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Context-Aware Remote Patient Monitoring System with IoT and Digital Security

Context-Aware Remote Patient Monitoring System with IoT and ...

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IEEE International conference on System, Computation, Automation and Networking (ICSCAN)

作者： S. Geetha P. Karthikeyan Yughesh N Prasanth D Vishva V Department of Banking Technology Pondicherry University Puducherry India Department of Computer Science and Engineering Sri Manakula Vinayagar Engineering College Puducherry India

ISBN: (数字)9798331510022

ISBN: (纸本)9798331510039

The “Context Awar Remote Patient Monitoring System with IoT and Digital Security” revolutionizes continuous healthcare by integrating IoT technology, sensors, and cloud computing to address the growing need for effective at-home patient monitoring. This system ensures vital health data is continuously recorded, analyzed, and made available to healthcare professionals in real-time. At its core is the Node MCU microcontroller, which connects key sensors to a cloud-based platform. The SPO2 sensor measures blood oxygen saturation to detect issues like hypoxemia, while the body temperature sensor tracks core temperature, signaling possible infections or fevers. An environmental temperature sensor monitors ambient conditions, crucial for patients with chronic illnesses or weakened immunity. Data is securely transmitted to the cloud for analysis using machine learning algorithms. These tools cross-reference vital and environmental data to detect health anomalies and predict early illness onset. For example, a drop in oxygen levels combined with a fever triggers alerts for potential respiratory infections, empowering healthcare providers to intervene promptly and prevent complications. This system's predictive capabilities and real-time alerts ensure timely responses to critical thresholds, enhancing patient safety and reducing hospital admissions. A user-friendly interface allows patients and caregivers to monitor health trends via mobile and web applications. By enabling continuous, remote monitoring, this solution benefits patients with chronic conditions, the elderly, and post-surgery individuals, providing peace of mind and reducing the workload on healthcare facilities. It promotes high-quality care from the comfort of patients' homes, aligning with modern telehealth needs. In conclusion, the “Context Awar Remote Patient Monitoring System with IoT and Digital Security” is a transformative tool for remote care, combining advanced sensor technology, real-time analytics,

关键词： Temperature sensors Temperature measurement Patient monitoring Cloud computing Medical services Real-time systems sensor systems sensors Security Biomedical monitoring

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An Efficient and Secure Framework for Smart Healthcare Using IoT and Machine Learning

An Efficient and Secure Framework for Smart Healthcare Using...

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Decision Aid Sciences and Application (DASA), International conference on

作者： Vivek Kumar Pandey Shiv Prakash Tarun Kumar Gupta Vandana Rathore Abhishek Singh Tiansheng Yang Rajkumar Singh Rathore Department of Electronics and Communication University of Allahabad Prayagraj India Department of Electronics and Communication University of Allahabad Prayagraj Uttar Pradesh India Department of Computer Science Miranda House University of Delhi Delhi India Institute of Engineering & Technology Dr. A.P. J. Abdul Kalam Technical University Lucknow India University of South Wales Pontypridd United Kingdom Cardiff School of Technologies Cardiff Metropolitan University Cardiff United Kingdom

ISBN: (数字)9798350369106

ISBN: (纸本)9798350369113

The healthcare systems worldwide are challenged with the increased demand for rapid and efficient patient care. In this context, an advanced solution is required to meet the growing needs. This paper presents an intelligent healthcare framework integrating IoT devices with machine learning algorithms to enable real-time predictive patient monitoring. It comprises a four-layer architecture: data acquisition from IoT sensors, data preprocessing, analytics for predictive modeling, and an application layer for user interactions. Validated with data from the MIMIC-iii and PhysioNet datasets along with 12 months of IoT sensor data from a university medical center, the framework achieved 96% prediction accuracy with precision, recall, and ROC AUC scores of 0.95, 0.96, and 0.98, respectively. The system had a great response time of 200 milliseconds. It has greatly improved early detection by 36.9% and reduced false alarms by 68%. False alarms decreased from 25% to 8%, and response time was reduced from 45 to 12 minutes, or 73.3 %. Resource utilization analysis reflects optimal performance since the analytics layer hit a spike at 45% CPU utilization, thereby pointing out optimal load management. Patient satisfaction also rose to 22.7%, increasing from 75% to 92%, reflecting the framework's impact on care quality. All these results render the framework an effective and scalable solution that optimizes healthcare resources while improving care for the patient.

关键词： Patient monitoring Accuracy Machine learning algorithms Medical services Predictive models Real-time systems Internet of Things Time factors Resource management Random forests

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Intelligent Paving and Rolling Construction Technology of Asphalt Pavement

Intelligent Paving and Rolling Construction Technology of As...

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2021 International conference on advanced Technologies and applications of Modern Industry, ATAMI 2021

作者： Yuan, Taiping Wang, Zheng Hong, Qiaozhang Chen, Jing Lei, Jiechao Meng, Yongjun China Southern Power Grid Energy Development Research Institute China College of Civil Engineering and Architecture Guangxi University Nanning China Key Laboratory of Disaster Prevention and Engineering Safety Ministry of Education Nanning China National High- Performance Computing Center Nanning Branch Nanning China

The intelligent construction system of asphalt pavement consists of an intelligent paver, driverless roller, mobile base station, intelligent control program, etc. By installing GPS(BDS)+ GNS satellite receiver, 5G communication chip, microwave communication host, radio signal receiving antenna on the construction equipment and connecting with the processor, switch, program software, and other components set on the equipment, integrate the laser obstacle avoidance radar, infrared temperature detection device, laser ranging sensor and other terminal equipment set on the equipment to realize the intellectualization of equipment use function;By running the intelligent control system, mobile 5G communication base station system and construction area acquisition system, command the linkage operation of multiple intelligent types of equipment to realize the intelligent control of pavement construction and meet the requirements of asphalt pavement design specifications. © Published under licence by IOP Publishing Ltd.

关键词： 5G mobile communication systems

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Enhancing Safety in Autonomous Vehicles through advanced AI-Driven Perception and Decision-Making systems

Enhancing Safety in Autonomous Vehicles through Advanced AI-...

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Intelligent Data Science Technologies and applications (IDSTA), International conference on

作者： Yazan Alahmed Reema Abadla Mohammed Jassim Al Ansari Faculty of Engineering Al Ain University Abu Dhabi U.A.E. School of Business University of Central Lancashire preston UK

ISBN: (数字)9798350354751

ISBN: (纸本)9798350354768

Accidents, congested roads, consumption of energy, and emissions may all decrease significantly with the rise of self-driving cars, providing a promising response to social and environmental issues. In this study, researchers investigate the way the integration of innovative AI-driven perception and decision-making systems into AVs impacts safety. AVs have the potential to change transportation by reducing accidents caused mainly by human error. They may operate on their own or in conjunction with human drivers. The primary goal is to investigate and enhance AV safety by creating highly sophisticated perception and decision-making technologies driven by machine learning. Pragmatism research philosophy, experimental research design, and inductive approach serve as the selected methods of the study. In addition, secondary qualitative data analysis methods help evaluate the entire study. The outcomes of the study demonstrated that the advancement of autonomous vehicles depends significantly on the creation of AI-driven sensors. “Vehicle-to-vehicle (V2X) networks” for communication and safety features increase security, while integrated camera systems with acoustic and thermal sensors improve sensing capacities. Deep learning techniques, especially “convolutional neural networks (CNN)” and “fully convolutional networks (FCN)”, facilitate accurate object recognition and segmentation. Vehicles’ ability to handle difficult road conditions is further improved by a real-time risk evaluation and trajectory planning based on human-like behavioral modeling.

关键词： Decision making Vehicular ad hoc networks Thermal sensors Real-time systems sensor systems Safety Autonomous automobiles Convolutional neural networks Vehicle-to-everything Vehicles

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Orbital angular momentum with the approach of using in sub-6GHz 5G mobile communications for wireless applications

Orbital angular momentum with the approach of using in sub-6...

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Global Power, Energy and Communication conference (GPECOM)

作者： Seyed Ali Khorasani Hassan Zakeri Gholamreza Moradi Mohammad Alibakhshikenari Chan Hwang See Ernesto Limiti Department of Electrical Engineering Sharif University of Technology Iran Department of Electrical Engineering Amirkabir University of Technology Iran Department of Signal Theory and Communications Universidad Carlos III de Madrid Leganés Madrid Spain School of Eng. and the Built Environment Edinburgh Napier University Edinburgh United Kingdom Department of Electronic Engineering University of Rome Tor Vergata Rome Italy

ISBN: (数字)9798350351088

ISBN: (纸本)9798350351095

This paper discusses the effect of the orbital angular momentum on the fifth generation of mobile communication. A new generation of mobile requires advanced antenna systems capable of sending and receiving massive amounts of data. The beamforming method and multi-input multi-output systems are proposed solutions to increase the communication network’s channel capacity by using a six-element multiple-input multiple-output (MIMO) antenna system working in the N77 (3.2-4.2 GHz) and the N79 (4.4 GHz to 5.0 GHz) frequency bands for smartphone *** OAM, an inherent feature of electromagnetic waves, is a suitable solution for increasing channel capacity. This feature will increase channel capacity by producing orthogonal modes. Using antenna arrays is an effective way to produce these modes. The results of FEKO simulations show the capability of this method.

关键词： Wireless communication Orbital calculations Channel capacity 5G mobile communication Array signal processing Electromagnetic scattering Receiving antennas

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Integrating In-Ear Wearable sensors with Deep Learning for Head and Facial Movement Analysis

Integrating In-Ear Wearable Sensors with Deep Learning for H...

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Big Data Analytics and Practices (IBDAP), International conference on

作者： Sakorn Mekruksavanich Ponnipa Jantawong Anuchit Jitpattanakul Department of Computer Engineering School of Information and Communication Technology University of Phayao Phayao Thailand Department of Mathematics Faculty of Applied Science Intelligent and Nonlinear Dynamic Innovations Research Center King Mongkut's University of Technology North Bangkok Bangkok Thailand

ISBN: (数字)9798350391749

ISBN: (纸本)9798350391756

Accurate and inconspicuous identification of eating behavior has substantial implications for wellness surveillance, nutritional tracking, and technological assistance. Conventional approaches for detecting eating habits frequently rely on invasive or unfeasible techniques, which restrict their practicality in real-life situations. This research introduces an innovative eating recognition system that utilizes head and face motions recorded by in-ear wearing sensors and advanced deep learning algorithms. Our approach is a non-invasive and simple-to-use method that utilizes the unique patterns of head and face motions related to eating actions. We use a specially developed in-ear wearable sensor from the EarSet dataset to gather movement information while individuals are eating. The dataset comprises a range of cranial and facial motions recorded from 30 individuals. The unprocessed sensor data is subjected to pre-processing to eliminate interference and extract pertinent characteristics. We use advanced deep learning models, such as CNN, LSTM, BiL-STM, GRU, BiGRU, and our novel hybrid model CNN-LSTM, to acquire knowledge of distinctive patterns and identify eating occurrences. Our eating recognition system has been extensively tested and proven successful. The CNN-LSTM model achieved an accuracy of 95.12% and an F1-score of 95.09% during the 5-fold cross-validation studies. Our technique demonstrates superior efficiency and applicability compared to standard deep learning algorithms, as a comparative study shows. The suggested system can combine in-ear wearable sensors with deep learning to provide inconspicuous and accurate identification of eating activities. This study enhances the development of eating detection technology and introduces new opportunities for individualized wellness tracking and helpful applications. Subsequent research will prioritize the enlargement of the dataset, integration of supplementary modalities, enhancement of deep learning models for

关键词： Deep learning Accuracy Tracking Face recognition Surveillance sensor phenomena and characterization sensor systems

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Non-invasive flow measurement technology based on Taylor's frozen turbulence hypothesis

Non-invasive flow measurement technology based on Taylor's f...

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2021 International conference on Industrial Engineering, applications and Manufacturing, ICIEAM 2021

作者： Krivonogov, Aleksey Laboratory for Self-Validating Sensors Systems and Advanced Instrumentation South Ural State University Chelyabinsk Russia

ISBN: (纸本)9781728145877

The article is devoted a new method of flow measurement using an original mathematical algorithm and piezo film sensor. We describe the first part of an investigative project to develop a new flow measurement system. The advantage of the presented method is that it supports noninvasive flow measurement through the pipe wall. We present different results of studying mathematical methods for signal processing and numerical simulations using LES turbulence models such as Stress-Blended Eddy Simulation (SBES). The physical effect based on Taylor's frozen turbulence hypothesis, which serves as the foundation of this measurement method, is described. The mathematical algorithm and signal processing method contain a two-dimensional Fourier transform to build the frequency-wavenumber spectrum and cross-correlation function. We provide a short description about the chosen sensor and justify its use for the proposed measured system. In conclusion, the findings of our investigation and a real prototype scheme are presented. © 2021 IEEE.

关键词： Flow measurement

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Wide Angle Beam Scanning Method (BSM) for the WSN Communication applications 37

Wide Angle Beam Scanning Method (BSM) for the WSN Communicat...

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37th International Technical conference on Circuits/systems, Computers and Communications (ITC-CSCC)

作者： Rahman, Md. Moklesur Ryu, Heung-Gyoon Chungbuk Natl Univ Dept Elect Engn Cheongju 28644 South Korea

ISBN: (数字)9781665485593

ISBN: (纸本)9781665485593

Nowadays, ultra-high frequency (UHF) radio frequency identification (RFID) technique has rapidly been used for the application of multiple wireless sensor networks (WSNs) system. Additionally, it is very important to have a strengthen information signals at the receiver for which the exact location of the RFID tag must be traced at a particular boundary to be communicated properly. Therefore, in this paper, an advanced direction finding method namely the beam scanning (BS) along with a selective beam switching (SBS) system based on the electronically steerable parasitic array radiator (ESPAR) antenna is proposed to improve the signal link budget for the long distance communication, received the strengthen information signal from a particular direction, and QoS (quality of service) by minimizing the interference at the receiver in the interference channel. Beam scanning method (BSM) in the ESPAR antenna side is based on the magnitude of the received signal strength (RSS) of the tag's pilot carrier. The simulation results provide wide beam scanning angle range from -48 to 48 with a peak gain of 11 dBi and the scanning loss drops to 2 dB approximately from the peak gain due to the subarray pattern.

关键词： WSN System ESPAR Antenna Interference SBS BSM

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Gesture to Speech: A Wearable Solution for Sign Language Translation

Gesture to Speech: A Wearable Solution for Sign Language Tra...

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International conference on advanced Computing and Communication systems (ICACCS)

作者： Balamanikandan A R Bindu Madhavi Pudi Abhiram Reddy Pinjari Ameer Sohel Pamala Vijay Kumar Ashokkumar N Electronics and Communication Engineering Mohan Babu University (Erstwhile Sree Vidyanikethan Engineering College) Tirupati India

ISBN: (数字)9798350384369

ISBN: (纸本)9798350384376

This paper introduces a groundbreaking wearable device designed to address communication challenges faced by the global mute community. The device utilizes embedded flex sensors strategically placed on a glove to capture intricate sign language gestures. An embedded system, featuring a microcontroller (Arduino), processes these gestures through a sophisticated translation algorithm, converting them into both textual and speech output. The seamless integration of Bluetooth technology enables real-time wireless communication with external devices, such as smartphones or tablets. The device's versatile design ensures comfort and unobtrusiveness, making it suitable for various social, educational, and professional settings. Additionally, a rechargeable battery and efficient power management contribute to prolonged and sustainable usage. The embedded system's role is pivotal, acting as the cognitive hub that interprets and translates sign language gestures, fostering inclusivity and breaking down communication barriers. The translation algorithm, backed by machine learning techniques, enhances accuracy, making the device a reliable and practical solution. The optional inclusion of Text-to-Speech software further enriches the user experience, offering a comprehensive communication tool for the mute community. This paper discusses the device's technological architecture, design considerations, and real-world applications, emphasizing its transformative impact on global inclusivity. The research explores the potential for widespread adoption and its contribution to creating a more accessible and cohesive world.

关键词： Wireless communication Sign language Wireless sensor networks Bluetooth Embedded systems Real-time systems User experience Text to speech Wearable devices Speech processing

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Determining Various Gait Metrics using IMU and the Geographical Location of the Patient Using GPS

Determining Various Gait Metrics using IMU and the Geographi...

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International conference on advanced Computing and Communication systems (ICACCS)

作者： K. Rajasekaran Kishor. S Alan Winston. M. A Naveen. V Department of Biomedical Engineering KPR Institute of Engineering and Technology Coimbatore Tamil Nadu India

Walking is an integral part of our daily routine and requires a high level of coordination between our limbs and trunk. Gait analysis, which assesses the way we stand and move while walking, is a crucial evaluation tool in determining our health. This analysis can be performed using wearable device-based gait analysis, which utilizes sensors to provide data relevant to various health applications. The proposed novel system, with the integration of IoT technology, patients are able to perform gait analysis using wearable technology at the comfort of their own homes, eliminating the need to visit a hospital or use expensive equipment. The data collected through wearable devices, such as foot angle, height, location, oxygen saturation levels, and step count, can be easily accessed by doctors through a mobile app. This information is then used to assess the patient's health and determine the next course of action. Hence, this innovation has the potential to revolutionize the way we monitor our health and manage illnesses. Its practicality, cost-effectiveness, and accuracy make it a valuable tool for both patients and healthcare professionals and has shown promising results in over 30 people evaluated in real-time.

关键词： Wireless communication Performance evaluation Legged locomotion Wireless sensor networks Wearable computers Stroke (medical condition) Real-time systems

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