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Design and Development of a Non-Invasive Glucose Monitoring Device Using advanced Microcontroller

Design and Development of a Non-Invasive Glucose Monitoring ...

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Expert Clouds and applications (ICOECA), International conference on

作者： S. Divya P Karthikeyan M. Vaigundamoorthi D Ramya Manzoore Elahi M. Soudagar Rajendiran M Department of Biomedical Engineering Dr. N.G.P. Institute of Technology Coimbatore Tamil Nadu India Department of Electronics and Communication Engineering Velammal College of Engineering and Technology Madurai Tamil Nadu India Department of Electrical and Electronics Engineering Karpagam Academy of Higher Education Coimbatore Tamil Nadu India Department of Computer Science and Business Systems Sri Eshwar College of Engineering Coimbatore Tamil Nadu India Department of VLSI Microelectronics Saveetha School of Engineering Saveetha Institute of Medical and Techinical Sciences Chennai Tamil Nadu India Department of Computer Science and Engineering Panimalar Engineering College Chennai Tamil Nadu India

ISBN: (数字)9798350385793

ISBN: (纸本)9798350385809

Millions of individuals all over the world are living with diabetes, a chronic condition that necessitates regular monitoring of Blood Glucose Levels (BGL). The present technique for minimal invasive BGL monitoring involves taking a small blood sample and transferring it to a glucometer. However, this procedure can be uncomfortable for the patient. This research presents a method for non-invasively monitoring BGL with the help of a powerful controller called the ARM Cortex-M4. For non-invasive applications, we use photoplethysmography (PPG) signals. Using a photodiode and an infrared LED light, PPG samples are received from a finger sensor. Signal processing and feature extraction are carried out using the Gray-Level Co-occurrence Matrix (GLCM) method. To predict the BGL, two ML models are developed: one employing a Linear Regression (LR) model and the other an Artificial Neural Network (ANN) model. The experimental findings show that the ANN model is quite effective, with an R2 score of 0.986. After careful consideration, the ARM Cortex-M4 microcontroller's processing capabilities were found to be optimal for running the ANN model. The model must be fine-tuned before deployment so it can communicate with the microcontroller and provide correct inference in real time. The finger sensor simplifies PPG sample collection, and the OLED display makes it simple to view BGL.

关键词： Strips Microcontrollers Artificial neural networks Predictive models Organic light emitting diodes Signal processing Glucose

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From Vision to Precision: The Dynamic Transformation of Object Detection in Autonomous systems

From Vision to Precision: The Dynamic Transformation of Obje...

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Computing and Informatics (ICCI), International conference on

作者： Nesma Alabyad Ziad Hany Abdelrahman Mostafa Reem Eldaby Ibrahim Ayman Tagen Amal Mehanna Future University In Egypt Cairo Egypt

This paper explores the evolution of self-driving cars, from early radio-controlled prototypes to today's advanced autonomous vehicles, highlighting key milestones such as Houdina Radio Control's 1920s efforts and Carnegie Mellon University's Navlab project in the 1980s. Recent advancements driven by industry leaders like Google, Tesla, and Uber incorporate advanced technologies, including sensors, cameras, radar, and lidar, empowering self-driving cars for autonomous navigation. The literature review in Frontiers in Future Transportation focuses on performance metrics for automated driving systems, discussing methodologies for quantifying obstacle threats and enhancing human-like perception and response mechanisms, with a significant emphasis on deep learning methods such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). Object detection algorithms' dynamic evolution, influenced by CNNs, is explored, and the integration of hardware accelerators like GPUs, FPGAs, and specialized AI accelerators is highlighted for real-time responsiveness. Deep learning applications in self-driving cars, including obstacle detection, lane recognition, and traffic sign and light recognition, are outlined. Vision sensor-based obstacle detection using monocular and binocular approaches is discussed, emphasizing the importance of binocular vision technology. Lane recognition's significance for deviation warning, collision prevention, and path planning is highlighted, along with deep learning approaches such as John et al.'s lane detection algorithm. Traffic sign and light recognition are explored for safety and regulatory compliance, utilizing CNNs and Deep Neural Networks (DNNs). The discussion on sensors covers simultaneous localization and mapping (SLAM) using both passive (digital cameras) and active sensors (LIDAR, RADAR), emphasizing the integration of sensors and pre-existing maps to enhance the SLAM process and contribute to the overall perception of a

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Wearable sensor-Based Gait Analysis: advanced Feature Extraction Techniques

Wearable Sensor-Based Gait Analysis: Advanced Feature Extrac...

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International conference on Advances in Information Technology (ICAIT)

作者： Karthik K Preethi Salian Ranjith H D Supriya Salian Jayashree K Annapoorneshwari Shetty Dept. of Electronics and Communication Engineering Nitte (Deemed to be University) NMAM Institute of Technology Nitte Udupi India Dept. of Information Science and Engineering Nitte (Deemed to be University) NMAM Institute of Technology Nitte Udupi India Dept. of Electronics and Communication Engineering Mangalore Institute of Technology and Engineering Moodabidri India Dept. of Computer Science and Engineering St. Joseph Engineering College Mangaluru India Dept. of Computer Science and Engineering NM Institute of Technology Bangalore India Dept. of Master of Computer Applications AIMIT St. Aloysius (Deemed to be University) Mangalore India

ISBN: (数字)9798350383867

ISBN: (纸本)9798350383874

Gait irregularities among adults are common in clinical settings and can result in severe consequences such as falls and injuries, leading to increased healthcare costs. Presently, gait evaluation primarily relies on subjective assessments using standardized clinical tools. Although motion capture systems like Qualisys and Vicon offer more objective analysis, they depend on costly, intricate equipment in specialized gait laboratories. Due to limited accessibility, involving factors like equipment scarcity, demand for technical expertise, in-person patient visits, complex procedures, and high costs, these methods remain largely inaccessible. Consequently, there is a pressing need for a more objective and cost-effective gait assessment solution. The proposed work introduces an economical automated feature extraction approach to address this issue. Leveraging Inertial Measurement Unit (IMU) sensors, comprising a three-axis gyroscope and accelerometer system captures precise foot position and orientation data crucial for comprehensive gait analysis. IMU sensors have gained popularity due to their adaptability in clinical environments and non-clinical settings like patient residences or community spaces. With the help of a microcontroller mounted on the barefoot, the IMU sensor collects raw gyroscope and accelerometer data for gait analysis. These data are wirelessly transmitted via Bluetooth to a computer for subsequent in-depth analysis, enabling effective feature extraction for comprehensive gait assessment.

关键词： Legged locomotion Accelerometers Costs Microcontrollers Pressing Feature extraction sensor systems Motion capture sensors Gyroscopes

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IoT-Enabled Automotive Software Development through Integration of Engine Control Unit Signals for Adaptive Autonomous Emergency Braking

IoT-Enabled Automotive Software Development through Integrat...

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Innovation in Technology (ASIANCON), Asian conference on

作者： Chinmayee Khondekar Priti Gade Department Of Electronics Engineering G. H. Raisoni College Of Engineering Nagpur (An Autonomous Educational Institute Affiliated to the Rashtrasant Tukdoji Maharaj Nagpur University)

ISBN: (数字)9798350354218

ISBN: (纸本)9798350354225

This paper explores the integration of engine control unit (ECU) signals within an IoT-enabled automotive software development framework. The study focuses on leveraging ECU data for real-time decision-making in adaptive systems, enhancing automotive safety and performance through advanced software development and testing methodologies. It presents the design and implementation of an adaptive autonomous emergency braking (AEB) system for automotive safety applications, focusing on the integration of engine control unit (ECU) signals within an IoT-driven software framework. The system employs a network of sensors and cameras to continuously monitor the vehicle’s surroundings and detect potential obstacles. When the vehicle’s battery and ignition are switched on, the sensors/cameras send detected obstacle signals to the ECU, which in turn initiates signal processing via Controller Area Network (CAN) communication. The signal processing algorithm analyzes the obstacle’s distance and the vehicle’s speed to assess collision risks in real-time. Upon detecting a potential collision, the system triggers a warning on the Human-Machine Interface (HMI) to alert the driver. If the driver fails to respond promptly, the AEB system automatically activates the brakes to prevent a collision.

关键词： Technological innovation Vehicle safety Signal processing algorithms sensor systems Real-time systems sensors Engines Software development management Vehicles Testing

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Visual Perception Challenges in Adverse Weather for Autonomous Vehicles: A Review of Rain and Fog Impacts

Visual Perception Challenges in Adverse Weather for Autonomo...

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IEEE Information Technology, Networking, Electronic and Automation Control conference

作者： Yongsheng Qiu Yuanyao Lu Yuantao Wang Chaochao Yang School of Electrical and Control Engineering North China University of Technology Beijing China School of Information Science and Technology North China University of Technology Beijing China

ISBN: (数字)9798350370805

ISBN: (纸本)9798350370812

Autonomous driving systems (ADS) offer efficient solutions for transportation, but their visual perception capabilities are significantly affected under adverse weather conditions such as rain and fog, posing a threat to vehicle safety. Rain droplets and fog can interfere with sensors, leading to inaccurate information acquisition and increased driving risks. Therefore, enhancing the environmental perception of ADS in adverse weather conditions is a critical research focus. This paper systematically evaluates the impacts and challenges of adverse weather conditions, specifically rain and fog, on ADS environmental perception sensors. It explores the imaging characteristics of rain and fog and their effects on visual perception, summarizing dehazing and deraining algorithms. Ad-ditionally’ this paper reviews the development status of advanced visual tasks such as object detection in autonomous driving under adverse weather conditions. The aim of this paper is to provide a comprehensive understanding of the reliability of ADS in adverse weather conditions, laying a foundation for future de-velopments and practical applications in autonomous driving technology.

关键词： Image sensors Visualization Rain Reviews Object detection sensor systems Autonomous vehicles Image enhancement Meteorology Visual perception

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advanced Uses of Micro Electro Mechanical systems-Based Devices in Healthcare and Robotics Design 2

Advanced Uses of Micro Electro Mechanical Systems-Based Devi...

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2nd IEEE International conference on Innovations in High-Speed Communication and Signal Processing, IHCSP 2024

作者： Rai, Hari Mohan Shukla, Kaustubh Kumar Janashin, Hasan Ammar, Mohd Gandhi, Devina Uniyal, Vinayak Gachon University School of Computing Korea Republic of Dronacharya Group Of Instutions Department of Ece Greater Noida India Dronacharya Group Of Instutions Department of Ecz Greater Noida India Dronacharya Group Of Institutions Department of Ecz Greater Noida India Dronacharya Group Of Institutions Department of Cse Greater Noida India Dronacharya Group Of Instutions Department of Csit Greater Noida India

ISBN: (纸本)9798350368949

This research aims to provide affordable and accessible devices for elderly and physically handicapped individuals, addressing self-reliance and societal impact. Micro-Electro-Mechanical systems (MEMS) is a popular technology, but limited in India due to limited resources. Here primary aim is to create novel devices that can improve design and analysis efficiency. The proposed sensor will normalize mobility for wheelchair bound patients and find industrial applications in robotics. The project also focuses on developing wearable devices for gait detection and analyzing reliability, sensitivity, and device response. The research uses multi-physics concepts and FEM to design and analyze sensing materials for MEMS/BioMEMS-based devices. It also focuses on the development of high-sensitivity MEMS-based microstructure devices for gait detection in wheelchair-bound patients. The sensor can be used in industrial robotics and medical sectors. The study also aims to analyze the reliability, sensitivity, and device response of the MEMS-based device, which could be used for the diagnosis and treatment of gait-related diseases. The goal is to make this technology accessible to the elderly and physically handicapped, addressing various healthcare and environmental issues. © 2024 IEEE.

关键词： Microchannels

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Data-Driven Precision Agriculture advanced Irrigation System for Sustainable Smart Farming

Data-Driven Precision Agriculture Advanced Irrigation System...

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Innovative Research in Applied Science, Engineering and Technology (IRASET),conference on

作者： Akram Ghilan Youssef EL AFOU Mostafa MERRAS Nabil El Akkad Laboratory: Engineering Systems and Applications (LESA) ENSA of Fez Sidi Mohamed Ben Abdellah University Fez Morocco IMAGE Laboratory High School of Technology Moulay Ismail University Meknes Morocco

ISBN: (数字)9798350309508

ISBN: (纸本)9798350309515

Precision Agriculture (PA) is a farming management strategy that leverages digital technologies and techniques to monitor and optimize agricultural production processes. By utilizing data streams from satellites, mobile phones, the Internet of Things (IoT), and technologies like cloud computing and artificial intelligence, PA has the potential to improve the quantity and quality of agricultural outputs while reducing inputs and waste. This article presents a proposed irrigation system for PA in the field of smart farming. The system incorporates a diverse set of sensors, including soil moisture and temperature sensors, air humidity and temperature sensors, water level sensors, and light sensors. It also integrates weather data from a forecasting platform, encompassing variables such as wind speed, wind direction, and weather status. By collecting and analyzing field-specific data alongside weather forecasts, the system enables precise and sustainable watering practices. The data is stored, analyzed, and visualized using a ThingSpeak platform, providing farmers with valuable insights to make informed irrigation decisions.

关键词： Temperature sensors Temperature measurement Irrigation Wind speed Soil moisture sensor systems Internet of Things

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Polarimetric diversity in reference-free amplitude-based Wi-Fi sensing

Polarimetric diversity in reference-free amplitude-based Wi-...

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IEEE National conference on Radar

作者： Carlo Bongioanni Fabiola Colone Marco Di Seglio Francesca Filippini Francesco Fioranelli School of Advanced Defence Studies Rome Italy Dept. of Information Engineering Electronics and Telecommunications Sapienza University of Rome Italy Dept. of Cognitive Procedures Fraunhofer Institute for High Frequency Physics and Radar Techniques (FHR) Germany Microwave Sensing Signals & Systems (MS3) Group Delft Delft TU Netherland

ISBN: (数字)9798350329209

ISBN: (纸本)9798350329216

Passive sensing exploiting Wi-Fi as an illuminator of opportunity has attracted considerable interest for the ubiquitous presence of Wi-Fi systems in many environments, and the relative low cost & complexity of related passive solutions. In this paper, we consider a reference-free, amplitude-based sensing strategy exploiting Wi-Fi signals of opportunity and we investigate the potential advantage conveyed by the use of polarimetric diversity on receive. Specifically, we exploit the data collected by a dual-pol receiver to experimentally demonstrate that the joint availability of the signals collected by differently polarized antennas (H and V) could remarkably enhance the detection performance of the resulting Wi-Fi sensor, even if based on such a simple and cost-effective reference-free sensing approach. Moreover, we analyze the characteristics of the target signatures extracted by the considered amplitude-based approach for either single and dual-pol receivers, in order to investigate their suitability for detecting and recognizing different human movements, in view of future applications for automatic classification.

关键词： Costs Target recognition Receiving antennas Radar Radar scattering Feature extraction Radar polarimetry

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An Energy Efficient Clustering for Underwater Acoustic sensor Networks using 6G Technology

An Energy Efficient Clustering for Underwater Acoustic Senso...

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Recent Trends in Computer Science and Technology (ICRTCST), International conference on

作者： Shams Tabrez Siddiqui Syed Ghyasuddin Hashmi Mohammed Maqsood Ali Ziauddin Syed Khalid Ali Qidwai Abu Salim Department of Computer Science College of Engineering and Computer Science Jazan University Jazan Saudi Arabia Department of Business Administration Applied College Jazan University Jazan Saudi Arabia

ISBN: (数字)9798350351378

ISBN: (纸本)9798350351385

These underwater Acoustic sensor Networks (UWSNs) present unique challenges due to the harsh and dynamic underwater environment, making efficient communication protocols essential for their operation. This paper introduces an innovative Energy Efficient Clustering Routing Protocol (EECRP) specifically designed for UWSNs, leveraging the advancements of 6G technology. EECRP employs a distributed clustering mechanism and energy-efficient routing strategy to optimize energy consumption, prolong network lifetime, and enhance communication reliability. The protocol integrates with 6G technologies, such as terahertz communication and quantum communication security, to further enhance performance and security in UWSNs. Through simulation and comparative analysis, EECRP demonstrates superior performance compared to existing routing protocols in terms of energy efficiency, throughput, and scalability. EECRP’s contributions lie in its novel approach to routing in UWSNs, emphasizing energy efficiency, sustainability, and integration with advanced technologies. This research paves the way for the adoption and deployment of EECRP in various underwater applications, facilitating scientific research, environmental monitoring, and technological innovation in underwater communication systems.

关键词： 6G mobile communication Underwater communication Technological innovation Routing Throughput Energy efficiency Routing protocols

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Social Group Optimization Based Cluster Head Identification in Underwater Acoustic sensor Networks 5

Social Group Optimization Based Cluster Head Identification ...

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5th International conference on Future Networks and Distributed systems: The Premier conference on Smart Next Generation Networking Technologies, ICFNDS 2021

作者： Bhattacharya, Trilok Patel, Pratul Jasmine Jena, Junali Acharya, Biswaranjan Sagayam, K. Martin Abd Wahab, Mohd Helmy Ambar, Radzi School of Computer Science and Engineering Kalinga Institute of Industrial Technology Deemed to Be University Odisha Bhubaneswar India Karunya Institute of Technology and Sciences Department of ECE India Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia Advanced Telecommunication Research Centre Malaysia Universiti Tun Hussein Onn Malaysia Faculty of Electrical and Electronic Engineering Malaysia

ISBN: (纸本)9781450387347

Due to the advancements in ocean monitoring and underwater exploration, it has become increasingly important to incorporate a method of underwater sensor network that would be cost effective and energy efficient, reducing maintenance efforts and increasing longevity. Underwater sensor Network applications based on acoustic, optical and RF communication are gaining popularity, especially acoustic communication in this area for applications such as offshore oil and gas extraction, military surveillance, mine detection, tsunami, and hurricane forecasts to name a few. One of the simpler architectural implementations of the sensor network is the 2D - Underwater sensor Network, where a group of sensor networks are anchored underwater to the surface, with a cluster head nominated for communication within the cluster nodes and the surface buoyant nodes. There exist certain optimization algorithms that address the problem of optimal cluster head selection to minimize resources consumed and increase the lifespan of the cluster. One such technique that we use in our research is Social Group Optimization (SGO). It is based on the human behavior of learning and solving complex problems. This report uses this SGO technique to choose the cluster head among a set of clusters, in which number of solutions are taken and calculated to yield a robust solution where the sacrifices of time and complexity are minimized. © 2021 ACM.

关键词： Offshore oil well production

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