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Human Activity Recognition Using Flexible sensor and Tiny Convolutional Neural Network

Human Activity Recognition Using Flexible Sensor and Tiny Co...

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International Flexible Electronics Technology conference (IFETC)

作者： Giuseppe Longo Andrea Fasolino Rosalba Liguori Luigi Di Benedetto Alfredo Rubino Gian Domenico Licciardo Department of Industrial Engineering University of Salerno Fisciano Italy

ISBN: (数字)9798331529468

ISBN: (纸本)9798331529475

A tiny Convolutional Neural Network (CNN) for Human Activity Recognition (HAR), based on a single wearable flexible sensor applied to the knee joint, is presented; it is capable to distinguish three activities taken from a public dataset (w-HAR): jump, walk, sit. HAR has gained increasing interest in recent years, particularly with the widespread adoption of Artificial Intelligence and Neural networks. A defining characteristic of this research domain is its versatility, spanning various fields, including healthcare and sports. The signal processing introduced in this work involves a grey-scale image encoding followed by a tiny CNN that consists of only one Convolutional layer. Activation functions employ a leaky ReLU while a Softmax function was used as a nonlinear component. Notably, during training the images were grey-scale encoded through a normalization while for the validation and test the images were built only with a routing of the time series data. Results in terms of test accuracy (94.43%) suggest the potentiality of HAR based on flexible and stretchable sensors using innovative image processing deep learning techniques and tiny CNN that could lead to intelligent sensors integrated with embedded AI capabilities.

关键词： Training Knee Image coding Time series analysis Medical services Routing Human activity recognition Convolutional neural networks Artificial intelligence Sports

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A Comprehensive Study on Aggregation and Routing Techniques with MATLAB Implementation and QoS Parameter Collection

A Comprehensive Study on Aggregation and Routing Techniques ...

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Innovation in Technology (APCIT), Asia Pacific conference on

作者： Navjyot Kaur Vetrithangam D Computer Science and Engineering Chandigarh University Mohali

ISBN: (数字)9798350361537

ISBN: (纸本)9798350361544

The basic units of WSNs, or distributed, self-organizing systems, are sensor nodes, which are low-cost, low-power, and small devices. These sensor nodes are equipped with the ability to sense, process, and communicate. The sensor nodes are equipped with a variety of sensors, including chemical, touch, motion, temperature, and weather sensors. Owing to their diversity, sensors are employed in a wide range of applications, including automation, tracking, monitoring, and surveillance. WSNs still suffer common issues such limited processing speed, poor memory, and short network lifetime despite the abundance of sensor applications. The implementation of a Wireless sensor Network (WSN) using MATLAB for real-time data collecting and Quality of Service (QoS) parameter analysis is thoroughly studied in this research. This system makes use of .mat files to record and store QoS measurements, making it possible to evaluate the network’s performance effectively. The goal is to build a scalable and dependable infrastructure for wireless sensor networks (WSNs) while taking energy consumption, throughput, and latency into account. In the experimental setup, MATLAB is used to monitor and record the QoS parameters as nodes in the WSN communicate with one another to gather data. After that, the gathered data is saved in .mat files for later examination. In order to secure the delivery of high-quality and dependable information, which is essential for applications ranging from industrial automation to environmental monitoring, the paper highlights the necessity of QoS in WSNs.

关键词： Temperature sensors Temperature measurement Wireless sensor networks Technological innovation Automation Tracking Surveillance

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A Secure Localization Scheme for UWSNs based on AUV Formation Cooperative Beamforming

A Secure Localization Scheme for UWSNs based on AUV Formatio...

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IEEE International conference on Communications (ICC)

作者： Rong Fan Pan Pan Zhigang Jin Yishan Su Fei Dou School of Electrical and Information Engineering Tianjin University Tianjin China School of Computing University of Georgia Athens GA USA

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

In harsh underwater environments, position accuracy and privacy of sensors are equally important. Most underwater localization schemes suffer from privacy leakage, and privacy protection schemes for terrestrial networks are not applicable to underwater acoustic networks with stratification effects and multipath. Therefore, this paper proposes a secure localization scheme based on autonomous underwater vehicle (AUV) formation cooperative beamforming for underwater wire-less sensor networks (UWSNs) considering acoustic channel char-acteristic. The underwater sensor receives position information from multiple AUV anchors and utilizes time difference of arrival (TDOA) for self-localization. Eavesdroppers exist to overhear the information emitted by the anchors, thereby destroying the entire localization system. We model the secure localization requirement as a multi-AUV multi-objective dual joint optimization problem to optimize the security and energy performance, and adopt the deep reinforcement learning (DRL)-based multi-agent deep deterministic policy gradient (MADDPG) algorithm to solve it. Simulation and sea experimental results corroborate the efficiency and accuracy of the proposed secure localization scheme.

关键词： Location awareness Privacy Accuracy Array signal processing Time difference of arrival sensors Security

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IoT-Powered Solution for Proactive Air Quality Management

IoT-Powered Solution for Proactive Air Quality Management

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Image processing and Capsule networks (ICIPCN), International conference on

作者： P Saraswathi M Prabha B Dhiyanesh R Akchay Kumar J Barith Ahamed M Mohamed Ismail Department of Information Technology Velammal College of Engineering and Technology Madurai Tamilnadu India Department of Computer Science and Engineering Dr. N. G. P. Institute of Technology Coimbatore Tamilnadu India

ISBN: (数字)9798350367171

ISBN: (纸本)9798350367188

Across the earth’s surface, gases are abundant resources, yet some pose significant hazards to human life. While halting their production is unfeasible, managing and monitoring them is vital for safeguarding environmental and public health. Hazardous gases such as Particulate Matters (Sulfates, Nitrates, Ammonia, Black Carbon, Dust), Carbon Monoxide, Ozone, Nitrogen Dioxide, and Sulfur Dioxide permeate the air we breathe, their levels influenced by temperature and humidity. Leveraging the Espressif ESP32 DevKit V1 Board, our IoT-based system connects various sensors to detect these gases, ensuring air quality. Data transmission to the cloud via integrated WiFi enables real-time monitoring. Crucial for IoT applications, maintaining sensor data quality enhances harmful gas monitoring, control, and prediction. Prompt alerts are dispatched when threshold levels exceed safety limits, aiding swift response. Thorough analysis of live sensor data or datasets, utilizing statistical methods and threshold values, enables proactive gas detection.

关键词： Temperature sensors Statistical analysis Air quality sensor systems sensors Internet of Things Sulfur

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Unlocking Eye Gestures with Earable Inertial Sensing for Accessible HCI

Unlocking Eye Gestures with Earable Inertial Sensing for Acc...

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International Communication Systems and networks and Workshops, COMSNETS

作者： Garvit Chugh Suchetana Chakraborty Sandip Chakraborty Department of Computer Science and Engineering Indian Institute of Technology Jodhpur India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India

ISBN: (数字)9798331531195

ISBN: (纸本)9798331531201

Eye gestures are widely used in many applications, including device control, biometrics, visual analytics, and health-care, like Alzheimer’s, accessibility, etc. The conventional method for eye gesture detection needs visual information processing devices or smart glasses to capture the movement patterns of the eyeballs. In this paper, we present a novel framework that utilizes inertial measurement unit (IMU) sensors embedded in earable devices for real-time eye gesture detection, which can work as a complementary to visual information processing devices. The framework translates specific eye movements into actionable commands, enabling hands-free interaction for users with limited mobility. Through extensive experimentation with 14 participants across diverse activities such as sitting, walking, running, and driving, the framework demonstrated high accuracy in eye gesture recognition, achieving a macro F1 score of 0.85 on our self-collected dataset.

关键词： Legged locomotion Vocabulary Measurement units Visual analytics information processing Gesture recognition Real-time systems Research and development intelligent sensors Smart glasses

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intelligent Face Mask and Body Temperature Detection System using Machine Learning Algorithm

Intelligent Face Mask and Body Temperature Detection System ...

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2022 International conference on Innovative Computing, intelligent Communication and Smart Electrical Systems, ICSES 2022

作者： Heltin Genitha, C. Kiruba Sangaree, R. Kokilavani, V. St.Joseph's College of Engineering Department of Information Technology Chennai India

ISBN: (数字)9781665474139

ISBN: (纸本)9781665474139

Face mask and body temperature detection is necessary for current pandemic period. Detecting face mask and body temperature helps in decreasing or to avoid spreading of COVID cases especially in crowded areas. The main purpose of face mask recognition and temperature prediction system is to find whether a person is wearing a mask or not and to check the body temperature. With the help of deep neural network based Convolution Neural Network algorithm, face mask has been recognized. For body temperature, LM35 temperature sensor is used. This system undergoes data pre-processing, training, detecting face mask and temperature. By using MobileNet V2, Frontcascadexml file, tensor flow and keras software library the face mask is detected. Then, the result is send to the Arduino microcontroller and displays that the face mask is detected or not by using LED. If the mask is not weared by the person, buzzer will be alarmed. Similar procedure was carried out for monitoring the temperature of a person using LM35 temperature sensor. The main advantages of MobileNet V2 are higher performance, lesser network size and minimum number of parameter are required. © 2022 IEEE.

关键词： Temperature sensors

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Unity makes strength: Coalition Formation-based Group-buying for Timely UAV Data Collection

Unity makes strength: Coalition Formation-based Group-buying...

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IEEE Global Communications conference (GLOBECOM)

作者： Qi, Nan Huang, Yeting Sun, Wen Jin, Shi Tsiftsis, Theodoros A. Wu, Qihui Su, Xiang Southeast Univ Natl Mobile Commun Res Lab Nanjing Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn Nanjing Peoples R China Southeast Univ Sch Cyber Sci & Engn Nanjing Peoples R China Jinan Univ Sch Intelligent Syst Sci & Engn Zhuhai Peoples R China Norwegian Univ Sci & Technol Dept Comp Sci Gjovik Norway Univ Oulu Ctr Ubiquitous Comp Oulu Finland

ISBN: (纸本)9781665435406

With their high mobility, unmanned aerial vehicles (UAVs) become appealing data collectors in hard-to-reach wide-area distributed sensor networks. Different from existing works focusing on the perspective of UAVs for service order optimization and UAV utility maximization, we consider the utilities of both sensors and UAVs, and innovatively model the competition among sensors (buyers) for the service of UAVs (sellers) as an auction game. A "unity makes strength" strategy is exploited. That is, to strengthen the bidding competitiveness, a group-buying coalition auction method that encourages sensors to form coalitions to bid for UAV service is proposed. Besides, we propose a parallel variable neighborhood ascent search algorithm, we can quickly determine the approximately optimal group-buying coalition structure. Numerical results show that the proposed method outperforms the joint trajectory design-task scheduling (TDTS) UAV-to-community method and the single coalition formation game (CFG) method.

关键词： Unmanned aerial vehicles (UAVs) age of information (AoI) auction mechanism coalition formation game

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Harnessing the Power of IOT for Next-Gen intelligent Traffic System 1

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15th International conference on Soft Computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Shekhar, Shashank Kumar, Manish Tyagi, Priyanka CSE Department Sharda University Greater Noida India CSE Department Tyagi Galgotia College of Engineering and Technology Greater Noida India

ISBN: (数字)9783031810862

ISBN: (纸本)9783031810855

Traffic congestion has significantly worsened in our country during the past few years, disrupting the everyday routine of modern cities and their environments. Cities grow in size as a result of rising population, which also causes a huge increase in the number of vehicles using the roadways. Numerous difficulties, including squandered fuel, air pollution, and delays in transportation, exist. Therefore, the largest challenge facing traffic management authorities is monitoring and controlling traffic. We create and implement real-time traffic monitoring systems utilizing sensor technologies and the Internet of Things (IoT) platform. The volume of vehicle traffic at the lanes is monitored by this system using ultrasonic sensors;the controller receives the information and sends it to the web server through a Wi-Fi module. The server processes and saves the tracked data. A strategy for managing traffic signals that is based on analyzing traffic density at the lanes is used in this instance to control traffic. When there is a lot of traffic in a lane, passing cars have precedence. To send and receive data, RF transceivers employ messages about traffic from the priority system to the main system. This technology, which is dependable, easy to use, and inexpensive, is provided at the intersection of lanes. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Traffic congestion

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Digital Twin-Based Collaborative Management for Energy-Aware 6G IoT Systems

Digital Twin-Based Collaborative Management for Energy-Aware...

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IEEE conference on Wireless Communications and Networking

作者： Kubra Duran Berk Canberk School of Computing Engineering and The Built Environment Edinburgh Napier University UK BTS Group Istanbul Turkey

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

Even though the emergence of 6G IoT systems has accelerated the deployment of hyper-connected networks, the inherent resource limitations of IoT sensors remain a significant problem. In addition, maintaining energy efficiency and low response times in such environments has become more challenging. However, the existing management methods often lack the real-time adaptability and intelligence to optimize energy consumption in 6G IoT networks. To tackle this, we propose a DT-based collaborative management consisting of a multi-agent twin layer, a collaboration protocol and a Reinforcement Learning (RL)-based learner model. In the multi-agent twin layer, each physical network sensor is modelled as an individual agent for enhanced granularity in the management. The collaboration protocol ensures information sharing among the sensors and, thus, lowers response times. Furthermore, in the learner model, we utilize a multi-agent Deep Deterministic Policy Gradient (MADDPG) algorithm to optimise actions according to the novel energy-aware reward function. According to our simulation results, the proposed DT-based collaborative management surpasses the traditional method by 27 % for longer battery levels and 65 % more rapid responses.

关键词： 6G mobile communication Adaptation models Protocols Simulation Collaboration Reinforcement learning sensor systems Batteries Time factors intelligent sensors

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IoT-Enabled Smart Stick with Multi-sensor Fusion and LSTM-Based Navigation for Enhanced Mobility

IoT-Enabled Smart Stick with Multi-Sensor Fusion and LSTM-Ba...

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International conference on Computer and Communications Technologies (ICCCT)

作者： R. Subramani G.Adiline Macriga Department of Information Technology Computer Science and Engineering (with specialization in networks) Sri Sairam Engineering College Department of Information Technology Sri Sairam Engineering College

ISBN: (数字)9798331537579

ISBN: (纸本)9798331537586

Visual impairment maintains substantial obstacles to independent movement because proper assistance technology should be applied for its resolution. The proposed system outperforms conventional walking sticks because it merges sensors from four categories including ultrasonic, LiDAR and infrared also water detection to improve network perception. The Multi-sensor Fusion technology allows data sensors to merge intelligently with an effective outcome of real-time decisions and decreased incorrect response rates. Historical movement data goes into an LSTM-based navigation module to forecast safety routes for stopping accidental collisions during use. Using connected IoT technology allows for the implementation of Location Trace functions while ensuring instant emergency SMS messaging with audio feedback delivered through wireless earpieces that produce complete user assistance systems. The adapter filters connected to sensors ensure that the system function reliably in both inside and outside environments. The study establishes three main objectives to achieve: •Develop an advanced assistive mobility solution with enhanced obstacle detection accuracy. •Predictive path planning based on LSTM networks will allow dynamic navigation as part of the research approach. •Ensure real-time location tracking and emergency alert systems for user safety. •Utilize IoT-cloud connectivity for data storage and continuous learning. Evaluation results indicate the developed MSF-LSTM system produces obstacle detection performance of 97.8% surpassing traditional models. The system achieves three main operational advantages through its high false detection prevention along with 2.1-second fast response times and 91.3% better navigation systems. The combination of AI-based assistance with IoT connectivity generates new security measures for autonomous vehicles that benefit users who are vision-impaired. The mobility assistance functions will receive enhancements through terrain modification

关键词： Legged locomotion Navigation Visual impairment sensor fusion Real-time systems sensor systems Path planning Long short term memory intelligent sensors Standards

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