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Mm-wave wireless sensor networks with zero energy consumption through backscattering metasurfaces

Mm-wave wireless sensor networks with zero energy consumptio...

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International conference on Electromagnetics in advanced applications (ICEAA)

作者： F. Costa S. Genovesi S. Rodini G. Manara Dipartimento di Ingegneria dell’Informazione Università di Pisa Pisa

ISBN: (数字)9798350360974

ISBN: (纸本)9798350360981

The future of 6 G communications emphasizes a deep understanding of human environments for improved quality of life and work efficiency. IoT sensors will play a crucial role, gathering extensive data about living environments for tasks like environmental monitoring and structural oversight [1]. The success of these systems hinges on cost-effectiveness, energy efficiency, and minimal maintenance requirements. Traditional IoT sensors, despite advancements, still face challenges such as power consumption and limited lifespans, particularly in indoor settings where energy harvesting is difficult. RFID sensors offer potential with their ability to transmit data without additional power, but their cost and reliability in harsh environments pose barriers to widespread adoption [2].

关键词： Wireless sensor networks Power demand Fasteners Metasurfaces sensors Maintenance Environmental monitoring Energy harvesting Faces Radiofrequency identification

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TECHNICAL AND HARDWARE IMPLEMENTATION OF A MODULAR TMS PROTOTYPE SYSTEM BY USING DATA MODELING, sensor COMPUTING AND WARNING systems 9th

TECHNICAL AND HARDWARE IMPLEMENTATION OF A MODULAR TMS PROTO...

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9th International conference on advanced Materials and systems, ICAMS 2022

作者： Sbirna, Sebastian Sbirna, Simona Ørsted Dept. of Digital Transformation Nesa Allé 1 Gentofte2820 Denmark University of Craiova Faculty of Science Chemistry Department 107i Bucharest Street Craiova Romania

The great necessity of realizing appropriate monitoring of cooling and heating systems seems to be essential in the current context, as we approach the reality of interconnected smart cities and vehicles, which can regulate their energy consumption and, at the same time, maintain high standards on the equilibrium that they provide. This work outlines the essential technical considerations when modeling a working device prototype designed for monitoring of temperature inside vehicles and other areas. The main focus of this paper is to present and explain the algorithm that has been developed throughout three months of intensive prototyping of such a system. The scope of our final prototype includes an automatic alarm function for extreme cases, along with visual feedback in the form of messages on an LCD screen and color-coded LED signals. There is a specific focus regarding the collection and processing of accurate data for vehicles, with the consequence of releasing appropriate warnings to drivers or system owners. The main research focus is on explainability and reproducibility of our decisions behind the programming approach. Finally, we have demonstrated the means through which the mentioned solution is adaptable and cost-efficient, together with short considerations that would take the prototype into mass production. © 2022 Toate drepturile asupra acestei ediţii sunt rezervate editorilor.

关键词： Energy utilization

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Internet of Things Protocols for Context-Aware Anonymity Authentication with an Emphasis on E-Health applications 10

Internet of Things Protocols for Context-Aware Anonymity Aut...

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17th INDIACom;2023 10th International conference on Computing for Sustainable Global Development, INDIACom 2023

作者： Srivastava, Shipra Gupta, Sumeet Gehlot, Anita Vijay, Pradkhshana Ramesh, Garla Aswal, Upendra Singh Greater Noida Institute of Technology U.P. Greater Noida India School of Business Upes India Uttaranchal Institute of Technology Uttaranchal University India King George's Medical University Fods Department of Oral Pathology and Microbiology Uttar Pradesh Lucknow India St. Martins Engineering College Electronics and Communication Engineering Telangana Secunderabad India Graphic Era Deemed to Be University Department of Computer Science and Engineering Uttarakhand Dehradun India

ISBN: (纸本)9789380544472

The Internet of Things (IoT) system improves existing healthcare systems and their data. Specifically, the patient's sensitive data may be eavesdropped and linked to the identities of the sensors in transmission and thus revealing the patient's medical conditions. Therefore, in the such resource-impoverished environment, anonymous authentication for sensor nodes while considering their stringent resource constraints is a paramount security concern. In order to ensure security services and safeguard private customer data in the healthcare industry, this study proposes a new idea known as a secure anonymous authentication protocol with advanced encryption standards (SAAPAES). The suggested identification method offers a highly secure and effective identification scheme for the healthcare sector. © 2023 Bharati Vidyapeeth, New Delhi.

关键词： Internet of things

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3D Object 360-Degree Motion Detection Using Ultra-Frequency PIR sensor

3D Object 360-Degree Motion Detection Using Ultra-Frequency ...

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2023 IEEE World conference on Applied Intelligence and Computing, AIC 2023

作者： Mahajan, Yash Shandilya, Deepak Batta, Priya Sharma, Muskan Chandigarh University Department of Computer Science and Engineering Mohali India

ISBN: (纸本)9798350310061

This research paper introduces a groundbreaking 3D object 360 motion detection system that employs radiation-based active motion detectors. These sophisticated detectors emit electromagnetic waves and meticulously measure the energy differentials pre and post-reflection to discern motion. The system further harnesses the power of wavelet representation for object recognition amidst crowded scenes, harnessing the prowess of dimensionality reduction and support vector machines for efficient and effective learning. Additionally, the paper explores advanced shape detection techniques, encompassing cutting-edge edge detection and precise geometric parameter estimation. It delves into the efficacy of frame subtraction and background subtraction as highly adaptable motion detection methodologies. The study also sheds light on the merits and demerits of diverse motion detection technologies, encompassing infrared sensors, video motion detection, thermal imaging cameras, and radar systems. Through its comprehensive analysis, this research paves the way for future investigations aimed at enhancing accuracy and performance in 3D object 360 motion detection, thus catering to the evolving needs of security and surveillance applications. © 2023 IEEE.

关键词： Object recognition

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A Hybrid Deep Learning Framework for Text-Independent Automatic Speaker Recognition System 3rd

A Hybrid Deep Learning Framework for Text-Independent Automa...

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3rd International conference on advanced Computing and applications, ICACA 2024

作者： Harh, Akash Bandhu, Spandan Barai, Bidhan Singh, Pawan Kumar Techno Main Salt Lake EM-4/1 Sector-V Salt Lake West Bengal Kolkata700091 India Techno Main Salt Lake EM-4/1 Sector-V Salt Lake West Bengal Kolkata700091 India Department of Information Technology Jadavpur University Jadavpur University Second Campus Plot No. 8 Salt Lake Bypass LB Block Sector III Salt Lake City West Bengal Kolkata700106 India Shinawatra University 99 Moo 10 Bang Toei Sam Khok Pathum Thani12160 Thailand

ISBN: (纸本)9789819747986

A variety of handcrafted features as well as techniques for Speaker Recognition (SR), which combines Speaker Identification (SI) and Speaker Verification (SV), have been developed over the previous 5 decades. Automatic speaker recognition (ASR), also referred to as vocal biometric recognition, is one method of human biometric identification. ASR plays such a crucial part in so many applications, including voice assistants, transcription services, and many more, and it has attracted a lot of attention lately. This paper develops a hybrid deep learning framework for text-independent ASR system. This framework is based on the integration of Gated Recurrent Units in Recurrent Neural Networks (RNN-GRU) with Connectionist Temporal Classification (CTC) loss via the layers of a 2D Convolutional Neural Network (2D-CNN). Using the benchmark LJspeech dataset, the model has been evaluated using a performance metric, Error Rate (ER). The achieved ER rate of about 16–17% for 20 epochs underscores the promising progress in ASR technology, setting the stage for continued advancements in this field. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Recurrent neural networks

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5th International conference on Data and Information Sciences, ICDIS 2023

5th International Conference on Data and Information Science...

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5th International conference on Data and Information Sciences, ICDIS 2023

ISBN: (纸本)9789819969050

The proceedings contain 45 papers. The special focus in this conference is on Data and Information Sciences. The topics include: bSafe: A Framework for Hazardous Situation Monitoring in Industries;comparative Review of Different Techniques for Predictive Analytics in Crime Data Over Online Social Media;An Approach Towards Modification of Playfair Cipher Using 16 $$\times $$ 16 Matrix;Real and Fake Job Classification Using NLP and Machine Learning Techniques;an Improved Privacy-Preserving Multi-factor Authentication Protocol for Wireless sensor Networks;blockchain-Powered Crowdfunding: Assessing the Viability, Benefits, and Risks of a Decentralized Approach;geospatial Project: Landslide Prediction;yoga Pose Identification Using Deep Learning;predicting Size and Fit in Fashion E-Commerce;A Novel Image Captioning Approach Using CNN and MLP;Multimodal Authentication Token Through Automatic Part of Speech (POS) Tagged Word Embedding;sensitive Content Classification;online Social Networks: An Efficient Framework for Fake Profiles Detection Using Optimizable Bagged Tree;Exploring Risk Factors for Cardiovascular Disease: Insights from NHANES Database Analysis;Review of Local Binary Pattern Histograms for Intelligent CCTV Detection;Enhancing Machine Learning Model Using Explainable AI;ioT-Assisted Mushroom Cultivation in Agile Environment;a Comprehensive Survey of Machine Learning Techniques for Brain Tumor Detection;current Advances in Locality-Based and Feature-Based Transformers: A Review;a Systematic Review on Detection of Gastric Cancer in Endoscopic Imaging System in Artificial Intelligence applications;route Optimizations Using Genetic Algorithms for Wireless Body Area Networks;propchain: Decentralized Property Management System;criminal Prevision with Weapon Identification and Forewarning Software in Military Base;advanced Cyber Security Helpdesk Using Machine Learning Techniques.

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Implementation of a 3D Indoor Positioning System Using MLP-based Distance Estimation for IoT applications

Implementation of a 3D Indoor Positioning System Using MLP-b...

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2022 International conference on Electrical Engineering, Computer and Information Technology, ICEECIT 2022

作者： Bengherbia, Billel Bougheriza, Mohamed El Amine Bouhedda, Mounir Tobbal, Abdelhafid Toubal, Abdelmoughni Hentabeli, Hamza University Yahia Fares of Medea Research Laboratory in Advanced Electronics Systems Lsea Medea Algeria Tipaza Kolea Algeria

ISBN: (纸本)9781665493529

Wireless sensor network (WSN) indoor location systems are based on effective distance estimation between the target node and anchors to find the node's precise location. Almost all low-cost wireless devices use the received signal strength indicator (RSSI) metric for estimating distance. This study aims to minimise the error in the estimated distance between the anchor nodes and the target node by proposing a model based on an Artificial Neural Network (ANN) for determining the distance using the RSSI. The proposed model was used to apply 3D indoor localisation. ANN is implemented in an Esp32 embedded system to make it compatible with WSN and IoT applications by using the TinyML approach for designing and implementing an efficient base station. The results show that the time required for the indoor localisation process does not exceed 40 ms, which is a very promising result for real-time localisation applications. © 2022 IEEE.

关键词： Indoor positioning systems

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Reinforcement Learning for Mobile Robot's Environment Exploration

Reinforcement Learning for Mobile Robot's Environment Explor...

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Robotics and Technologies for Industrial Automation (ROBOTHIA), IEEE International conference on

作者： Saif Alahdal Nasr Abdalmanan Kamarulzaman Kamarudin Muhammad Aizat Abu Bakar Mohd Rizal Manan Ahmad Shakaff Ali Yeon Syed Muhammad Mamduh Faculty of Electrical Engineering & Technology Universiti Malaysia Perlis Arau Malaysia Center of Excellence for Advanced Sensor Technology Faculty of Electrical Engineering & Technology Universiti Malaysia Perlis Arau Malaysia Faculty of Electrical Engineering & Technology Universiti Malaysia Perlis Perlis Malaysia Center of Excellence for Advanced Sensor Technology Universiti Malaysia Perlis Arau Malaysia

ISBN: (数字)9798350356755

ISBN: (纸本)9798350356762

The field of mobile robotics has become increasingly significant in today's technology-driven world, with applications ranging from autonomous vehicles to automated delivery systems. This project aims to enhance the capabilities of mobile robots in navigating and exploring unfamiliar environments by developing and implementing a Reinforcement Learning (RL) model. The core objective is to enable these robots to autonomously explore, navigate, and adapt to new surroundings efficiently. By integrating the RL model into a mobile robot using the Robot Operating System (ROS), the project evaluates the system's efficiency through comprehensive ground experiments. The research compares the RL-based approach with established exploration methods, emphasizing the effectiveness of the Value Iteration algorithm, a dynamic programming algorithm for Markov Decision Processes (MDPs). Controlled experiments conducted in a 6×3 meter flat space with static obstacles and a 2D lidar sensor provide valuable insights into the RL model's performance and potential real-world applications. The findings highlight the advantages of the Value Iteration algorithm over traditional exploration methods, demonstrating its potential for improving autonomous robotic navigation and exploration.

关键词： Adaptation models Accuracy Service robots Heuristic algorithms Reinforcement learning Robot sensing systems Robustness Dynamic programming Mobile robots Robots

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The Implementation of the "My Parking" Application as a Tool and Solution for Changing the Old Parking System to a Smart Parking System in Indonesia 1

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International conference on Innovative Technologies in Intelligent systems and Industrial applications, CITISIA 2022

作者： Harahap, Anisah El Hafizha Sardjono, Wahyu Information Systems Management Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

Nowadays with globalization and digitalization, many companies change their business process from conventional business to digital-based business. It aims to shorten and simplify business processes and also to avoid fraud that can occur. It’s the same with the parking system in Indonesia, by taking the advantage of advanced technology to create a better parking system, a smart parking system can be implemented in Indonesia. To be specific by using the Internet of Things or IoT, a sensor system, and developing an application that can be accessed and used by the driver as a user to make a reservation of parking space. Came along with that problem, the existence of "My Parking" can be the problem solver, and with the My Parking innovation as an application to implement a smart parking system in Indonesia, it is hoped that it can help both the community and the government in building a smart city in Indonesia which will lead Indonesia to become a developed country. The purpose of this paper is to visualize the My Parking Apps starting from the flowchart diagram to the User Interface of the apps. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： User interfaces

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Nanostructure-Based Highly Sensitive and Reliable Piezo-Transmittance Strain sensor and Integrated System

Nanostructure-Based Highly Sensitive and Reliable Piezo-Tran...

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IEEE International conference on Micro Electro Mechanical systems

作者： Myung-Kun Chung Su-Min Jeon Jae-Soon Yang Jae-Young Yoo Min-Uk Kim Beom-Jun Kim Tae-Yeon Lee Min-Seung Jo Jun-Bo Yoon School of Electrical Engineering Korea Advanced Institute of Science and Technology (KAIST) Republic of Korea Department of Semiconductor Convergence Engineering Sungkyunkwan University (SKKU) Republic of Korea Center for Bio-Integrated Electronics Northwestern University Evanston IL USA

ISBN: (数字)9798331508890

ISBN: (纸本)9798331508906

Advancements in human-machine interaction, health monitoring, and robotics have led to increasing demand for reliable strain sensors. Of the various flexible sensors, piezo-transmittance strain sensors adjust their optical transmittance in response to strain and can overcome limitations seen in other sensor types. However, current piezo-transmittance strain sensors face challenges related to controllability and applicability, as well as constraints from bulky designs and complex wired connections. This paper reports a highly sensitive, reliable, and mechanically durable piezo-transmittance strain sensor that addresses these challenges. In addition, we propose a simple, wireless integrated sensor system that eliminates the need for bulky and complex wiring, offering a practical solution for human motion detection applications.

关键词： Wireless communication Micromechanical devices Human computer interaction Wireless sensor networks Materials reliability Capacitive sensors sensor systems Optical sensors Monitoring Strain

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