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2025 International conference on control, Automation, and Instrumentation, IC2AI 2025

作者： Anthony, Michael J. Technology & Innovation Rockwell Automation - Capitol Technology University MilwaukeeWI United States

ISBN: (纸本)9798331529604

This paper provides a future looking perspective on the evolution of cloud-native technologies in the design, operation, and maintenance of industrial control systems with aging device communication protocols. First a look at traditional control system design patterns and technologies before the Industry 4.0 shift. Then consider how advanced computing and networking power introduced with Industry 4.0 changed control systems in the past 10 years. Finally, a look at how the shift towards cloud-native technologies, big data processing, AI, and advanced computer-aided learning algorithms are challenged by the data modeling and transport norms of today's systems. This paper is a work in progress and draws no conclusions on the future. The purpose of this paper is to bring academic discussion into the needs for communication standardization in the evolving space of cloud-based control system design. © 2025 IEEE.

关键词： Cloud platforms

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A Review of Grid-Connected Inverters and control Methods Under Unbalanced Grid Conditions 16

A Review of Grid-Connected Inverters and Control Methods Und...

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16th Annual Power Electronics, Drive systems, and Technologies conference, PEDSTC 2025

作者： Marangalu, Milad Ghavipanjeh Rehman, Fazal Ur Kurkdjian, Naser Vosoughi Computer Queen's University Dep. Of Electrical and Computer Engineering KingstonON Canada University of L'Aquila Dep. Information Engineering Computer Science and Mathematics L'Aquila Italy San Diego State University Faculty of Electrical and Computer Engineering San DiegoCA92182-0001 United States

ISBN: (纸本)9798331533946

Grid-connected inverters play a pivotal role in integrating renewable energy sources into modern power systems. However, the presence of unbalanced grid conditions poses significant challenges to the stable operation of these inverters. This review paper provides a comprehensive overview of grid-connected inverters and control methods tailored to address unbalanced grid conditions. Beginning with an introduction to the fundamentals of grid-connected inverters, the paper elucidates the impact of unbalanced grid voltages on their performance. Various control strategies, including voltage and current control methods, are examined in detail, highlighting their strengths and limitations in mitigating the effects of grid imbalance. Lastly, the review identifies emerging trends and future research directions in the field, emphasizing the need for innovative solutions to address the evolving challenges posed by unbalanced grid conditions in the context of renewable energy integration. © 2025 IEEE.

关键词： control strategy fault conditions grid-connected inverters Photovoltaic systems

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The future of Traffic Management: Embracing AI for Sustainable Urban Mobility

The Future of Traffic Management: Embracing AI for Sustainab...

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

作者： Sharma, Prashant Sharma, Siddharth Pratap, Raj Chauhan, Rosey Verma, Shikha Sharda University Greater Computer Science and Engineering Noida India

ISBN: (纸本)9798331529833

The management of traffic in urban environments has become increasingly complex due to rapid urbanization and the growing number of vehicles on the road. This literature review synthesizes research on various traffic management systems and technologies, focusing on solutions such as real-time image processing, IoT-based systems, wireless sensor networks, and deep learning models. The review highlights key advancements, including intelligent traffic controllers utilizing real-time video analytics, IoT for congestion control, and AI-enabled traffic monitoring systems. © 2025 IEEE.

关键词： Traffic congestion

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An application of smart visual air conditioning controller to enhance control efficiency in office environments

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RESULTS IN ENGINEERING 2025年 25卷

作者： Tian, Yu Zhao, Zilong Loo, Junn Yong Univ Malaya Fac Engn Dept Mech Engn Kuala Lumpur 50603 Malaysia Monash Univ Malaysia Sch Informat Technol Jalan Lagoon Selatan 47500 Bandar Sunway Selangor Darul Malaysia

Innovative solutions for sustainability and energy efficiency are crucial in green building management. This study presents a novel approach to optimizing air conditioning (AC) system operations in commercial buildings, with a focus on real-time control aimed at reducing energy consumption. We propose the Smart Visual Air Conditioning controller (SVACC), which utilizes computer vision and deep learning-based human detection to intelligently manage AC operation, minimizing unnecessary runtime. By detecting human presence in meeting rooms, the system dynamically adjusts AC activation based on occupancy, thereby significantly reducing energy waste. A statistical analysis conducted over five months across ten conference rooms demonstrated that the SVACC reduced AC usage time by 33.60 %. We validate and optimize the SVACC across various building types, including commercial office spaces, industrial warehouses and laboratories, and residential apartments. The system achieved an optimal balance with 96.55 % precision and 93.33 % recall, resulting in an F1 score of 0.9492, demonstrating high performance across various environments. Our results underscore the effectiveness of the SVACC, which highlights the potential of integrating advanced deep learning models with HVAC systems to optimize energy consumption. This approach offers a promising solution for improving HVAC design and energy management across diverse building environments. future work will focus on refining sensor technology and control algorithms to further optimize energy efficiency.

关键词： HVAC Building management Deep learning Image processing computer vision

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Intelligent control algorithms for industrial automation systems

Intelligent control algorithms for industrial automation sys...

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

作者： Sarathkumar, D. Anil, A.R. Sivadasan, J. Jayakumar, T. Manivel, Murugesan Anandhakumar, C. Engineering Kongu Engineering College Department of Electrical and Electronics Tamil Nadu 638 060 India Sree Buddha College of Engineering Pattoor Department of Computer Science &engineering Kerala Alappuzha India Psr Engineering College Department of Electronics and Communication Engineering Tamil Nadu Sivakasi626140 India Nandha Engineering College Department of Electrical and Electronics Engineering Tamil Nadu 638052 India Karpagam Institute of Technology Department of Electrical and Electronics Engineering Tamilnadu Coimbatore641021 India Sri Ramakrishna Institute of Technology Department of Electrical and Electronic Engineering Tamil Nadu Coimbatore641010 India

ISBN: (纸本)9798331529833

Industrial automation has become a cornerstone of modern manufacturing, enhancing efficiency, reliability, and scalability. The integration of intelligent control algorithms, such as fuzzy logic, neural networks, genetic algorithms, and model predictive control, has revolutionized traditional automation systems, enabling more adaptive, efficient, and robust operations. This paper explores the application and impact of these intelligent control techniques in industrial settings. It highlights how machine learning algorithms can predict equipment failures, optimize processes, and enhance decision-making in real-time. Case studies are presented to illustrate the benefits and challenges of deploying these algorithms across various automated systems, such as robotic assembly lines, process control in chemical plants, and smart warehousing. Furthermore, the paper discusses the integration of these algorithms with industrial IoT (IIoT) platforms, facilitating seamless communication and data exchange between machines and control systems. The research also addresses the challenges of implementing intelligent control, such as computational complexity, security concerns, and the need for real-time processing. Finally, this study evaluates future trends, emphasizing the potential of combining artificial intelligence and deep learning techniques with industrial automation for a more adaptive and autonomous manufacturing ecosystem. © 2025 IEEE.

关键词： Genetic algorithms

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Enhancing Two-Area Interconnected Power systems Using Model Predictive and PID control Approaches 1

Enhancing Two-Area Interconnected Power Systems Using Model ...

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1st International conference on Advances in computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Kushwaha, Ritesh Kumar Prakashyadava, Ram Malik, Monu Alam, Monauwer Ahamad, Isarar Naugai, Divyanshu Chandigarh University Dept. of Electronic and Communication Engineering Punjab Mohali India Integral University Deptt. of Electrical Engineering U.P. Lucknow India Maharaja SurajMal institute of Technology Electronics and Electrical Engg Deptt India Integral University Deptt. of Electrical Engineering Lucknow India BTKIT Dwarahat Dept. of Electronics and Communication Engineering Uttarakhad Almora India

ISBN: (纸本)9798331518578

This research represents a comparative study of Load Frequency control (LFC) using Model Predictive control (MPC). The results have also been compared with Proportional-Integral-Derivative (PID) controllers. LFC is evident for power system stability which keeps equilibrium between generation and load. PID controllers are widely employed, however in the modern-day power systems which are complex in nature the performance of the PID controllers is not as par. Therefore, different control schemes have and are being explored. MPC is one of them techniques. The aim of this research is to evaluate and compare the effectiveness of MPC and PID controllers, in two-area system. A case study featuring a two-area system is presented to illustrate how the controllers respond to load conditions and disturbances. This paper aims to provide insights into the merits and limitations of each controller. The results contribute to a more profound comprehension of the practical implications associated with implementing MPC in LFC systems, thereby influencing future research and practical applications. © 2025 IEEE.

关键词： Predictive control systems

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Hardware-in-The-Loop-Based Validation of Distribution System control Applications with Grid Operators, Customer and Market Participants 4th

Hardware-in-The-Loop-Based Validation of Distribution System...

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4th Energy Informatics Academy conference

作者： Otte, Marcel Krueger, Carsten Das, Pratyush Rohjans, Sebastian Lehnhoff, Sebastian OFFIS Inst Informat Technol Oldenburg Germany Carl von Ossietzky Univ Oldenburg Oldenburg Germany Jade Univ Appl Sci Oldenburg Germany

ISBN: (纸本)9783031747373;9783031747380

The flexibility potential of electric vehicles, heat pumps, photovoltaics, and storage systems allocated at customer premises raises attention to grid-serving and market-serving control applications. However, control applications vary as the kind of flexibility differs due to the complexity of interactions behind the meter, the actors involved, conflict of interests, regulatory requirements, and the number of systems to integrate. Consequently, the validation of applications across all phases of development reveals the potential bottlenecks of the application before deployment. This work presents the use cases for distribution system control applications and how they can be validated in a hardware-in-the-loop simulation environment. The validation environment covers the systems of a distribution system operator and its upstream grid operator, virtual field devices, a real-time grid simulation, the meter operator including the operation of an advanced metering infrastructure, as well as applications from market participants like aggregators. As a proof of concept, two use cases are selected to demonstrate how grid operator coordination and customer behaviour can be validated. Thereafter, it will be implied how the validation environment is suitable for future use cases, such as the coordination of grid-serving and market-serving control applications.

关键词： active distribution grid flexibility provision validation environment smart meter customer premises

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Investigating Research Trends in computer Vision for Food Quality control: A Bibliometric Approach 6

Investigating Research Trends in Computer Vision for Food Qu...

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6th International conference on Industry 4.0 and Smart Manufacturing, ISM 2024

作者： Lysova, Natalya Solari, Federico Montanari, Roberto Department of Engineering for Industrial Systems and Technologies University of Parma Parco Area delle Scienze 181/A Parma43124 Italy

The production throughputs of the food industry grow continuously due to the ever-increasing customer demand. At the same time, food safety measures become increasingly strict. To this end, efficient quality control is essential to ensure quality and safety for consumers, and to guarantee efficient and valuable production for industrial stakeholders. computer vision is often applied to this end, usually integrated with other Industry 4.0 technologies and process automation. computer vision applications in quality control, indeed, can greatly enhance supply chain management in the food industry by maintaining consistent product quality and minimizing waste. In this paper, a keyword-based analysis is carried out to assess the main research trends and topics in the field of computer vision for quality control in the food industry. The bibliometric analysis aims to assess the main applications of the technology in terms of processes and products and the main issues targeted by the analyses. Finally, the results of the bibliometric investigation allow to identify and highlight topics that present potential for future investigations in the field. © 2024 The Authors. Published by Elsevier B.V.

关键词： Food industry

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Real-Time Drone System for Detecting, Tracking, and Following of a Mobile Robot in ROS/Gazebo

Real-Time Drone System for Detecting, Tracking, and Followin...

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2025 International conference on control, Automation, and Instrumentation, IC2AI 2025

作者： Salman, Ali Dika, Mohammad Diab, Hassan Owayjan, Michel Achkar, Roger American University of Science & Technology Faculty of Engineering and Computer Science Beriut Lebanon Nantes University Saint-Nazaire France

ISBN: (纸本)9798331529604

Surveillance drones equipped with video transmission capabilities play a crucial role in modern security systems, with the integration of OpenCV for object detection marking a significant advancement. This study evaluates the detecting accuracy by varying the distance between the drone and the target object, addressing gaps in current research through a detailed practical insight. This research explores key aspects of drone-based video surveillance, including object detecting, tracking and real-time following, aiming to enhance understanding and methodology in computer Vision (CV) applications with Unmanned Aerial Vehicles (UAVs). The Simulation of a surveillance drone system in Gazebo simulator within the ROS2 framework. The drone is programmed to dynamically follow and track a mobile robot, enabling systematic analysis of the object detection algorithm's performance. The findings contribute to advancing the reliability and effectiveness of drone-based video surveillance systems for future innovations in security and monitoring applications. © 2025 IEEE.

关键词： Drones

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Routing and Charge Planning Strategies for Ridesharing EV Fleets 11

Routing and Charge Planning Strategies for Ridesharing EV Fl...

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11th International conference on Vehicle Technology and Intelligent Transport systems, VEHITS 2025

作者： Singh, Ashutosh Gupta, Arobinda Dept. of Computer Science & Engineering Indian Institute of Technology KharagpurWB-721302 India

ISBN: (纸本)9789897587450

Ridesharing systems have become an important part of urban transportation. At the same time, electric vehicle (EV) adoption is also growing at a fast pace as an eco-friendly and sustainable transportation option. To operate a ridesharing system with EV fleets, scheduling an EV fleet to serve passenger requests requires consideration of both the requests, and the available charge and potential future charge requirements of the EVs. In this paper, we address the problem of scheduling EVs by a ridesharing operator, and propose four algorithms that schedule passenger requests while taking into consideration charging requirements of the EVs. Detailed simulation results are presented on a real world data set to show that the algorithms perform well. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Urban transportation

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