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检索条件"任意字段=International Conference on Trends in Automation, Communications and Computing Technology"

共 3241 条记录，以下是31-40 订阅

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Measuring AI′s Impact on HR Strategies and Operational Effectiveness in the Era of Industry 4.0 1st

Measuring AI′s Impact on HR Strategies and Operational Effe...

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1st international conference on Innovation and Emerging trends in computing and Information Technologies, IETCIT 2024

作者： Devi, K. Singh, Jagendra Garg, Neha Tiwari, Mohit Shaik, Nazeer Elangovan, Muniyandy Department of Commerce DAV Autonomous College Titilagarh India School of Computer Science Engineering and Technology Bennett University Noida India Department of Computer Science and Engineering Bharati Vidyapeeth’s College of Engineering Delhi India Department of Computer Science and Engineering Srinivasa Ramanujan Institute of Technology – Autonomous Anantapur India Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India

ISBN: (纸本)9783031808388

This study examines the transformative impact of automation-training programs on human resources strategies and operational effectiveness in the Industry 4.0 era. Through an in-depth analysis of training-performance metrics before and after including knowledge acquisition, skill proficiency, increased productivity, and product quality, the report describes the quantifiable benefits of investment in employee development initiatives designed specifically for automation technologies. Surveys of different groups of respondents show that having undergone formal training programs with workshop practice, peer mentoring, collaborative study groups, and virtual reality-based simulations, workers gain a more profound understanding of automation concepts. They will have increased skill in operating equipment, with a consequently large leap in quality and productivity for the organization. Furthermore, it was observed that cycle times and equipment downtimes fell appreciably across the board post-training, suggesting improved operational efficiency and more streamlined production processes. This research points out the immense significance of training for automation projects led by HR managers in enabling employees to meet increasing demand for automation in the workplace, and this may well contribute greatly to a continuing learning society that is favorable to innovation--the basis of success in an Industry 4.0 digital world. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Investments

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A Lightweight Network Deployed on ARM Device for Hand Gesture Recognition

A Lightweight Network Deployed on ARM Device for Hand Gestur...

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Intelligent Control, computing and communications (IC3), international conference on

作者： Shreyas P S Varshith V Hegde Shivaneeth Keshav Shetty Shreevanth R Bhandary Manjunath Kotari Alva's Institute of Engineering and Technology Mijar Moodbidri India

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

Enhancing interactions with natural and user-friendly computer interfaces (HCIs) requires the use of hand gestures. This article illustrates a particularly created brilliant neural network that can identify the flat-based platform's movements. Real-time applications on low-power devices can benefit from the suggested approach, which is solely software-implemented and tailored for resource-constrained contexts. To classify hand gestures with high accuracy and minimal computing complexity, the network analyzes input from infrared (IR) sensors. Particular care is taken to reduce the model's memory and processing needs without sacrificing recognition efficiency. The system is tested using a variety of hand gestures and shows that, despite having little hardware resources, it is capable of quickly and accurately recognizing movements. The software solution offers a scalable method for integrating gesture detection systems into a range of HCI applications on wearable and embedded devices. The system demonstrated competitive performance and low power consumption following rigorous testing. This study demonstrates the practical application of lightweight, software-driven machine learning models in fields including home automation, assistive technology, and robotics.

关键词： Hands Program processors Power demand Computational modeling Neural networks Gesture recognition Robot sensing systems Real-time systems Sensor systems Testing

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A Lightweight Network Deployed on ARM Device for Hand Gesture Recognition

A Lightweight Network Deployed on ARM Device for Hand Gestur...

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2025 international conference on Intelligent Control, computing and communications, IC3 2025

作者： Shreyas, P.S. Hegde, Varshith V. Shetty, Shivaneeth Keshav Bhandary, Shreevanth R. Kotari, Manjunath Alva's Institute of Engineering and Technology Mijar Moodbidri India

ISBN: (纸本)9798331527495

关键词： Integration testing

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Deep Transfer Learning in Parasites Imaging: A Systematic Review 5th

Deep Transfer Learning in Parasites Imaging: A Systematic Re...

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5th international conference on computing, communications, and Cyber Security, IC4S 2023

作者： Kumar, Satish Arif, Tasleem Department of Information Technology BGSB University Rajouri185131 India

ISBN: (纸本)9789819773701

Transfer Learning (TL) is a method that uses convolutional neural networks to improve performance on a new task by leveraging previously acquired knowledge from related tasks. It has been particularly useful in medical image analysis, where data scarcity can be an issue. TL has helped save time and resources. However, most of the research conducted on this topic has arbitrarily applied transfer learning. This review paper aims to provide clear guidelines on how to select appropriate models and TL methods for medical image categorization. This comprehensive review thoroughly examines the current status of research on the use of deep-transfer learning algorithms for parasite imaging. We obtained 300 research papers from four databases, such as ACM, PubMed, Springer, and Web of Science. We followed the retrieve and filter process for paper selection, and 247 studies were found to be relevant to the scope of our review. Our review focused on papers related to selecting backbone models and transfer learning techniques such as feature extractor, feature, fine-tuning, and other attributes from scratch. The review covers a range of topics related to parasite imaging, including the parasites studied, the imaging methods used, the techniques for transfer learning, the datasets employed, the performance metrics analyzed, and the challenges faced. Additionally, we identify trends, advancements, and future possibilities in the area of TL parasite imaging. By conducting this study, we aim to provide insights into the effectiveness, limitations, and potential of TL techniques in parasite identification. Ultimately, our goal is to contribute to the enhancement of diagnostic technologies, leading to better healthcare outcomes for patients with parasitic disorders. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Automatic Door Opening System Using RFID and Arduino System

Automatic Door Opening System Using RFID and Arduino System

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Intelligent Control, computing and communications (IC3), international conference on

作者： Shashidhar Ramaraddi Inamati Sinchana HV Narendra R N Priyanka CM Ajay Kumar Dwivedi Vivek Singh Department of Electronics and Communication Engineering Nagarjuna College of Engineering and Technology Bengaluru India

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

Among the many potential applications of inexpensive radio frequency identification (RFID) technology are security, tracking assets, people monitoring, supply recognition, and access control. This project's principal objective is to design and develop a digital security system suitable for deployment in a restricted area that can only be accessed by authorized users. As part of our security system, we included a mechanism to lock the doors. The system is able to do the job because it uses RFID technology in conjunction with Arduino. The system obtains the user's unique identification (UID) and checks it against the stored UID when the RFID scanner at the entry detects an RFID tag. Access is given or refused based on whether the user's captured UID matches one of the stored UIDs. The system's three most important components are an electrical locking mechanism, an Arduino microcontroller, and an RFID reader module. The RFID reader will verify the card's validity, and then the Arduino microcontroller will use that information to start the lock. The results prove without a doubt that the system is an efficient, dependable, and cost-effective way to give or restrict access in a protected setting.

关键词： Wireless communication automation Microcontrollers Employment Security Reliability RFID tags Monitoring Radiofrequency identification Intelligent control

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A Study on LiFi and Visible Light Data Connectivity Exploring High-Speed, Secure Data Transmission in Wireless Communication

A Study on LiFi and Visible Light Data Connectivity Explorin...

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2025 international conference on Intelligent Control, computing and communications, IC3 2025

作者： Sharma, Swati Chandrashekar, Rakesh Begum, Rowsonara Singh, Navdeep Inti, Lakshmi Bindhu Shakir, Sarah Abbas Galgotias university Department of Electrical Electronics & Communication Engineering Uttar Pradesh Gerater Noida203201 India New Horizon College of Engineering Bangalore India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India Lovely Professional University Phagwara India Griet Department of Information Technology Bachupally Telangana Hyderabad India College of Medical Technology The Islamic University Radiology Techniques Department Najaf Iraq

ISBN: (纸本)9798331527495

As an innovative wireless communication technology, LiFi, derived from visible light to transmit data, will be a new choice of alternative to classical radio frequency (RF) communications. Data can be transferred backward and forth between the user and a computer with high speed using rapid modulation of LED light bulbs, a technique known as LiFi. An Internet of Things (IoT) based visible light data connectivity system for efficient data transmission over LiFi technology is introduced in this paper in the form of IoTVLDC. Visible light communication (VLC) smart systems are called LiFi., they make use of enhanced bandwidth and resistance to electromagnetic interference. LiFi can operate within the 60 GHz spectrum and achieves data rates in excess of 10 Mbps, compared to the several Mbps reacheable through conventional WiFi systems. Several gaps exist: in particular, how LiFi performs in dynamic environments and energy efficiency metrics, as well as how it can coexist with RF based systems. This study will then evaluate these aspects and propose a hybrid system that combines traditional technologies and LiFi to provide seamless connectivity between lit and non lit. The study will also examine the possibility of its use in real world IoT applications, for example smart homes, industrial automation and secure communications in networks. This paper will demonstrate through extensive experimentation that LiFi technology can provide sustainable, secure, and more efficient communication solutions for the future of wireless networking. © 2025 IEEE.

关键词： Bandwidth

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Implementing Blockchain for Transparent and Secure Financial Transactions in the Modern Business World

Implementing Blockchain for Transparent and Secure Financial...

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Intelligent Control, computing and communications (IC3), international conference on

作者： Ali Saeed K Swetha Navdeep Singh Mohit Yadav R J Anandhi Akila Venkatraman Radiology Techniques Department College of Medical Technology The Islamic University Najaf Iraq Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Telangana India Lovely Professional University Phagwara India Department of Electrical Electronics & Communication Engineering Galgotias university Gerater Noida Uttar Pradesh Department of Information Science Engineering New Horizon College of Engineering Bangalore India Department Of Information Technology GRIET Bachupally Hyderabad Telangana India

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

The main point of this study is to find out how blockchain technology might be able to help make business financial deals safer and more open. Blockchain technology is changing the financial world because it creates a global record system that can't be changed. These tools are making this change happen. Three parts are used in the method given to create a safe system: the Elliptic Curve Digital Signature Algorithm, Proof of Work agreement, and Merkle Trees. In this method, Merkle Trees are also used. These techniques are used by this system to investigate not only the data, but also the security of the cryptography and the proof that comes from outside the system. To find out how well firewalls, audit trails, SSL encryption, multi-signature wallets, and role-based access control work, the components must be compared to them. Using this method could have several benefits, such as decentralization, immutability, openness, correctness, foreign access, automation of smart contracts, and increased efficiency. According to the study, blockchain technology can make information easier to find, speed up financial transfers, and reduce concerns about security.

关键词： Technological innovation Firewalls (computing) Smart contracts Proof of Work Blockchains Encryption Stakeholders Financial services Business Intelligent control

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Leveraging Machine Learning for Dynamic Resource Allocation in Cloud automation

Leveraging Machine Learning for Dynamic Resource Allocation ...

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

作者： Ahluwalia, Gunveen Suresh, Vaibhav Goutham Praveena, M. D. Anto Acharjya, Kalyan Paridaname, Trushna Chitkara University Chitkara Centre for Research and Development Himachal Pradesh Baddi174103 India Karnataka Bangalore India Sathyabama Institute of Science and Technology Department of Computer Science and 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

Cloud automation enables the dynamic management and allocation of resources in a computing environment and is one of the most common uses available. Yet despite their power when cloud systems were simple and small, traditional approaches to allocating resources have proven far less feasible lately. This scenario has also created the need for new evolution methods that will adapt to dynamic cloud environments and improve the system's overall performance. A solution to this challenge comes from machine learning, which has been increasingly used recently. ML algorithms can process vast amounts of data and identify patterns and trends to predict resource use and user needs. Deep learning helps cloud-enabled automation systems adapt in real-time to changing conditions, distribute resources efficiently and improve user experience. For example, reinforcement learning and deep learning are ML techniques that can be applied to resource allocation algorithms or demand prediction models to increase accuracy. Integrating cloud automation and machine learning brings effectiveness in dynamic resource allocation, boosting the overall performance of a system, which leads to savings, better experience, and greater flexibility in using cloud resources. Reinforcement and deep learning are machine learning techniques to optimize order allocation algorithms and enhance demand estimation models. © 2025 IEEE.

关键词： Learning algorithms

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Development of Digital Telecommunication to Analyse and Store Complex Media Data: A Way to Data Engineering

Development of Digital Telecommunication to Analyse and Stor...

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Advances in Computer Science, Electrical, Electronics, and Communication Technologies (CE2CT), international conference on

作者： Yesu Ratnam Pachigolla Pflugerville Texas

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

In the era of digital world data flows are saturated with development of universal multifunctional system to solve problems and to optimise the computing resources. The information system is highly loaded with modern data and large number of resources. The user request and heterogeneity of the incoming streams can be evaluated using different types of multimedia services and its requirement for computing resources and its performance with the entire data. The incoming flow of data heterogeneity is considered as the distinctive feature of request in the modern information system to support different types of multimedia services in single platform. Large volumes of data and data heterogeneity Creates numerous problems related to data storage security and the speed of digital system. To address these challenges artificial intelligence technology can be used for execution of digital telecommunication complex for processing and storing the dynamic flow of data that are in multi format. The prospects and trends can be identified to develop these models based on the perspective characteristics. The development of digital communication with multi object analytic system for storing and analysing complex data with data engineering. An fuzzy based model is used for data processing with enhanced accuracy of 98%.

关键词： Memory Multimedia computing Streaming media Media Data engineering Data processing communications technology Artificial intelligence Streams Information systems

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AI-Powered Warehouse Management: Autonomous Mobile Robots and Advanced Optimization with NFC, MILP, and Swarm Algorithms

AI-Powered Warehouse Management: Autonomous Mobile Robots an...

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international conference on Wireless communications, Signal Processing and Networking (WiSPNET)

作者： Jyothi Bobba Ramya Lakshmi Bolla Rajeswaran Ayyadurai Karthikeyan Parthasarathy Naresh Kumar Reddy Panga Sandhya Rani Lead IT Corporation Illinois USA ERP Analysts Ohio USA IL Health & Beauty Natural Oils Co Inc California USA LTIMindtree Tampa USA Virtusa Corporation New York USA School of Computing and Information Technology REVA University India

ISBN: (数字)9798331524227

ISBN: (纸本)9798331524234

Warehouse automation, coupled with slightly increased outlay executions and a task distribution process, has become an exceedingly fundamental supply chain operation in modern-day reality. In this article, an AI-Refined framework is proposed that combines Automated Mobile Robots, Near-field Communication, Mixed Integer Linear Programming, and swarm algorithms that would result in maximal efficiency within the warehouse. The proposed design examines swarm techniques for task distribution, and NFC for seamless data sharing, MILP for tactical optimization, combined with AMRs for automation; all directed toward reducing inefficiencies and enabling real-time decision-making. The main objectives of this framework include maximization of resource utilization, enhancement of efficiency, scalability, adaptability, and support for dynamic supply chain management. Experimental results showed that the proposed framework performed better than conventional techniques, with an accuracy of 94%, an F1 score of 95%, and a scalability score of 92%. This gives an insight that integrated methods can really help ameliorate the operations in the warehouse. Finally, this research has shown the enormous capability of AI automation with regards to the resource management, process enhancement, and solving critical issues set in warehousing that will start offering a more intelligent and flexible logistics solution.

关键词： automation Scalability Heuristic algorithms Supply chains Warehousing Signal processing algorithms Real-time systems Resource management Mobile robots Optimization

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