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An IoT Machine Learning Model-based Real-Time Diagnostic and Monitoring System 4th

An IoT Machine Learning Model-Based Real-Time Diagnostic and...

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4th international conference on Machine Intelligence and signal Processing, MISP 2022

作者： Awotunde, Joseph Bamidele Misra, Sanjay Ajagbe, Sunday Adeola Ayo, Femi Emmanuel Gurjar, Ramchandra Department of Computer Science Faculty of Information and Communication Sciences University of Ilorin Ilorin240003 Nigeria Department of Computer Science and Communication Ostfold University College Halden Norway Department of Computer Engineering Ladoke Akintola University of Technology Ogbomosho Nigeria Department of Mathematical Sciences Olabisi Onabanjo University Ago-Iwoye Ogun State Nigeria Shri Govindram Seksaria Institute of Technology and Science Indore India

ISBN: (纸本)9789819900848

internet of things (IoT) and machine learning (ML) have recently changed the paradigm in the area of applications in health-care systems with significant results. The ML-based models enabled with IoT-based systems have greatly expedited the medical diagnosis, real-time monitoring, and treatment in the health-care system, thus reducing the burden of health-care processes and the cost of taking care of patients by caregivers and physicians. Therefore, in this paper, a framework is proposed based on an ML model-enabled IoT-based system for real-time diagnosis of various diseases using data collected from wearable devices and sensors attached within the body of patients. The captured data are stored using an integrated cloud database for further preprocessing and processes using ML-based models. ML model was used to select the most relevant features from the cloud database and thus use the preprocessed data for the diagnosis of various diseases. The findings from the study show that the XGBoost performs reliably better when compared with other existing ML-based models with an accuracy of 95.7%, recall of 95.9%, precision of 96.0%, F1-score of 94.8%, and Receiver Operating Characteristic Curve (ROC) of 94.3%. The results proposed a framework to show that the system can be widely used to diagnose various diseases and can be used in remote areas for better monitoring of patients. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： internet of things

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Compressed Sensing of Skin Conductance Level for IoT-based wearable sensors

Compressed Sensing of Skin Conductance Level for IoT-based w...

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IEEE international Instrumentation and Measurement technology conference (I2MTC)

作者： Iadarola, Grazia Poli, Angelica Spinsante, Susanna Polytech Univ Marche Dept Informat Engn Ancona Italy

ISBN: (纸本)9781665483605

In the context of physiological monitoring applications, wearable sensor platforms usually have to sustain long-term acquisitions, necessary to assess correctly the individual health status, but also to compensate for uncertainty and noise effects, due to the uncontrolled conditions in which data are collected. Therefore, smart measurement systems based on the internet of Things paradigm require approaches able to optimize the on-board resources, either in terms of computational effort and power consumption. With a view to ensuring such an optimization, this paper presents a Compressed Sensing (CS) method for the reconstruction of the Skin Conductance Level, a signal able to encode individual traits of observed subjects, useful also in bio-metric applications. The proposed CS method employs a deterministic measurement matrix and it exploits the sparsity in the domain defined by the Discrete Cosine Transform. The Percentage of Root-mean-squared Difference, chosen as figure of merit, shows very low values for a Compression Ratio as high as 12, thus proving the excellent performance of the proposed method.

关键词： Compressed Sensing data compression remote health monitoring internet of Things wearable devices Skin Conductance Electrodermal Activity

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Deraining of image Using UNet-based Conditional Generative Adversarial Network 4th

Deraining of Image Using UNet-Based Conditional Generative A...

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4th international conference on Computing, Communications, and Cyber-Security, IC4S 2022

作者： Bose, Samprit Chavan, Deep R. Kolekar, Maheshkumar H. Indian Institute of Technology Patna Bihar India PDPM-IIITDM Jabalpur India

ISBN: (纸本)9789819914784

Adverse weather conditions like rain, fog and storm cause degradation in the quality of an image. Computer vision operations such as detection, classification and various monitoring of objects activities are adversely affected due to image degradation. Hence, image enhancement is an important pre-processing step. We propose a method for the elimination of rain streaks from rain-affected images by making use of conditional generative adversarial networks. We have used structural similarity index measure and peak signal-to-noise ratio as evaluation metrics evaluate the model. We have tested our model on one synthetic and four real-world datasets and compared the performance with other state-of-the-art methods. We have obtained a generated image that has a close resemblance with the ground truth images. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： image enhancement

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Bin Reservation based on IVPO Reversible Data Hiding Using Smoothness Mode Selection Strategy 17th

Bin Reservation Based on IVPO Reversible Data Hiding Using S...

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17th international conference on Intelligent Information Hiding and Multimedia signal Processing (IIH-MSP) / 14th international conference on Frontiers of Information technology, Applications and Tools (FITAT)

作者： Lee, Chin-Feng Shen, Jau-Ji Lin, Zong-Ye Chaoyang Univ Technol Dept Informat Management Taichung 41349 Taiwan Natl Chung Hsing Univ Dept Management Informat Syst Taichung 40277 Taiwan

ISBN: (纸本)9789811910531;9789811910524

Pixel value ordering (PVO) is a popular reversible data hiding (RDH) technology. The embedding strategy of the PVO method is to divide the image into blocks of the same size, sort the pixel values in each blocks, and embed the secret data to the maximum and minimum pixel values when embeddable conditions are satisfied. The embedding capacity of the PVO method will change due to the complexity of the block. If the pixels in the block is too different from each other, the embedding capacity of the PVO method will be limited. Therefore, in view of this limitation of the PVO method, this research proposes the smoothness mode selection (SMS) strategy. The SMS strategy determines the image shape according to the complexity of the pixels within image blocks, and then uses the bin reservation based on improved PVO RDH method to embed the secret data in the picture. The embedding strategy of this method enables each block of four pixels to carry at most four bits, so it has a significant higher embedding capacity. The experimental results show that the embedding capacity of our proposed method is higher than other PVO-based RDH schemes, and it also maintains a certain good image quality.

关键词： Block complexity Improved pixel value ordering Pixel value ordering Reversible data hiding

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OCCROB: Efficient SMT-based Occlusion Robustness Verification of Deep Neural Networks 29th

OCCROB: Efficient SMT-Based Occlusion Robustness Verificatio...

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29th international conference on Tools and Algorithms for the Construction and Analysis of systems (TACAS)

作者： Guo, Xingwu Zhou, Ziwei Zhang, Yueling Katz, Guy Zhang, Min East China Normal Univ Shanghai Key Lab Trustworthy Comp Shanghai Peoples R China Hebrew Univ Jerusalem Jerusalem Israel

ISBN: (纸本)9783031308222;9783031308239

Occlusion is a prevalent and easily realizable semantic perturbation to deep neural networks (DNNs). It can fool a DNN into misclassifying an input image by occluding some segments, possibly resulting in severe errors. Therefore, DNNs planted in safety-critical systems should be verified to be robust against occlusions prior to deployment. However, most existing robustness verification approaches for DNNs are focused on non-semantic perturbations and are not suited to the occlusion case. In this paper, we propose the first efficient, SMT-based approach for formally verifying the occlusion robustness of DNNs. We formulate the occlusion robustness verification problem and prove it is NP-complete. Then, we devise a novel approach for encoding occlusions as a part of neural networks and introduce two acceleration techniques so that the extended neural networks can be efficiently verified using off-the-shelf, SMT-based neural network verification tools. We implement our approach in a prototype called OccRob and extensively evaluate its performance on benchmark datasets with various occlusion variants. The experimental results demonstrate our approach's effectiveness and efficiency in verifying DNNs' robustness against various occlusions, and its ability to generate counterexamples when these DNNs are not robust.

关键词： Deep neural networks

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Structural Tensor Nonlinear Complex Diffusion-based Method for Sonar image Denoising 14

Structural Tensor Nonlinear Complex Diffusion-Based Method f...

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14th international conference on signal Processing systems, ICSPS 2022

作者： Tan, Minjia Yang, Yifei School of Automation Nanjing University of Science & Technology Nanjing China Ocean College Jiangsu University of Science & Technology Zhenjiang China

ISBN: (纸本)9798350336313

This paper presents a sonar image denoising method based on structural tensor and nonlinear complex diffusion (STNCD). The complex diffusion in STNCD utilizes the imaginary value generated by the diffusion process as the directional structure indicator, then controls the diffusion coefficient by introducing the eigenvalue of the structural tensor and the spatial variation structure factor related to the eigenvector. As a result, the complex value of STNCD ensures that the phase information of the image is preserved during the noise suppression process. Furthermore, we make use of the difference between the principal eigenvectors of the structural tensor to describe the local coherence of the features, and then solve the problem that the phase angle cannot be accurately estimated when constructing the structural tensor. Experimental results show that STNCD not only suppresses sonar image noise but also enhances the signal of image edge, which has a wide range of applications. © 2022 IEEE.

关键词： Eigenvalues and eigenfunctions

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DESIGN AND IMPLEMENTATION OF INTELLIGENT LIGHTING REAL image CONTROL SYSTEM based ON IOS 2

DESIGN AND IMPLEMENTATION OF INTELLIGENT LIGHTING REAL IMAGE...

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2nd international conference on internet of Things and Smart City, IoTSC 2022

作者： Sun, Wen-Chao Jin, Chun-Yong Su, Jian-De Guangxi Normal University College of Electronic Engineering Guangxi China

ISBN: (纸本)9781510654990

Aiming at the problems of single lamp control mode in traditional lighting system, monotonous light color display, and difficulty in meeting people's demand for high-quality life, an intelligent lighting control system based on iOS was designed and implemented. Use low-energy Bluetooth Mesh networking technology to uniformly manage, control, and personally change the color of multiple lighting devices;use OpenCV image processing technology to take pictures of smart lighting devices and switch the lighting devices on the photos After the operation processing of color adjustment and light intensity adjustment, the real image control that the lights in the photos on the mobile phone screen and the lighting effects of the physical lamps change simultaneously are realized, creating an immersive lighting experience and increasing the playability of smart lighting. © 2022 SPIE

关键词： Control systems

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A PHR Sharing Model based on Tangle and PRE 1

引用

作者： Xue, Xiaofeng Li, Shuzhe Liu, Siyu Li, Qiong Harbin Inst Technol Sch Cyberspace Sci Harbin Peoples R China

ISBN: (数字)9789811910531

ISBN: (纸本)9789811910531;9789811910524

The rapid development of the internet of Medical Things (IoMT) has brought new opportunities to the healthcare field, and the Personal Health Record (PHR) generated by the wearable devices in IoMT has become more and more important for the diagnosis and treatment of patients. A PHR sharing model based on Tangle and proxy re-encryption (PRE) is proposed in this paper. In the model, the PHR hash and operation log are stored in the Tangle, and the PHR is shared with medical institutions through lightweight PRE. The Tangle is adopted to meet the demand of high throughput PHR generated by IoMT, and the lightweight PRE provides effective PHR sharing while protecting patient's privacy.

关键词： Lightweight PRE PHR Sharing model Tangle

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IoT-based Air Pollution Monitoring System to Measure Air Quality on Cloud Storage 2

IoT-based Air Pollution Monitoring System to Measure Air Qua...

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2nd international conference on Paradigm Shifts in Communications Embedded systems, Machine Learning and signal Processing, PCEMS 2023

作者： Tembhurne, Vilas Kisanrao Shinde, Vinayak Dagadu Kumar, Santosh Shrimali, Manish Chhabra, Gunjan Quadri, M.N. Rajpoot, Vikram IHLR & SS Sardar Patel College Maharashtra Chandrapur India Shree L.R. Tiwari College of Engineering Maharashtra Thane India ERA University Uttar Pradesh Lucknow India Janardan Rai Nagar Rajasthan Udaipur India Graphic Era Hill University Dehradun India Nilkanthrao Shinde Arts and Science College Maharashtra Bhadrawati India Madhav Institute of Technology & Science Gwalior India

ISBN: (纸本)9798350310719

Air pollution (AP) is today's most pressing issue. Particularly concerning are the potential adverse effects that an excessive amount of certain hazardous gases, such as CO, SO2, particulate matter, and several others, may have on human health. Other environmental gases are affected by temperature, humidity, etc., wind speed, and their causes and impacts. These weather factors include temperature, humidity, as well as wind *** this project, a centralized cloud-based system using sensors that monitor and analyze AP will be developed. The information gathered by each sensor node is uploaded to a cloud server, where it is stored and can be viewed through a web browser at any time and from any location. Because the environment is being monitored in real-time, prompt action may be performed in response to discovering a contaminant in the ecosystem. This project aims to monitor the AP of the surrounding area and ensure that data are kept up to date on the internet. Readings are conducted continuously throughout the day and in real-time. Many air pollutants like SO2, CO, PM10, humidity, and temperature are considered to measure air quality by IoT-based air pollution monitoring systems (APMS). We created graphics that simplify analyzing the proportion of pollutants in a certain location. The LCD can show the gas sensor's real-time data constantly. © 2023 IEEE.

关键词： Wind

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A cellular IoT based sensor system for atmospheric studies using UAVs

A cellular IoT based sensor system for atmospheric studies u...

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2022 IEEE international conference on signal Processing, Informatics, Communication and Energy systems, SPICES 2022

作者： Rajesh, K. Ch, Laxma Reddy Varaprasad, G. Muralikrishnan, S. Indian Space Research Organization National Remote Sensing Centre Hyderabad India

ISBN: (纸本)9781665449403

internet of Things (IoT) is a network of objects or sensors which are interconnected through communication technologies for exchange of information to provide services. Sensors for atmospheric studies can be integrated into a module and mounted on Unmanned Aerial Vehicles (UAV) and data from these sensors can be uploaded to cloud for real time access. In cases where UAVs are used, most of the papers discuss atmospheric studies or air pollution monitoring through IoT where WiFi module/RF communication module and base stations on ground are used. This limits the range of the studies carried out. The proposed study intends to build a portable sensor system to be mounted on UAV for atmospheric studies and couple the same with cellular IoT using a 4G LTE modem for internet connectivity. The sensors' data is uploaded to cloud via the cellular networks and accessed anywhere in real time directly from the cloud platform without range limitations. The proposed system does not require Wifi modules or base station on ground thus reducing the hardware complexity. The designed system is capable of measuring temporal data of atmospheric parameters like PM2.5, PM10, Co2, CO, NH4, barometric pressure, temperature periodically along with spatial data: latitude, longitude and altitude. © 2022 IEEE.

关键词： internet of things

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