection Using Super-Resolution GANs and Deep Learning 2

Enhanced Coffee Bean Defect Detection Using Super-Resolution...

引用

2nd international conference on Computational Intelligence, communication Technology and Networking, CICTN 2025

作者： Prabu, S. Thanigaivelu, P.S. Poonkodi, S. Anand, M. Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur TamilNadu Chennai603203 India

ISBN: (纸本)9798331530389

Image Super-Resolution (SR) is a key challenge in computer vision, focusing on enhancing low-resolution images while preserving details. This paper presents a novel method using Generative Adversarial Networks (GANs) for improving image quality, specifically targeting coffee bean defect detection. The proposed SR-GAN model includes a generator that upscales low-resolution inputs and a discriminator that differentiates between generated high-resolution images and real ones. Trained on a coffee bean dataset, the model optimizes loss functions to balance perceptual quality and fidelity, capturing subtle defects like cracks and discolorations. Enhanced images are processed by two Convolutional Neural Networks (CNNs): one identifies broad defect categories, such as defective black beans, brown beans, broken beans and non-defective high-quality beans. This layered approach ensures more precise defect identification and classification, overcoming limitations of previous methods that struggled with subtle defects. Performance evaluations show that SR-GAN and CNN significantly outperforms existing models in resolution enhancement and classification accuracy, offering a robust solution for improving quality control in coffee production. © 2025 IEEE.

关键词： Convolutional neural networks

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Extended State Observer-based Hybrid Dynamic Event-Triggered Consensus control with External Disturbances 24

Extended State Observer-based Hybrid Dynamic Event-Triggered...

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2nd international conference on Frontiers of Intelligent Manufacturing and automation, CFIMA 2024

作者： Pei, Wenliang Hua, Changchun Cui, Hailong Zhao, Guanglei Ma, Zhuang The Institute of Electrical Engineering The Key Lab of Intelligent Rehabilitation and Neuroregulation in Hebei Province Key Laboratory of Intelligent Control and Neural Information Processing Ministry of Education Yanshan University Hebei China Tangshan University Hebei China

ISBN: (纸本)9798400710681

This paper solves the event-triggered robust consensus problem of disturbed multi-agent systems (MASs) in fully distributed fashion. First, a distributed extended state observer (DESO) is developed for appropriately estimating system states and external disturbances. Then, by utilising these estimates, a fully distributed event-triggering control protocol, that composes of an adaptive distributed controller to avoid using global information while maintaining desired consensus property, and a novel hybrid dynamic event-triggering mechanism (ETM) to save communication resources, is put forward for the MASs. It is notable that an auxiliary differential equation is incorporated in the triggering condition, with which, positive minimum interevent times (MIETs) are available to ease the hardware implementation, while being with adaptive coefficients, the proposed hybrid dynamic ETM can be independent of any global information. Finally, the obtained main results are testified via a numerical example. © 2024 Copyright held by the owner/author(s).

关键词： State estimation

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Learning to Program: Mapping Errors and Misconceptions of Python Novices to Support the Design of Intelligent Programming Tutors 17

Learning to Program: Mapping Errors and Misconceptions of Py...

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17th international conference on Computer Supported Education, CSEDU 2025

作者： van der Heyden, Lisa Batur, Fatma Chounta, Irene-Angelica Department of Human-centered Computing and Cognitive Science University of Duisburg-Essen Duisburg Germany Computing Education Research Group University of Duisburg-Essen Essen Germany

ISBN: (纸本)9789897587467

Students often struggle with basic programming tasks after their first programming course. Adaptive tutoring systems can support students’ practice by generating tasks, providing feedback, and evaluating students’ progress in real-time. Here, we describe the first step for building such a system focusing on designing tasks that address common errors and misconceptions. To that end, we compiled a collection of Python tasks for novices. In particular, a) we identified errors occurring during introductory programming and mapped them to learning tasks;b) we conducted a survey to validate our mapping;c) we conducted semi-structured interviews with instructors to understand potential reasons for such errors and best practices for addressing them. Synthesizing our findings, we discuss the creation of a tasks’ corpus to serve as a basis for adaptive tutors. This work contributes to the standardization and systematization of computing education and provides insights regarding the design of learning tasks tailored to addressing errors. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Python

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UAV control in Multi-access Edge computing Using Markov Decision Process 1st

UAV Control in Multi-access Edge Computing Using Markov Dec...

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1st international conference on Intelligent Systems, Blockchain, and communication Technologies, ISBCom 2024

作者： Elghitani, Fadi Fayed, Ibraheem M. National Telecommunication Institute Cairo Egypt

ISBN: (纸本)9783031823763

Cloud computing is the pradigim where service providers carry-on computational tasks for their customers. Multi-access Edge computing (MEC) is a recent form of service where the computational tasks are carried in a distributed manner at the edge of the network to be as close to customer as possible. This new pradigim have the advantage of lowering the latency, making the pradigim suitable for real-time applications. One promising way to deploy MEC is to mount the servers over a UAV which can be moved dynamically to become closer to users. In this paper, we address the challenges associated with UAV-mounted servers like energy consumption and path routing. We propose a UAV control mechanism based on continuous-time Markov Decision Process (CT-MDP). We demonstrated the advantage of the proposed mechanism in terms of task-satisfaction rate and policy computational time. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Markov processes

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Design Process and Development of automation for Smart Buildings 1

Design Process and Development of Automation for Smart Build...

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1st international conference on Advances in Computer Science, Electrical, Electronics, and communication Technologies, CE2CT 2025

作者： Sethi, Gunjan Khurana, Deepika Verma, Monika Pant, Surmadhur Chauhan, Priyanka Bhatt, Bhaskar Department of Computer Science and Engineering Delhi Technical Campus Uttar Pradesh Greater Noida India IIMT College of Engineering Department of Computer Science and Engineering Uttar Pradesh Greater Noida India Shivalik College of Engineering Department of ECE Dehradun India Uttaranchal Institute of Technology Uttaranchal University Dehradun248007 India Bipin Tripathi Kumaon Institute of Technology Department of Mechanical Engineering Dwarahat Almora India

ISBN: (纸本)9798331518578

In order to create spaces that are secure, cozy, energy-efficient, and visually beautiful, smart buildings are becoming more and more sophisticated cyber-physical systems. However, as functional complexity, financial concerns, and market demands increase, traditional design methodologies are becoming less effective. Current framework's plan and activity have been totally changed by the presentation of automated smart building, which ensures expanded security, better inhabitant solace, and energy effectiveness. With an emphasis on MATLAB-based reproductions, this study offers a careful assessment of the plan interaction and improvement procedures for computerizing savvy structures. The study delineates how MATLAB makes it simpler to depict, reproduce, and investigate savvy building frameworks with certainty. Through the mix of numerous advancements, like sensors, regulators, and correspondence conventions, the research shows the turn of events and check of a mechanized smart building framework. The intelligent building's building automation system prioritizes a humanized interface and uses a combination of mechanical, electrical, and fire control systems, access control systems, and parking management systems to give building occupants a convenient and comfortable place to live and work. The discoveries show prominent additions in functional viability, natural adaptability, and energy utilization. The conventional heuristic and ad hoc design paradigms are becoming ineffective and inadequate for the future due to cost, the requirement to handle growing functional complexity, adaptability, supply chain fragmentation, and time-to-market pressure. © 2025 IEEE.

关键词： Smart homes

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Suitable for 5G elastic fusion accurate positioning technology in near-power construction site environment 24

Suitable for 5G elastic fusion accurate positioning technolo...

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2nd international conference on Frontiers of Intelligent Manufacturing and automation, CFIMA 2024

作者： Zhao, Binglan Li, Lianpeng Beijing Information Science &Technology University Beijing China

ISBN: (纸本)9798400710681

Considering the challenges posed by the complex electromagnetic conditions in substations, the high levels of risk, and the difficulty in ensuring safety inspections, the development of a highly accurate positioning system plays a critical role in safeguarding the lives of personnel. This approach involves analyzing the specific positioning needs of multiple devices and personnel in the vicinity of power construction sites. It integrates inertial autonomous positioning, carrier motion data acquisition, and 5G reference positioning technology. The core of this method is based on inertial autonomous positioning and orientation, supported by satellite navigation and positioning enhancement technology. It establishes a multi-source fusion autonomous positioning approach that as signal strength, environmental conditions, and motion patterns. The design includes a distributed adaptive multi-source information fusion architecture, integrating diverse observation information at multiple scales, rates, and modes. By utilizing 5G and deep learning, a digital regional elastic fusion and precise positioning method is established for high-precision positioning in the vicinity of power environments, enabling effective safety control for substation operators. © 2024 Copyright held by the owner/author(s).

关键词： 5G mobile communication systems

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Review on Advanced computing control Techniques in BLDC Motors for Electrical Vehicles 3

Review on Advanced Computing Control Techniques in BLDC Moto...

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3rd international conference on Intelligent Data communication Technologies and Internet of Things, IDCIoT 2025

作者： Vara Prasad, K.S.R. Usha Reddy, V. Department of EEE S.V.U College of Engineering Tirupati India

ISBN: (纸本)9798331527549

Among all electrified transportation instruments, electric vehicles (EVs) garnered high mark lately and are becoming increasingly popular trends because they can both vie with and surpass vehicles powered by fossil fuel. Enhancing range of vehicle driving and minimizing energy utilization are the main goals of EV advancement. These are necessary goals that can only be met by enhancing and advancing motor performance. With the peak power density and capabilities compared with other motors, brushless direct current (BLDC) motor is best option for electric vehicles (EVs). In addition to their excellent performance in position and speed controls, BLDCs are becoming more and more common in EVs because they can smoothly maintain torque and reduce torque ripple. An overview of several advanced control strategies is given in this study, it also discusses the different fault that occur in BLDC motors and their mitigation strategies. In addition, current issues and challenges in developing torque ripple mitigation management systems are discussed, along with comparisons and recommendations for further research on electric vehicle technology. Lastly, the importance and possible consequences of BLDC motor drive in EVs with various control schemes are revealed via evaluation research. © 2025 IEEE.

关键词： Brushless DC motors

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