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Enhancing Quality control in the Age of Industry 4.0 through Real-Time Automation and Big Data Analysis 15

Enhancing Quality Control in the Age of Industry 4.0 through...

引用

15th international conference on computing communication and networking Technologies, ICCCNT 2024

作者： Bhosale, Nilesh Sollapur, Shrishail B. Borade, Monali Ravindra Vijayalakshmi, V.J. Aulakh, Damanjeet Kodmalwar, Pratik Yeshwantrao Chavan College of Engineering Department of Applied Mathematics and Humanities Nagpur India School of Engineering and Technology Department of Aerospace Engineering Karnataka Bangalore India Vishwakarma Institute of Technology Department of Ai & Ds Pune India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore641021 India Datta Meghe Institute of Management Studies Department of Mba India

ISBN: (纸本)9798350370249

Industry 4.0 has transformed industries, with intelligent and automated systems introduced into the manufacturing process on a larger scale. But this shift introduces problems of scale that still need to be solved using traditional quality control measures - manual inspections may take time and leave space for human error. Summary: This paper introduces a new solution for improving quality control in the era of Industry 4.0 using real-time automation and extensive data analysis as an abstract. This eliminates human error and ensures that all inspections are performed in the same way to produce consistent and accurate results. Moreover, the information from these automated activities can be examined in genuine time for repetition and real-time anomaly identification, helping to maintain adequate quality control action. To sum up, using real-time automation and big data analysis can significantly improve quality control by ensuring that products are sent off on time in top working conditions under Industry 4.0 methodological processes. This benefit is a better quality product and more productivity and cost-effectiveness for industries from manufacturing the products. © 2024 IEEE.

关键词： Accurate Results Adequate Quality Intelligent Largerscale Transformed Industries

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A Simplified Approach of Voice Authentication and Device control 14

A Simplified Approach of Voice Authentication and Device Con...

引用

14th international conference on computing communication and networking Technologies, ICCCNT 2023

作者： Shreya, S. Goel, Raghav Katariya, Priyanshi Kamboj, Harshit Kashyap, Nirbhay Amity University Department of Computer Science and Engineering Noida India

ISBN: (纸本)9798350335095

The objective of this paper is to propose a method for safeguarding user privacy in a designated environment by utilizing speech patterns to differentiate genuine users from fraudulent or cloned speech users or to grant access to specific features. To achieve this, we systematically classify a dataset of seven hundred and fifty audio recordings where multiple speakers, including the authors of this paper, articulate the same word for an identical duration. The key factor that distinguishes each speaker is their unique speech delivery pattern, frequency, and pitch. The findings of this study will contribute significantly to creating a secure environment for users to interact. © 2023 IEEE.

关键词： Machine learning

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Design of Event Trigger control System Based on Output Feedback Event Trigger control Algorithm

Design of Event Trigger Control System Based on Output Feedb...

引用

2023 international conference on networking, Informatics and computing, ICNETIC 2023

作者： Lin, Meihuan Wu, Weilin Guangxi Minzu University Guangxi Nanning530006 China

ISBN: (纸本)9798350313314

In recent years, with the continuous development of network communication technology and control theory, Networked control system (NCS) has been paid more attention and developed rapidly. Compared with the traditional control system, this system has great advantages. It can build a closed-loop feedback control system in a larger area without the need of point-to-point connection. The remote transmission of semaphore depends on digital communication network, which improves the execution efficiency and flexibility. From the feedback signal of the system, state feedback control and output feedback control are two basic feedback control methods. Because the output feedback is generally measurable, it has certain advantages compared with the state feedback. In this paper, based on the event triggered control, the sampling based event triggered control is studied;Then, the event triggered control is extended to discuss the advantages of self triggered control over event triggered control. Because the event triggered control is controlled by error, the measurement error of local combined state is defined. Then, the event trigger function is given after deduction. Finally, it is proved that Zeno behavior of the system is excluded. © 2023 IEEE.

关键词： Networked control systems

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A Hybrid Cryptographic Algorithm for Resource-Constrained IoT Devices 5

A Hybrid Cryptographic Algorithm for Resource-Constrained Io...

引用

5th IEEE international conference on computing, Power, and communication Technologies, IC2PCT 2024

作者： Florence, S. Metilda Alban, Stavin Mogalipuvvu, Harish Srm Institute of Science and Technology Department of Networking and Communications Kattankulathur India

ISBN: (纸本)9798350383522

In the modern digital age, data security stands as a very important priority. The increasing need for lightweight devices and their resource-constrained environments calls for certain cryptographic solutions that can enhance security while optimizing performance. This research focuses on the creation and evaluation of a hybrid cryptography algorithm, combining the strengths of Attribute-Based Encryption (ABE) and Elliptic Curve-based Cryptography (ECC). Through a thorough assessment of this amalgamation, our study seeks to examine its potential to enhance security and performance in resource-constrained environments. The outcomes of this research could offer professionals and researchers a novel and potent tool for safeguarding information in lightweight devices present in resource-constrained environments. © 2024 IEEE.

关键词： Access control Computational efficiency CP-ABE Data security ECC Hybrid encryption algorithm

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IoT - Based Quality Monitoring and control Automation in Dairy Industry 15

IoT - Based Quality Monitoring and Control Automation in Dai...

引用

15th international conference on computing communication and networking Technologies, ICCCNT 2024

作者： Priyadharshini, N. Kiruthika, S. Radha, J. Vaishya, R. Pranavi, D. Sasidharan, P. Kongu Engineering College Perundurai India Kongu Engineering College Department of Physics Perundurai India Nandha Engineering College Department of CSE Perundurai India

ISBN: (纸本)9798350370249

Milk is the essential basic product in day-to-day life which undergoes a series of essential processes from production to consumption. The industry faces a significant challenge in ensuring the freshness and quality of milk during storage and transportation. The primary objective of the proposed work is to develop an integrated system that enables dairy industries to remotely monitor and control parameters such as temperature, pH value and level of the milk in the tank using Internet of Things (IoT) technology. It incorporates components such as DS18B20 temperature sensor for accurate temperature monitoring, an ultrasonic sensor for precise level detection in the tank and a pH sensor for monitoring the pH value. These sensors are integrated with an Arduino UNO microcontroller, which serves as the central processing unit for data collection and control. When the temperature goes above the range of 5° C the controller activates the chiller thereby the temperature is maintained within the range of 4-5° C. The values of temperature, pH and the level of milk are monitored and displayed in the LCD. Additionally, IoT connectivity is facilitated through the ESP8266 module enabling remote access of the system via the Blynk App. Integration with the Blynk App offers a user-friendly interface for remote interaction, empowering dairy operators to monitor the chiller performance and the quality of the milk in the dairy sector. © 2024 IEEE.

关键词： Tanks (containers)

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Resilient Fog-Based Adaptive Traffic control System 14

Resilient Fog-Based Adaptive Traffic Control System

引用

14th international conference on computing communication and networking Technologies, ICCCNT 2023

作者： Matange, Ashwini Taneja, Varun Chaumal, Aarya Buwa, Pallavi Abraham, Jibi Coep Tech Dept. of Computer Engineering and Information Technology Pune India

ISBN: (纸本)9798350335095

Traffic congestion is a growing problem in India, largely caused by the increasing number of vehicles. To address this, creating an adaptive traffic control system has become essential. To present a solution, this paper aims to create a resilient, adaptive traffic control system that dynamically adjusts signal timings based on the current traffic density. The paper proposes introducing a Fog layer at each traffic junction to capture real-time video feeds and process them locally, with the final decision about dynamic signal control being taken in the Cloud. The validity of the solution is tested through simulations in SUMO. A Machine Learning model is trained in the Cloud to predict expected vehicle numbers to set adaptive signal times for contingency situations. The paper aims to demonstrate the resilience and performance of the system with the adaptive traffic signal control algorithm, potentially offering a solution to traffic congestion in India. © 2023 IEEE.

关键词： Traffic congestion

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Minimal Parameter Estimation Based Non-Linear control of Hexarotors With Uncertainty in Mass 14

Minimal Parameter Estimation Based Non-Linear Control of Hex...

引用

14th international conference on computing communication and networking Technologies, ICCCNT 2023

作者： Ashima, C.R. Kanagalakshmi, S. National Institute of Technology-Calicut Electrical Engineering Department Calicut India

ISBN: (纸本)9798350335095

Dynamics of a hexarotor contain non-linearities and uncertainties in the system parameters. The purpose of this study is to design a self-learning controller to track the altitude commands given to a hexarotor and achieve a stable hovering position amidst uncertainties in mass due to changes in the payload. The backstepping controller is a Lyapunov based controller which can accurately control and stabilize the vehicle when plant dynamics are completely known. While adaptive backstepping controller employs a dynamic feedback law with which it adapts to changes in the physical parameters. In this work, a Lyapunov based backstepping control law is first developed for a hexarotor platform, later an adaptive backstepping control is also introduced to nullify any destabilizing uncertainties in mass and thereby achieve stable hovering. Numerical simulations are performed on the MATLAB platform with variation in mass incorporated to test the effectiveness of the proposed control strategy. Software implementation of the system gives satisfactory results. © 2023 IEEE.

关键词： MATLAB

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VANET Congestion control and Stability Performance Analysis using Seagull Optimization Deep Learning 15

VANET Congestion Control and Stability Performance Analysis ...

引用

15th international conference on computing communication and networking Technologies, ICCCNT 2024

作者： Niaz Ahamed, V.M. Sivaraman, K. Bharath Institute of Higher Education and Research Department of Computer Science and Engineering Tamil nadu Chennai73 India

ISBN: (纸本)9798350370249

Significant matters in VANET environment include high vehicle versatility, changing vehicle thickness and dynamics between vehicle separating. Therefore, improved routing protocol enhances overall performance of VANET through intermittent service availability. In this regard, a group-based AI technique is implemented to predict VANET mobility. Effective routing based on a hybrid metaheuristic algorithm combined with Ensemble Learning produces significantly improved results. Vehicle Ad Hoc Networks (VANETs) are currently used in various applications such as transportation using vehicle-to-vehicle multi hop wireless communication since they offer scalable and cost-effective solutions for it. On the other side, multi-hop communication development is regarded as a challenging task in VANET conditions due to rapid alterations of periodic and topological network breakdowns. In general, mobile ad hoc routing protocols, this leads to failure of routing or its invalidation. In order to solve the problem of routing and get multi-constrained QoS (quality of service) measures in VANETs, numerous research works have been conducted on it. Another aspect for application is traffic collision control. Unfortunately, there are hardly any sensors anywhere which make it basically impossible to obtain continuous information about traffic states. Accurate predictions about traffic flow are difficult because road accidents and public events cannot be predicted in advance and both these can essentially affect the traffic flow. This article reports the framework of Seagull Optimization Deep Learning for predicting accuracy and experiments various nodes. This framework exhibition focuses on different vehicle flows, position rates, and road organization typologies. Our framework effectively reduces the general waiting time of vehicles during aggregation and shortens the vehicle travel season even when the location rate is low. © 2024 IEEE.

关键词： Congestion control (communication)

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Efficient Approach for Epileptic Seizure Classification and Detection based on Genetic Algorithm with CNN-RNN Classifier 3

Efficient Approach for Epileptic Seizure Classification and ...

引用

international conference on advances in computing, communication and Applied Informatics (ACCAI)

作者： Priyanka, R. Sathesh, M. Selvi, Tamil T. Saikumar, P. Janardhan Venkatachalam, K. Raja, M. SRM Inst Sci & Technol Sch Comp Dept Networking & Commun Coll Engn & Technol KTR Campus Chengalpattu India Vel Tech Rangarajan Dr Sagunthala R&D Inst Sci & Dept ECE Chennai Tamil Nadu India Sri Sai Ram Engn Coll Dept Elect & Instrumentat Engn Chennai Tamil Nadu India Audi Sankara Coll Engn & Technol Dept ECE Gudur India Audi Sankara Coll Engn & Technol Gudur Dept Elect & Commun Engn Gudur India Saveetha Inst Med & Tech Sci Saveetha Sch Engn Dept ECE Chennai Tamil Nadu India

ISBN: (纸本)9798350389432;9798350389449;9798350389456

One of the most physically and psychologically damaging neurological conditions that affect people of all ages is an epileptic seizure. The abnormality should be recognized early so that the proper treatment is timely. It is possible only with advanced signal processing techniques to distinguish and predict epileptic patterns in which substantial effort is invested. Therefore, efficient seizure detection and classification methods are proposed for machine learning and deep learning algorithms. The proposed method uses deep and machine-learning algorithms for seizure detection and classification. The objective is to analyze the performance and efficiency of deep and machine learning classifiers by comparing the various classifiers. This proposed work uses 11,500 EEG data samples from the UCI machine learning repository. To suggest an Improved Fitness Function Genetic Algorithm (IGA) technique for optimal feature selection to improve the detection rate and CNN-RNN algorithm used as the classifier. The analysis proved that the hybrid CNN-RNN(LSTM with GRU) classifier with GA-based feGA-based-lection provides better densification accuracy results of 98% when compared with all other classifiers.

关键词： Epileptic Seizures Genetic Algorithm Convolutional Neural Network Recurrent Neural Network Classification Algorithm

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Linear Position control for the Autofocus of Cameras Using Wavelet Decomposition 3

Linear Position Control for the Autofocus of Cameras Using W...

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3rd international conference on Smart Generation computing, communication and networking, SMART GENCON 2023

作者： Kulkarni, Jayant Patankar, Sanika Bhanuse, Vijaykumar Kekan, Vijay Kerkar, Kimaya Mandlik, Chinmaya Lohar, Durva Lokhande, Hrishikesh Maharashtra Pune411037 India

ISBN: (纸本)9798350319125

Automated focus adjustment is a critical aspect of modern camera systems, enabling the capture of sharp and clear images. This paper's novel approach is to automate focus adjustment using wavelet decomposition. The image is decomposed into different frequency subbands using wavelet transform. By computing a focus measure using each subband which quantifies the sharpness or clarity of the image at that particular time, the optimal focus position is found. The algorithm effectively searches for the position that maximises the overall image sharpness and gives the accurate focused image. A web Camera, linear actuator and Arduino UNO microcontroller is used in the project. © 2023 IEEE.

关键词： Arduino UNO Autofocus camera Focus measure Linear actuator Wavelet decomposition

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