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IoT-Driven Smart Car Parking system: Optimizing Urban Mobility and Reducing Environmental Impact 3

IoT-Driven Smart Car Parking System: Optimizing Urban Mobili...

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3rd International Conference on Intelligent Data communication Technologies and Internet of Things, IDCIoT 2025

作者： Tanvi, Y. Lakshmi Sowmya, B. Prashanth, B.N. Rajagopal, Shinu M. Dept. of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India Dept. of Electronics and Communication Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India Dept. of Mechanical Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

The rapid increase in urban vehicle numbers has significantly worsened traffic congestion, particularly in public parking spaces, where conventional parking systems often prove inefficient, leading to wasted time, excessive fuel consumption, and increased environmental pollution. A Smart Car Parking system is proposed to address these challenges by integrating advanced technologies, including the Internet of Things (IoT), to optimize parking operations. The system employs sensors embedded in parking spaces to detect vehicle presence and provide real-time data on availability. This enables drivers to locate free parking spaces efficiently, improving traffic flow. Additionally, the system offers valuable insights to city planners and facility managers, supporting optimal space allocation and dynamic pricing models. By reducing vehicle idling and unnecessary driving while searching for parking, the system helps minimize emissions, contributing to environmental sustainability. The study builds an automated smart car parking system for parking slot monitoring and gate control. The system ensures correct slot occupancy reading, status displayed in real time, and smooth operation of an opening and closing system. It manages additional features such as real-time sensor calibration and effective gate control with a high degree of accuracy and accountability. The proposed Smart Car Parking system represents a key innovation in urban mobility, offering a user-friendly, efficient, and ecofriendly solution to one of the most persistent challenges faced by modern cities. © 2025 IEEE.

关键词： Traffic congestion

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Real World Deployment of Dual Branch MRC Enhanced by Adaptive Algorithms LMS and RLS in 5G Networks to Improve SNR and QoS 4

Real World Deployment of Dual Branch MRC Enhanced by Adaptiv...

引用

4th International Conference on Intelligent Technologies, CONIT 2024

作者： Upadhyay, Deepak Upadhyay, Abhay Gupta, Mridul Sharma, Kunj Bihari Maindola, Meenakshi Garg, Shobhit Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era Deemed to Be University Dept. of Electronics and Communication Engineering Dehradun India Graphic Era Deemed to Be University Dept. of Computer Science and Engineering Dehradun India Graphic Era Deemed to Be University Dept. of Management Studies Dehradun India

ISBN: (纸本)9798350349900

This research is aimed at understanding the performance benefits of the use of adaptive algorithms in dual-branch MRC systems as a solution for developing 5G networks. We developed controlled simulations to determine the performance influences of the algorithms in SNR, QoS, BER, and throughput under different network conditions. Our results indicate that the algorithms significantly reduce BER safe power divergence that improves the reliability and performance of the communication platform. The adaptive systems in addition reveal a significantly impressive ability to maintain a higher rate of throughput that is necessary in the current networks due to the increasing volume of data consumed by different users. In conclusion, therefore, this research has showed that adaptive MRC techniques might be a highly-viable option toward enabling the development of 5G technology, provided a suitable method for boosting performance during uncertain communications. © 2024 IEEE.

关键词： 5G mobile communication systems

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Implementation of Dynamic Spectrum Access Techniques in Cognitive Radio Networks under Generalized Fading Conditions 2

Implementation of Dynamic Spectrum Access Techniques in Cogn...

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2nd International Conference on Advanced Computing and communication Technologies, ICACCTech 2024

作者： Upadhyay, Deepak Sharma, Kunj Bihari Gupta, Mridul Garg, Shobhit Sharma, Amulya Devgan, Divyansh Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Graphic Era Deemed to be University Dept. of Management Studies Dehradun India

ISBN: (纸本)9798331519056

This paper is organized as follows: Section II provides a background on our research work based on DSA in CRNs using CR under different fading conditions. c) Performance: We also study how effective adaptive algorithms along with the machine learning can prove in achieving higher spectrum sensing accuracy and decision making on run time. By conducting simulations and extensive performance evaluation, we show that the traditional solutions fall short when compared to our AI-based methodology in terms of accuracy especially under harsh fading conditions. Finally, sensitivity analysis highlights the control parameters that need to be submitted to further optimization for better system performance. With all above analysis, our results indicate that DSA can alleviate spectrum underutilization problem and enhance communication reliability in CRNs. Thus, with proper adaptation strategies and machine learning algorithms, the DSA systems provide an appealing opportunity to meet the continuously increasing requirements of bandwidth-consuming applications in current days wireless networks. The results of this research are helpful in providing effective value input to Advances in the understanding and design of robust, efficient spectrum management approaches for dynamic and diverse wireless settings. © 2024 IEEE.

关键词： Sensitivity analysis

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Pelican optimized extreme learning machine based prognosis of heart failure using textural patterns in CMR images

Pelican optimized extreme learning machine based prognosis o...

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2023 IEEE Technology and engineering Management Conference - Asia Pacific, TEMSCON-ASPAC 2023

作者： Muthulakshmi, M. Ashwini, K. Jansi, R. Kiran, Batchu Bhanu Sai Mani Greeshma, Nimmagadda Keerthi, Pulimi Amrita School of Engineering Dept. of Electronics and Communication Engineering Amrita Vishwa Vidyapeetham Chennai India Amrita School of Computing Dept. of Computer Science and Engineering Amrita Vishwa Vidyapeetham Chennai India Srm Institute of Science and Technology Faculty of Engineering and Technology Dept. of Electronics and Communication Engineering Kattankulathur Chennai603203 India Amrita School of Engineering Dept. of Computer and Communication Engineering Amrita Vishwa Vidyapeetham Chennai India

ISBN: (纸本)9798350384659

One of the abnormal cardiovascular conditions with the greatest rate of increase is heart failure (HF). There is a lot of correlation in the exterior symptoms observed that are typically ignored, particularly when there is progression from one stage to another. Planning an efficient treatment requires grouping patients into different phenotypic categories. In CMR imaging, these conditions show damaged heart muscles. Understanding the classification performance of ELM aided by optimal texture features is the main aim of the proposed work. In this study, Krawtchouk moment and the co-occurrence of neighboring sparse local ternary pattern descriptors are used to extract texture and anatomical information of LV. However, an effective feature selection strategy is required to handle the high dimensionality of the feature vector. The primary benefit of the Pelican optimization algorithm (POA), which takes inspiration from nature, is its capacity to carry out both global and local searches effectively. This paper suggests usage of multi-objective POA to optimize the proportion of extracted features and improve the performance of the ELM classifier. The people with various HF stages have been diagnosed with the maximum accuracy of 95.7 % as a result of this inclusion. The enhanced traits have distinguished moderate and severe HF patients from control participants with significant performance. The proposed work further shows the impact of tissue characterization from CMR image and optimized features-based classification on the HF stage detection. © 2023 IEEE.

关键词： Magnetic resonance

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Design of Alcohol Detection and Alert system for Vehicles 1

Design of Alcohol Detection and Alert System for Vehicles

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1st IEEE International Conference on Advances in Computing, communication and Networking, ICAC2N 2024

作者： Bhardwaj, Indu Saravanan, D. Bhardwaj, Ajay Yadav, Daman Kumari, Vijeta Kumar, R Ramesh Galgotias University Dept. of Electrical Electronics and Communication Engineering Greater Noida India Madanapalle Institute of Technology and Science Dept. of Electrical and Electronics Engineering India Delhi Technological University Dept. of Computer Science and Engineering New Delhi India

ISBN: (纸本)9798350356816

Recent days accidents are increasing on an exponential basis due to drinking and drive. Driving after drinking alcohol is a major cause of the majority of the accidents due to which sometimes innocent people lose their lives. As the number of vehicles is increasing day by day, accidents are also occurring due to many reasons but alcohol consumption is a major factor in many of the accidents. To avoid these accidents, an alcohol detection and alert system for vehicles is proposed in this paper that is based on MQ3 sensor. The proposed system gives a coherent solution to control injuries because of consumption of alcohol while driving. The alcohol detected by the MQ-3 sensor is processed via an ATmega328P Microcontroller that collate it with a fixed threshold for compliance. The device will nonstop monitor concentration of alcohol by the alcohol recognition sensor and consequently flip off the working of automobile's engine if the alcohol concentration is exceeding threshold value. The replica can even send the alert of locality of the car via SIM900A (GSM module). The model presents an adequate answer to regulate injuries by the influence of alcohol driving. The LCD module is used to show that alcohol has been identified. The proposed system is cost effective, less bulky and more reliable. © 2024 IEEE.

关键词： Microcontrollers

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An earlier serial lactate determination analysis of cardiac arrest patients using a medical machine learning model

An earlier serial lactate determination analysis of cardiac ...

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2023 International Conference on Intelligent systems for communication, IoT and Security, ICISCoIS 2023

作者： Mohammed, Mehmood Ali Mohammed, Murtuza Ali Mohammed, Vazeer Ali Logeshwaran, J. Jiwani, Nasmin University of the Cumberlands Dept. of Information Technology WilliamsburgKY United States Lewis University Dept.of Computer Information System IL United States Sri Eshwar College of Engineering Dept. of Electronics and Communication Engineering Coimbatore India

ISBN: (纸本)9798350335835

In general, cardiac arrest results in an inability to pump enough blood for the body's needs. Through this, the organs and tissues get enough oxygen and nutrients for their metabolic needs, and excess fluid accumulates. This further increases the severity of the patient's problems. Cardiac arrest is the leading cause of hospitalization in people over 65 and is therefore considered a significant public health problem. It is a pathology linked to an increase in average life expectancy, and its incidence is increasing every year due to the general ageing of the population. In this paper, an earlier serial lactate determination analysis of cardiac arrest patients using a medical machine learning algorithm. It can occur following an episode of cardiac arrest or inadequate treatment of chronic diseases, including diabetes and hypertension. Adopting lifestyle habits that prevent the onset of these conditions is an essential strategy for preventing heart failure. The proposed approach has achieved 91.58% accuracy, 87.96% precision, 84.62% recall, and 85.23% F1-score results compared to other methods. © 2023 IEEE.

关键词： Tissue

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JARVIS - Smart AI Support system 3

JARVIS - Smart AI Support System

引用

3rd Odisha International Conference on Electrical Power engineering, communication and Computing Technology, ODICON 2024

作者： Ramya Manaswi, V. Saketh, Meduri Ravi Tejha, Mandumula Sai Karthikeya, Atluri Sai Prakash, Dharani Chandra Alkhayyat, Ahmad Gokaraju Rangaraju Institute of Engineering and Technology Dept. of Computer Science Engineering Hyderabad India Gitam University Dept. of Computer Science Engineering with Specialisation of Cybersecurity Hyderabad India K.G Reddy College of Engineering and Technology Dept. of Electronics & Communication Engineering Telangana Hyderabad India College of Technical Engineering The Islamic University Dept. of Computers Techniques Engineering Najaf Iraq

ISBN: (纸本)9798350354379

The JARVIS AI Support system represents a remarkable fusion of modern technology, blending a sophisticated GUI design, seamless voice control, and inventive features like the captivating 'Air Canvas' facilitated by OpenCV. This AI-driven virtual assistant offers users a natural and intuitive experience, allowing them to effortlessly perform tasks such as browsing the web, interacting with a chatbot, and executing dynamic voice- controlled actions. Moreover, the system showcases advanced capabilities including motion detection and facial recognition with an accuracy of 95% in multiple runs. Leveraging the power of computer vision, the Air Canvas feature empowers users to express creativity through fluid hand gestures, while voice commands effortlessly manage diverse tasks. This innovative project presents an approachable way to interact with technology in the world of AI. © 2024 IEEE.

关键词： Face recognition

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Real-Time Object Detection with IOT Using a Smart Cart 18

Real-Time Object Detection with IOT Using a Smart Cart

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18th International Conference on Ubiquitous Information Management and communication, IMCOM 2024

作者： Omer, Muhammad Ali, Sardar Jaffar Raza, Syed Muhammad Le, Duc-Tai Choo, Hyunseung College of Computing and Informatics Sungkyunkwan University Suwon Korea Republic of Sungkyunkwan University Dept. of Computer Science and Engineering Suwon Korea Republic of Sungkyunkwan University Dept. of AI System Engineering Suwon Korea Republic of Sungkyunkwan University Dept. of Electrical and Computer Engineering Suwon Korea Republic of

ISBN: (纸本)9798350331011

With Industry 4.0's technological advancements, the convenience and affordability of Artificial Intelligence (AI) and IoT have increased. However, customers still face long waiting times in payment queues during the smart shopping experience. Current solutions rely on expensive sensor-based RFIDs or simple barcodes, making them impractical and limited in scalability. This paper proposes an economically smart solution with two cameras on NVIDIA JETSON NANO for realtime object monitoring and automated shopping. communication between modules is facilitated by TCP/IP and HTTP protocols. By utilizing the YOLO v7, real-time monitoring is achieved. This innovative approach revolutionizes the customer experience by providing a seamless interface and time-saving features. Additionally, it offers potential integration with e-commerce businesses and payment gateways, further enhancing the overall customer and vendor experience. © 2024 IEEE.

关键词： Graphical user interfaces

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Revolutionizing Diabetic Retinopathy Recognition with Advanced Deep Learning Techniques 1

Revolutionizing Diabetic Retinopathy Recognition with Advanc...

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1st International Conference on Computing, Sciences and communications, ICCSC 2024

作者： Rajalingam, S. Kanagamalliga, S. Bhavani, U. Chouksey, Mausam Saveetha Engineering College Dept. of Electrical and Electronics Engineering Chennai India Saveetha Engineering College Dept. of Electronics and Communication Engineering Chennai India School of Computer Science University of Petroleum and Energy Studies Dehradun India

ISBN: (纸本)9798350353648

Diabetic retinopathy (DR) is a severe complications arising from diabetes and the primary cause of vision impairment worldwide. Early recognition is essential for efficient intervention and prevention of permanent vision loss. This research focuses on using Deep Learning Techniques (DLT) for accurate and efficient recognition of DR. It utilizes a dataset of retinal images from diabetes, covering several stages of DR progression. Convolutional Neural Networks (CNNs), is DLT subset, are employed for extracting features and performing classification. The proposed model effectively detects subtle retinal abnormalities indicative of DR. This research contributes to existing methods by introducing a novel deep learning approach that shows high specificity and sensitivity in DR detection. The DR-Color-Fundus-Images recognition using DLT were analyzed using available Color-Fundus-Retina datasets. Performance metrics, comprising the area beneath the curve receiver operating characteristic, specificity, and sensitivity, validate the model's accuracy. The outcomes have implications for developing automated screening tools, enabling timely intervention and improving healthcare outcomes for individuals with diabetic retinopathy. This research represents a significant advancement in harnessing deep learning for enhancing DR detection and highlights the importance of technological progress in ophthalmic healthcare. © 2024 IEEE.

关键词： Convolutional neural networks

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Mobile Gateways for LoRa End-Devices: Support Connectivity on the Move 29

Mobile Gateways for LoRa End-Devices: Support Connectivity o...

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29th IEEE International Workshop on computer Aided Modeling and Design of communication Links and Networks, CAMAD 2024

作者： Moysiadis, Vasileios Skoutas, Dimitrios N. Skianis, Charalabos Lagkas, Thomas Argyriou, Vasileios Sarigiannidis, Panagiotis University of the Aegean Dept. of Information and Communication Systems Engineering Samos83200 Greece International Hellenic University Dept. of Computer Science Greece University of Western Macedonia Dept. of Electrical and Computer Engineering Kozani Greece Kingston University Dept. of Networks and Digital Media Kingston upon Thames United Kingdom

ISBN: (纸本)9798350377644

This paper proposes a method enabling mobile LoRa gateways to support mobile end devices. The approach utilizes trilateration and similar approaches based on RSSI to estimate the position of end devices and specify the movement of the gateways to maintain contact. The evaluation of the proposed method tests various parameters such as speed and number of end devices, and it shows that it is able to retain contact even with speeds up to 12 mps. Moreover, the evaluation shows that the ADR-MIN algorithm performs better in this scenario than the default ADR. © 2024 IEEE.

关键词： Gateways (computer networks)

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