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检索条件"任意字段=International Conference on Advances in Intelligent Control and Computer Engineering"

共 47514 条记录，以下是351-360 订阅

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Utilizing A Deep Learning Model's Hotspot Detection Technique for Uterine Cancer Image Segmentation

Utilizing A Deep Learning Model's Hotspot Detection Techniqu...

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2024 international conference on advances in Data engineering and intelligent Computing Systems, ADICS 2024

作者： Singh, Tonjam Gunendra Karthik, B. Wahengbam, Monita Bharath Institute Of Higher Education And Research Department Of Electronics And Communication Engineering Tamil Nadu Chennai India Bharath Institute Of Higher Education And Research Department Of Computer Science And Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350364828

In gynecology, uterine cancer is the most common. The rise in obesity, diabetes, the number of women who have never given children, and greater life expectancy are all contributing to its rise. The most important is early cancer detection. Artificial intelligence (A.I.) has recently been used to diagnose and cure many diseases and injuries. This study used five distinct kinds of information, encompassing normal, diseased, and benign cells. The suggested methodology comprises three sequential steps. The initial stage was to locate tumor cells in photos using Hotspot - the second stage-trained deep learning models on segmented tumor cells. The final step was choosing the best activation sets from deep learning models of each category (for five datasets) - the selection using Pigeon-Inspired Optimization. The five categories' best activation sets were classified using Softmax. 99.85% was the total accuracy success rate attained using the method recommended due to the classification. © 2024 IEEE.

关键词： Image segmentation

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Human Movement Recognition with Machine Learning Techniques

Human Movement Recognition with Machine Learning Techniques

引用

2024 international conference on advances in Computing Research on Science engineering and Technology, ACROSET 2024

作者： Sinha, Raj Sinha, Pankaj Chandra Tiwari, Meena School of Computer Applications Lovely Professional University Phagwara India Jayoti Vidyapeeth Women's University Department of Computer Science Jaipur India Srist College Department of Cse Jabalpur India

ISBN: (纸本)9798350388800

Human MR (HMR) use of IAs has generated much attention on their applications on various campuses, including health services, deportations, security, and security situations. This research focuses on creating powerful computations and models for data mining and collecting accurate human information as a source of information obtained from sensors, accelerometers, sensors, and wearable devices. Artificial intelligence techniques including deep learning, support vector machines (SVMs), and irregular plots are used to process and analyze sensor information, extraction, and meaningful aspects to separate the results, such as a fireplace, adjustment, senders, parse, and movements compels. The goal is to create HMR brands trusted for preparation to realize accurate information about constant and precise actions, carry out mass medical surveillance, provide Bienstar personalized customization, and create the highest association between people and computers in an intelligent environment © 2024 IEEE.

关键词： Accelerometers

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Enhancing Intrusion Detection System (IDS) Through Deep Packet Inspection (DPI) with Machine Learning approaches

Enhancing Intrusion Detection System (IDS) Through Deep Pack...

引用

2024 international conference on advances in Data engineering and intelligent Computing Systems, ADICS 2024

作者： Bathiri, K.A. Vijayakumar, M. Hindustan Institute Of Technology And Science Department Of Computerscience Engineering Chennai India

ISBN: (纸本)9798350364828

In today's era of ever connecting devices and exponential growth in the number of small networks in every digital workspace, security concerns are also growing rapidly. Intrusion Detection System (IDS) and Intrusion Prevention System (IPS) is a well-known security environment to monitor, detect and prevent malicious activities, however the emerging threats and manually engineered threats and intrusion attempts may not be detected by traditional signature-based security systems. So, this project utilizes Deep Packet Inspection (DPI) to better understand the activity and the purpose of the packets and their data in the network to provide authentic security solutions which provides better detection rates in the face of novel and emerging threats. Further, this project also utilizes various Classification models in an ensemble voting scheme approach to perform the intrusion detection in the network. Deep Packet Inspection also provides more insights on the critical parameters to be included in the dataset to create more realistic data to perform better analysis in an optimal time. This approach to utilize DPI covers the downsides of traditional IDS while providing better detection of novel threats. © 2024 IEEE.

关键词： Intrusion detection

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Automated Unified System for LPG Refill Booking & Lekage Detection: A Pervasive Approach 15

Automated Unified System for LPG Refill Booking & Lekage Det...

引用

15th international conference on advances in Computing, control, and Telecommunication Technologies, ACT 2024

作者： Suraksha, P. Aishwarya Kumari, Kavana L. Dept.of Computer Science and Engineering Vidyavardhaka College of Engineering Karnataka Mysuru India Dept.of Artificial Intelligence and Machine learning Vidyavardhaka College of Engineering Karnataka Mysuru India

ISBN: (纸本)9798331300579

Civilization is becoming increasingly aware of natural resources, it results in the use of propane and butane, and hence the use of *** India most people use the LPG *** per current government regulations, intense demand but shortage in production of LPG cylinder, once a new cylinder is booked we need to wait for some days to get it *** no cost-efficient technique is available which identifies when cylinder is about to get *** this paper we designed, developed, a proven Automated Unified System using smart Pervasive sensors, where LPG retailer requests for a new cylinder using Short Message Service (SMS) once it identifies cylinder will be empty in few days and also provides detection of gas leakage for better service to the consumers and reduce the scope of irregularities. © Grenze Scientific Society, 2024.

关键词： Liquefied petroleum gas

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OpenCV-enabled Gesture control for Smart Devices: A User-Centric Approach 4

OpenCV-enabled Gesture Control for Smart Devices: A User-Cen...

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4th international conference on intelligent Technologies, CONIT 2024

作者： Devi, Priyanka Chadha, Shivani Bhardwaz, Saumyamani Chandigarh University Department of Computer Science and Engineering Mohali India University Institute of Computing Chandigarh University Mohali India

ISBN: (纸本)9798350349900

This research delves into the realm of human-computer-interaction, presenting an innovative user-centric approach togesture control for smart devices. Integrating the powerful OpenCV (Open-Source computer Vision Library), our system demonstrates enhanced accuracy, responsiveness, and user satisfaction in real-world scenarios. The study includes a comprehensive evaluation of the system's performance, addressing identified limitations, proposing improvement strategies, and exploring potential applications in emerging technologies. By analyzing a diverse dataset and employing a Convolutional Neural Network (CNN), our OpenCV-enabled gesture control system showcases its adaptability to varied gestures and environmental conditions. Future directions include addressing limitations, expanding application scopes, and integrating with emerging technologies, positioning this research at the forefront of advancements in gesture recognition technology. © 2024 IEEE.

关键词： Gesture recognition

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Optimization of Construction Processes Using Artificial Intelligence and Big Data Analytics 1

Optimization of Construction Processes Using Artificial Inte...

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1st international conference on advances in computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Sil, Amitava Shenoy, Nandan N Ananthayya, M.B. Yashwanth, M.K. Theerthananda, M.P. Aravinda, P.T. Institute of Wood Science and Technology West Bengal Kolkata India PES Institute of Technology and Management Department of Civil Engineering Karnataka Shivamogga India Sai Vidya Institute of Technology Department of Civil Engineering Karnataka Bangalore India Maharaja Institute of Technology Department of Civil Engineering Mandya Karnataka Mysore India Government Engineering College Department of Civil Engineering Karnataka Chamarajanagara India Government Engineering College Department of Civil Engineering Karnataka Hassan India

ISBN: (纸本)9798331518578

The rise in the Internet of Things (IoT)-based smart building construction process offers an acceptable fix to the challenging issues of energy administration, equitable expansion, and economic optimization as the number of people living in metropolitan areas rises and the desire for eco-friendly lifestyles rises. This study investigates the construction process in smart buildings by offering a deep learning (DL) approach to energy optimization. The investigation outlines a novel architecture that uses DL methods to optimize energy use in IoT-based smart buildings. To enable intelligent energy optimization and performance choices, it leverages current statistics from various resources, such as detectors, gadgets, big data processing, and smart grids. By using DL systems, such as neural networks and recurrent neural networks (RNNs), the suggested method provides accurate demand predictions while adhering to flexible use patterns. The empirical study demonstrates the efficacy of the DL-based approach using actual case investigations and intricate models conducted in multiple intelligent construction processes across the globe. The results demonstrate notable energy consumption drops, financial savings, and noteworthy actions to the eradication of carbon emissions, thus enhancing ecological sustainability. Furthermore, the system's adaptability and scalability demonstrate how it may be used in a range of urban contexts. In addition to addressing contemporary energy optimization in construction process concerns, this research paper lays the groundwork for a more efficient and ecologically responsible metropolitan future. © 2025 IEEE.

关键词： Smart homes

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Steady-state visual evoked potentials based 2D continuous control of brain-computer interface 3

Steady-state visual evoked potentials based 2D continuous co...

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3rd international conference on intelligent Mechanical and Human-computer Interaction Technology, IHCIT 2024

作者： Huang, Dingyong Yang, Xueliang Shen, Hui College of Intelligence Science and Technology National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781510683105

Two-dimensional continuous control based on brain-computer interface (BCI) systems is becoming a research hotspot. However, due to the discreteness in BCI signal decoding, achieving smooth 2D continuous control is often challenging. To address this issue, this paper proposes an innovative 2D continuous control method that converts three discrete commands into continuous ones and validates it through a real-time online BCI system. We used dry electrodes for signal acquisition and applied the Canonical Correlation Analysis (CCA) algorithm for electroencephalography (EEG) decoding. Two simulation experiments were designed: obstacle avoidance for unmanned vehicles and trajectory tracking for unmanned vehicles, to verify the effectiveness of the 2D continuous control method. By analyzing experimental data from three subjects and multiple evaluation metrics, we comprehensively and thoroughly assessed the proposed method. © 2024 SPIE.

关键词： Electroencephalography

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AI-Optimized Irrigation for Sustainable Agriculture

AI-Optimized Irrigation for Sustainable Agriculture

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2024 international conference on advances in Data engineering and intelligent Computing Systems, ADICS 2024

作者： Hussain, Mansoor Karthikeyan, N. Maurya, Ipsit Sinha, Subhratha School Of Computer Science And Engineering Vellore Institute Of Technology Chennai India School Of Electornics And Engineering Vellore Institute Of Technology Chennai India

ISBN: (纸本)9798350364828

This paper presents an innovative AI-enhanced irrigation system designed to optimize water management in agriculture. The system integrates advanced technologies such as IoT, sensor networks, and artificial intelligence algorithms to achieve precise and efficient irrigation scheduling. Leveraging real-time data from sensors including soil moisture, temperature, and humidity, combined with historical weather forecasts, the system employs a dynamic algorithm to make informed irrigation decisions. Experimental evaluation conducted over a week-long period using a garden rose as a test subject demonstrated the system's ability to maintain optimal soil moisture levels within the range of 60-75%, while significantly reducing water consumption compared to conventional methods. Simulation results further validated the system's effectiveness in predicting soil moisture levels and optimizing irrigation scheduling. Key metrics including enhanced crop output, reduced water usage, and adherence to sustainable farming practices were used to assess the superiority of the proposed model. Overall, the AI-enhanced irrigation system presents a promising solution for sustainable agriculture, offering improved water conservation, enhanced crop productivity, and efficient resource utilization. © 2024 IEEE.

关键词： Water conservation

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IoT-Enabled Black Box for Driver Behavior Analysis Using Cloud Computing

IoT-Enabled Black Box for Driver Behavior Analysis Using Clo...

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2024 international conference on advances in Data engineering and intelligent Computing Systems, ADICS 2024

作者： Jegan, J. Suguna, M. Raja Shobana, M. Azath, H. Murugan, S. Rajmohan, M. School Of Technology The Apollo University Department Of Computer Science And Engineering Andhra Pradesh Chittoor India Rmk College Of Engineering And Technology Department Of Computer Science And Engineering Tamil Nadu Chennai India Srm Institute Of Science And Technology Department Of Networking And Communication Chennai Tamil Nadu Kattankulathur India School Of Computing Science And Engineering Vit Bhopal University Bhopal India Saveetha School Of Engineering Saveetha Institute Of Medical And Technical Sciences Saveetha University Department Of Computer Science And Engineering Tamil Nadu Chennai India Hindustan Institute Of Technology And Science Department Of Electronics And Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350364828

The Internet of Things (IoT)-powered black box for advanced driver behavior analysis and vehicle safety is a revolutionary strategy for improving driver behavior and road safety via the use of black boxes powered by the Internet of Things. This project captures realtime data on driving behavior, encompassing characteristics such as speed, acceleration, braking, and adherence to lanes via the seamless integration of IoT technologies into the vehicle's black box. It does this by providing in-depth insights into drivers' behaviors, which encourages adopting safe driving practices thanks to the advanced data analytics it employs. In addition to its behavior monitoring capabilities, the IoT-driven black box enhances the vehicle's safety by including collision detection technologies. If an accident occurs, the system immediately sends an alert, communicating the severity of the collision and the exact GPS locations to the emergency services, which speeds up the process of responding to the incident. This attempt combines cutting-edge Internet of Things capabilities with vehicle safety to develop responsible driving behaviors and, eventually, a safer highway environment for all parties involved. This invention can modify driving norms thanks to its comprehensive approach, highlighting the potential of technology-driven solutions in promoting safer roadways. © 2024 IEEE.

关键词： Vehicle safety

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intelligent control Method of Indoor Physical Environment in Atrium Under Social Information Network 7th

Intelligent Control Method of Indoor Physical Environment in...

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7th EAI international conference on Advanced Hybrid Information Processing, ADHIP 2023

作者： Huang, Hai Shi, Linmei Zhou, Xian Shanghai Dong Hai Vocational Technical College Shanghai200241 China Institute of Economics and Management Zhi Xing College of Hubei University Wuhan430011 China

ISBN: (纸本)9783031505485

In order to meet the needs of human body for indoor environment, an intelligent control method of indoor physical environment in atrium under social information network is proposed. Considering the fluid dynamic characteristics of the building atrium, the physical environment model of the building atrium is constructed. Use social information network to collect physical environment parameters such as temperature and humidity. Set the environment intelligent control target according to the thermal comfort of human body. The intelligent controller of indoor physical environment is designed by combining fuzzy control and PID control. With the support of control commands, the intelligent control task of indoor physical environment in the atrium of the building is realized. Through the performance test experiment, it is concluded that compared with the traditional control method, the control errors of indoor ambient temperature, humidity and daylighting coefficient are reduced by 0.61℃, 0.51% and 0.145 respectively, while the control error of sound pressure is reduced. © ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Fuzzy control

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