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检索条件"任意字段=2023 Intelligent Computing and Control for Engineering and Business Systems, ICCEBS 2023"

共 3241 条记录，以下是191-200 订阅

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Convenient Way of Accessing Multimedia Functions Using Ml and Open CV

Convenient Way of Accessing Multimedia Functions Using Ml an...

引用

2023 intelligent computing and control for engineering and business systems, iccebs 2023

作者： Hemavathi, C. Vivekanandhan, G. Cibi, C. Abhinav Krishna, R. Velmurugan, K.Jayasakthi Kavitha, D. Sri Sairam Engineering College Cse Department India Saveetha School Cse Department India

ISBN: (纸本)9798350394580

In current world, most of the activities are machine-used and the existing systems to human computer interaction is not sufficient or efficient. So this paper demonstrates the idea to facilitate the interaction by using hand movement with help of Arduino sensor. This innovative approach harnesses the power of gesture recognition, enabling users to control and manipulate digital interfaces effortlessly. By bridging the physical and virtual realms, this technology opens new avenues for creative expression, efficient task execution, and enhanced user experiences. This paper delves into the realm of human-computer interaction through Arduino sensor-based hand movement, exploring the underlying principles, applications across various domains, and the potential to reshape the way we interact with computers. © 2023 IEEE.

关键词： Arduino sensor Gesture recognition

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IOT Based Optimized Load Scheduling and Automation on Charging EV

IOT Based Optimized Load Scheduling and Automation on Chargi...

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2023 intelligent computing and control for engineering and business systems, iccebs 2023

作者： Maheswari, E. Balaji, V. Ezhilarasi, G. Lakshmi, D. Srikanth, R. Goakul, B. Sri Sai Ram Instiute of Technology Department of Eee Chennai India MAI-NEFHI College of Engineering and Technology Department of Electrical Engg. Eritrea Amet Deemed to Be University Department of Eee Chennai India Mu Sigma Business Solutions Pvt. Ltd Chennai India Tata Consultancy Services Chennai India

ISBN: (纸本)9798350394580

To ensure the safety of vehicles and riders, researchers are still working on accurate monitoring, estimation of State of Charge (SOC), State of Health (SOH), and early detection of rechargeable battery failures in electric cars. The locally optimum scheduling strategy is robust against the dynamic arrival of EVs and scalable to a large EV population. In order to successfully flatten the demand profile of the electric system, an intelligent scheduling technique may be used to schedule EV charging patterns. This will reduce operating costs and potential capital expenditures. An increasingly important stage in the adoption of smart grids is intelligent scheduling for EV charging and discharging. © 2023 IEEE.

关键词： Charging Unit Cloud Server EV battery Internet of things Microcontroller Node MCU

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Location Based Disaster Report

Location Based Disaster Report

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2023 intelligent computing and control for engineering and business systems, iccebs 2023

作者： Fathima Mubarakkaa, M. Anish, T.P. Balasubramaniyan, N. Selvakumar, C. Balamurugan, S. Sri Sairam Engineering College Tamilnadu Chennai India R M K College of Engineering and Technology Tamilnadu Chennai India

ISBN: (纸本)9798350394580

Disasters of various types and magnitudes afflict regions worldwide, necessitating a comprehensive understanding of their causes, characteristics, and impacts. Preparedness measures are paramount in mitigating the fear and losses that accompany such events. This research addresses the imperative for disaster preparedness by developing a novel informatics approacha region-wise repository and prediction web application. The primary objective of this project is to lower the risk of disaster impact by creating a repository that not only catalogs the types of disasters but also recommends necessary precautions, contingent upon the user's location. Each geographical region's susceptibility to specific disasters is unveiled, facilitating informed decisions regarding housing construction and disaster resilience. Furthermore, this paper emphasizes the colossal human and economic toll of disasters and highlights the pivotal role of the web application in constructing a region-wise disaster repository. By favor of web scraping techniques and machine learning algorithms, this application generates detailed predictions and offers needed precautionary guidance. This research represents a significant advancement in disaster preparedness, empowering individuals and communities to proactively safeguard against the catastrophic consequences of unforeseen events. © 2023 IEEE.

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An Analysis of the Strategic Approach to Utilizing Deep Learning for the Purpose of Predicting Stock Prices

An Analysis of the Strategic Approach to Utilizing Deep Lear...

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2023 intelligent computing and control for engineering and business systems, iccebs 2023

作者： Venkatesh, P. Ilakkiya, T. Ramu, M. Manikandan, M. Senthilnathan, C.R. Sri Sairam Engineering College Department of Management Studies Chennai India Sri Sairam Institute of Technology Chennai India Sri Sairam Engineering College Chennai India

ISBN: (纸本)9798350394580

Stock price forecasting for extended periods of time is notoriously challenging, so it pays to create a solid algorithmic groundwork before delving in. Due to the interconnected nature of stock prices imposed by market dynamics, accurate price forecasting is difficult. The suggested method employs artificial intelligence techniques like recurrent neural networks and Long Short Term Memory to anticipate the share price based on market data. The system's visualizations can now be informed by the training and validation outcomes obtained across several dimensions of input data. The results are promising, suggesting that an LSTM model can be used to forecast the stock market. © 2023 IEEE.

关键词： Long & Short term memory Machine Learning Price forecasting Risk Stock Market prediction

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Cybug - The Malicious File Detecting Software

Cybug - The Malicious File Detecting Software

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2023 intelligent computing and control for engineering and business systems, iccebs 2023

作者： Saradha, K.R. Kavin, T. Udayakumar, G. Abdul Kalam, K.U.A. Gayathri, S. MacRiga, G. Adiline Sri Sairam Engineering College Department of Information Technology Chennai India

ISBN: (纸本)9798350394580

The most significant fact of ages is that when we install Antivirus software, our system is safe from viruses. But what if we prove it wrong, The most classic and effective way to hack or spread viruses into systems is by malicious files. These are done by sending an infected file to the user and this file bypasses the antivirus software using its blind spots to its advantage to evade the software. When you just click on it the virus file also runs in the background and the system's security is being compromised. So, We have planned to build full-fledged software that will be going to detect these infected files. © 2023 IEEE.

关键词： File Malicious Software Virus

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Image-Based Plant Disease Detection Using Deep Learning

Image-Based Plant Disease Detection Using Deep Learning

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2023 intelligent computing and control for engineering and business systems, iccebs 2023

作者： Gayathri, S. Pradeep, S. Aziz, Azrina Abd Sri Sairam Engineering College Department of Electronics and Communication Engineering India Universiti Teknologi Petronas Department of Electrical and Electronics Engineering Malaysia

ISBN: (纸本)9798350394580

Due to the nation's rapid population expansion and rising food consumption, agriculture is essential to India's economy and people. Consequently, agricultural yields need to rise. Crops produce so little as a result of diseases brought on by bacteria, viruses, and fungi. Adopt techniques for identifying plant diseases to stop it. To diagnose diseases since they lay a high emphasis on the data themselves and provide significance to the results of certain tasks using algorithms. Here, a method for employing CNN to find plant diseases has been proposed. To ascertain the size of the sick area and the time complexity, simulation studies and analyses are conducted on sample photos. It is accomplished using image processing methods. There are 32 different classes, including three courses focused on plants (apple, potato, and tomato), have been fed to the model. The total number of sick plant leaves is 24, including those that are impacted by diseases like Apple Rust and others. Different performance matrices are built and jointly trained using the ResNet architecture to categorize the images of sick and healthy leaves for the same produced datasets of leaves. When compared to other models like the Random Forest and SVM, the model's output exhibits superior accuracy, which is 99.2%. © 2023 IEEE.

关键词： Accuracy Convolutional Neural Network Diseased and Healthy leaf ResNet

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Prediction of Depression using the KNeighbors-Classifier Algorithm Compared for Improved Accuracy with Support Vector Machine

Prediction of Depression using the KNeighbors-Classifier Alg...

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2023 intelligent computing and control for engineering and business systems, iccebs 2023

作者： Mahesh, Biyyapu Amanullah, M. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamilnadu India

ISBN: (纸本)9798350394580

The intention of the research is to regulate the level of precision via comparing the Support-Vector-Machine(S-V-M) algorithm and KNeighbors Classifier for predicting Depression. The proposed machine learning method aims to enhance the accuracy of depression prediction using the S-V-M algorithm, in evaluation with the Novel KNeighbors Classifier. The training dataset comprises two groups, with 10 individuals in each group. The example size calculation conducted via a pretest control of 80%, a significance level of 0.05%, then a 95% sureness interval. When associated to the current system, which has an accurateness of only 84%, it remained originate that the future method attained 95% accuracy. Here exists no consequence amid the S-V-M Model then KNeighbors Classifier Prototypical grounded on a example T-test through the p value is 0.000 (p © 2023 IEEE.

关键词： Depression Machine Learning Mental Health Novel KNeighbors Classifier Prediction S-V-M

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Design of Aircraft control System for Accident Prevention

Design of Aircraft Control System for Accident Prevention

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2023 intelligent computing and control for engineering and business systems, iccebs 2023

作者： Puviyarasi, B. Suveka, S. Logaadhashini, G. Shruthi, P.D. Sri Sairam Engineering College Department of Electronics and Instrumentation Engineering Chennai600044 India

ISBN: (纸本)9798350394580

In recent years, aircraft accidents have highlighted the critical need for advanced control systems to enhance flight safety and prevent catastrophic events. The proposed control system utilizes high-precision sensors (accelerometers, gyroscopes, radar, optical) to gather real-time data on the aircraft's position, orientation, speed, and environmental conditions. intelligent algorithms and predictive models process this data to accurately assess risks and predict hazardous scenarios Adaptive control algorithms dynamically adjust control surfaces, engine thrust, and flight control parameters to maintain stability and maneuverability. The system prioritizes proactive measures, employing predictive algorithms to anticipate hazards and adjust the aircraft's configuration and trajectory. The proposed control system will undergo rigorous testing through advanced simulations and real-world flight trials. Its performance and effectiveness in preventing accidents will be evaluated across various scenarios. By combining cutting-edge technologies, intelligent algorithms, adaptive controls and pilot assistance, the proposed control system aims to revolutionize flight safety, reducing accidents and ensuring passenger and crew safety. © 2023 IEEE.

关键词： control algorithms fault tolerance sensor fusion etc

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Enhancing Healthcare with Li-Fi Technology

Enhancing Healthcare with Li-Fi Technology

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2023 intelligent computing and control for engineering and business systems, iccebs 2023

作者： Behera, Saswati Kumari Karthikeyan, M. Amose David, A. Evan Singh, M. Mohammed Azeem Affan, A. Sri Sairam Engineering College Department of Electrical and Electronics Engineering Chennai India

ISBN: (纸本)9798350394580

In the pursuit of enhancing healthcare, Li-Fi, a cutting-edge visible light-based wireless communication technology, offers transformative potential in critical settings such as the ICU and OT. Li-Fi's high-speed data transmission in the ICU enables real-time patient monitoring and instant access to electronic health records, aiding rapid decision-making. In the OT, it facilitates precise surgery with low-latency access to critical data and seamless team communication. Furthermore, Li-Fi's inherent security, with its limited signal range and obstruction requirements, safeguards patient data in an environment where privacy is paramount. © 2023 IEEE.

关键词： Intensive Care Unit(ICU) Light Fidelity (Li-Fi) Operation Theatre(OT)

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Power Theft Detection and Protection in Distribution Lines

Power Theft Detection and Protection in Distribution Lines

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2023 intelligent computing and control for engineering and business systems, iccebs 2023

作者： Subiksa, G. Suriyan, N.A. Muralidharan, P. Mukeshwaran, A. Sudharsan, M. Surya Vigneshwar, C. Sri Sai Ram Engineering College Department of Electrical and Electronics Engineering west tambaram Chennai44 India

ISBN: (纸本)9798350394580

A distribution line power theft detection and protection system is developed in this project. Voltage sensor and Microcontroller are used in the system's design. The management of electric distribution system has become increasingly challenging due to an increase in the demand for electricity from residential, industrial, and commercial loads. The main obstacle in the distribution network's efficient monitoring and control has been recognized as a lack of information at the base station regarding its state. An unlawful tapping on a distribution line can be found and protected using an electrical power theft detection and protection system. The instrument used in this project to interface between the power line current and Arduino is an ACS712 series current sensor. Relay used as switching gear to protect power line from power theft. All actions that all devices take are controlled by Arduino. With the help of this system, an electrical power theft may be easily detected and stopped without the need for human intervention. It would also increase the profit margin for the power utility business and reduce overload-related faults. By employing this technique, through which the server received the message when users by passed the meter, it was also feasible to identify electricity theft. In addition to detecting and guarding against power theft, this system also provides billing activities. © 2023 IEEE.

关键词： Distribution Intervention Network Power theft

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