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A novel healthcare decision support system using IoT and ANFIS

International Journal of Information technology (Singapore) 2024年第8期16卷 5421-5427页

作者： Dewangan, Naveen Kumar Pandey, Neeti Gautam, Ritu Goswami, Avinash Krishna Mitkari, Santosh Rameshwar Singh, Amanveer Kopare, Anand Gobi, N. Electronics & amp Telecommunication Engineering Bhilai Institute of Technology Chhattisgarh Durg India Madhav Vidhi Mahavidyala Jiwaji University Gwalior India School of Law Sharda University Noida India Sharda School of Law Sharda University Noida India Engineering Sciences & amp Allied Engineering Bharati Vidyapeeth’s College of Engineering for Women Maharashtra Pune India Centre of Interdisciplinary Research in Business and Technology Chitkara Institute of Engineering and Technology Chitkara University Punjab Rajpura India Department of ISME ATLAS SkillTech University Maharashta Kurla India Department of Computer Science and Information Technology JAIN (Deemed-to-be University) Karnataka Bangaluru India

Modern healthcare facilities are equipped with major difficulties, particularly in poor nations where there are insufficient high-quality hospitals and medical professionals in remote places. Healthcare has profited from artificial intelligence’s revolution in many other areas of life. A few issues with the current architecture of the store-and-forward method of conventional telemedicine are that it requires a local health center with a dedicated staff, medical equipment to prepare patient reports, and long turnaround time for receiving a diagnosis and medication details from a medical expert in a main hospital, the cost of local health centers, and the requirement for a Wi-Fi connection. In this work, we present a new intelligent healthcare system built on cutting-edge technology such as deep learning and the Internet of Things (IoT). This system has the intelligence to use a medical decision support system to sense and process patient data by making use of adaptive neuro fuzzy inference system (ANFIS). For those who live in rural places, this system offers an affordable solution. By contacting local hospitals, users can determine whether they have a serious health concern and seek appropriate treatment. Additionally, the experiment findings demonstrate that the suggested system is capable of providing health services due to its efficiency and intelligence. © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： ANFIS Fuzzy logic (FL) IoT Neural networks Smart healthcare

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Priority Queueing Model-Based IoT Middleware for Load Balancing 6

Priority Queueing Model-Based IoT Middleware for Load Balanc...

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6th International Conference on Intelligent Computing and Control Systems, ICICCS 2022

作者： Ajay, P. Sharma, Avinash Dankan Gowda, V. Sharma, Anil Kumaraswamy, S. Arun, M.R. Anna University Department of Electronics and Communication Engineering Tamilnadu Chennai India Maharishi Markandeshwar Engineering College Department of Computer Science Engineering Haryana India Bms Institute of Technology and Management Department of Electronics and Communication Engineering Karnataka Bangalore India Guru Gobind Singh Indraprastha University University School of Information Communication & Technology Delhi India Global Academy of Technology Department of Computer Science and Engineering Karanataka Bengaluru India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Electronics and Communication Engineering Tamilnadu Chennai India

ISBN: (纸本)9781665410359

The Internet of Things (IoT) is a technology that extends the reach of the Internet to items in the real world, encompassing both living and non-living objects. The Internet serves as a platform for linking people and computers. Things are real-world items such as automobiles, schools, animals, heart rate monitors, and other household equipment, amongst many more examples. Since the previous several decades, scientists have been working on developing devices, networks, and protocols that may be used to monitor, control, and track real-world objects and events. Sensors, actuators, and Radio Frequency Identification Devices (RFID) are the devices that are employed for these reasons, and they are collectively referred to as IoT devices in this thesis. Wireless sensor and actuator networks (WSAN), machine-to-machine networks, and other networks established with the help of these devices are examples of networks built with the help of these devices. Communication between machines (M2M), SCADA, and RFID tracking system, among other things. The collaborative load balancing across fog nodes is proposed in this work, and the load balancing approach is used to disperse the load. © 2022 IEEE.

关键词： Middleware

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A comprehensive strategy for optimizing demand side management in smart grid systems, using both forecasting techniques and advanced metering infrastructure frameworks

A comprehensive strategy for optimizing demand side manageme...

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2023 International Conference for Technological engineering and its Applications in Sustainable Development, ICTEASD 2023

作者： Prathap, N. Vijayalakshmi, S. Kumar, Rakesh Gobinath, V.M. Srinivasan, S. Azamat Kizi, Mukhtorova Madina Al-Farouni, Mohammed Siri, Dharmapuri Electronics and Communication Engineering E.G.S. Pillay Engineering College Tamil Nadu Nagapattinam India Electronics and Communication Engineering R.M.K. Engineering College Tamil Nadu Kavaraipettai India Computer Engineering & Applications GLA University Mathura India Mechanical Engineering Rajalakshmi Institute of Technology Chennai India Electrical and Electronics Engineering CMR College of Engineering & Technology Hyderabad501401 India Tashkent State University of Economics Green" Economy and Sustainable Business Tashkent Uzbekistan College of Technical Engineering The Islamic University Department of Computers Techniques Engineering Najaf Iraq GRIET Telangana Hyderabad India

ISBN: (纸本)9798350336474

The use of Advanced Metering Infrastructures (AMI) in Smart Grid (SG) has allowed customers to engage in Demand-Side Monitoring (DSM) via the utilization of price-based Demand Response (DR) schemes provided by Distribution Companies (DC). By adopting this approach, both customers lower their energy costs and comfort, while DCs can effectively manage high electricity demand and mitigate carbon (CO2) emissions in a regulated manner. Developing an optimization framework to optimize cost, demand during peak hours, waiting time, and CO2 emission is a challenging endeavor and a priority for DSM. Most evaluations focus on minimizing costs and the Peak-to-Average Ratios (PAR). However, the efficacy of the DSM system is also influenced by customer satisfaction and the reduction of CO2 emissions. This study effectively develops a unique DSM Framework (DSMF) including four devices: (i) DC, (ii) Multi-Layer Perceptron (MLP) based prediction engine, (iii) AMI, and (iv) demand-side energy management components. The simulation outcomes clearly illustrate the efficacy of our suggested approach in surpassing all benchmark models and achieving both consumer and DC goals. © 2023 IEEE.

关键词： Forecasting

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Fabrication, Simulation and Comparison of Three Types of Polymer-based, Perovskite and Dyesensitized Solar Cells

Fabrication, Simulation and Comparison of Three Types of Pol...

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Electrical, computer and Energy Technologies (ICECET), International Conference on

作者： Majid Yahagh Farhad A. Boroumand Organic Electronics Lab Electronics Group Faculty of Electrical and Computer Engineering K.N. Toosi University of Technology Tehran Iran Organic Electronics Lab Electronics Group Materonics and Materionics Research Group Faculty of Electrical and Computer Engineering K.N. Toosi University of Technology Tehran Iran

ISBN: (数字)9798350395914

ISBN: (纸本)9798350395921

In this study, three types of polymer-based, perovskite and dye-sensitized solar cells have been fabricated and simulated. Then, these three structures are compared in terms of output parameters such as efficiency, fill factor, fabrication methods and etc. In the fabrication of the polymer-based solar cell with Al / MEH-PPV:ZnO np / PEDOT:PSS / ITO structure, in the perovskite solar cell with Au / Spiro-OMeTAD / CH 3 NH 3 PbI 3 / TiO 2 / FTO structure and for the dye-sensitized solar cell with Pt / Electrolyte/ TiO 2 -N719 / FTO structure by the spin-coating and Dr. Blade method is used. The simulation of these three structures has been done using two software, Comsol Multiphysics and Silvaco. According to the results of experimental characterizations, the efficiency for the polymer-based solar cell is η exp = 0.74%, the perovskite η exp =8.66% and for the dye-sensitized η exp =6.07%. Also, according to the simulation results, the efficiency for the polymer-based solar cell is η comsol =1.1%_η silvaco =0.73%, the perovskite η comsol = 6.06%_η silvaco = 8.6% and for the dye-sensitized η comsol =1.4%_η silvaco =1.74%. According to the results of this study, the Perovskite solar cell is the most suitable cell in terms of efficiency and, of course, has a higher manufacturing cost than the other two types.

关键词： Costs Spontaneous emission Absorption Photovoltaic cells Optical device fabrication Voltage Perovskites Software Titanium dioxide Optical polymers

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Polarization-induced photocurrent switching effect in heterojunction photodiodes

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Nano Research 2023年第4期16卷 5503-5510页

作者： Dingbo Chen Yu-Chang Chen Guang Zeng Yu-Chun Li Xiao-Xi Li Dong Li Chao Shen Nan Chi Boon S.Ooi David Wei Zhang Hong-Liang Lu State Key Laboratory of ASIC and System Shanghai Institute of Intelligent Electronics&SystemsSchool of MicroelectronicsFudan UniversityShanghai 200433China Key Laboratory for Information Science of Electromagnetic Waves Department of Communication Science and EngineeringFudan UniversityShanghai 200433China Photonics Laboratory Division of ComputerElectricaland Mathematical Sciences and EngineeringKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia

The unipolar photocurrent in conventional photodiodes(PDs)based on photovoltaic effect limits the output modes and potential versatility of these devices in *** photodiodes with photocurrent switching are emerging as a promising solution for obtaining photoelectric devices with unique and attractive functions,such as optical logic ***,we design an all-solid-state chip-scale ultraviolet(UV)PD based on a hybrid GaN heterojunction with engineered bipolar polarized electric *** introducing the polarization-induced photocurrent switching effect,the photocurrent direction can be switched in response to the wavelength of incident light at 0 V *** particular,the photocurrent direction exhibits negative when the irradiation wavelength is less than 315 nm,but positive when the wavelength is longer than 315 *** device shows a responsivity of up to−6.7 mA/W at 300 nm and 5.3 mA/W at 340 nm,*** particular,three special logic gates in response to different dual UV light inputs are demonstrated via a single bipolar PD,which may be beneficial for future multifunctional UV photonic integrated devices and systems.

关键词： GaN heterostructure ultraviolet(UV)photodiodes bipolar photocurrent optical logic device

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Design and Implementation of a LoRa-Based Remote Health Monitoring System with Emergency Alert Capabilities

Design and Implementation of a LoRa-Based Remote Health Moni...

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International Conference on Circuit, Power and Computing Technologies (ICCPCT)

作者： Rajesh K P Vinu Kumar S M Parameshwari V Divyaa N Manikanda Prabu Nallasivam Padma Suresh L Electronics & Communication Engineering Sri Krishna College of Technology Coimbatore India Mechanical Engineering Sri Krishna College of Technology Coimbatore India Electronics & Communication Engineering Nandha Engineering College Erode India Electronics & Communication Engineering Velalar College of Engineering and Technology Erode India Computer Science and Engineering Baselios Mathews II College of Engineering Sasthamcotta Kerala India

ISBN: (数字)9798350372816

ISBN: (纸本)9798350372823

Saving human lives is essential in the field of medical science. engineering technologies support to achieve this goal. This article explores the integration of Internet of Things and LoRa technology in hospital wristbands to enhance patient care and streamline healthcare operations. The proposed system employs Arduino Pro Mini microcontrollers and LoRa1276 in the LoRa enabled Patient Wrist Band Module (LPWM) to facilitate real-time monitoring of patient vital signs, such as temperature and pulse. The acquired data is transmitted wirelessly to a central nursing station. In the nursing station, a Raspberry Pi equipped with a LoRa receiver device consolidates and displays the data. Grey Wolf Optimization algorithm is used in Raspberry Pi to prioritize patient care based on predefined parameters. The integration of Explainable AI in the receiver module enhances the transparency and trustworthiness of AI-driven recommendations. This supports personalized patient care. This comprehensive approach aims to bridge the healthcare gap in ensuring efficient resource allocation and improved patient outcomes through advanced technological solutions.

关键词： Wrist Microcontrollers Explainable AI Medical services Receivers Real-time systems Resource management

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Active power reserve provision with large-scale WES and BESS

Active power reserve provision with large-scale WES and BESS

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IEEE Power engineering Society Conference and Exposition in Africa, PowerAfrica

作者： Siphelele Joseph Mndiya Mukovhe Ratshitanga Senthil Krishnamurthy Department of Electrical Electronics and Computer Engineering Cape peninsula University of Technology Cape Town South africa

ISBN: (数字)9798350389388

ISBN: (纸本)9798350389395

For an electrical system to function properly, active power reserves are needed to stabilize the frequency. Recent studies show that power utilities can convert variable wind power generation into dispatchable technology by integrating wind farms with battery energy storage systems. For this study, an IEEE 9 bus system was modified and modelled using Real-time Simulator computer-Aided Design (RSCAD) simulation package by Real-Time Digital Simulator (RTDS) technologies. Using RSCAD, active power compensation control systems for both the wind energy system and the battery energy storage system were developed. The simulation results indicate that the developed control schemes are effective, and the combination of a wind energy system and the battery energy storage system can successfully provide the active power reserves and help balance the generation and demand.

关键词： Time-frequency analysis Battery energy storage system Wind energy Simulation Wind power generation Wind farms Power system stability Real-time systems IEC Standards Standards

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Temporal-Spatial Feature Extraction in IoT-Based SCADA System Security: Hybrid CNN-LSTM and Attention-Based Architectures for Malware Classification and Attack Detection

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IEEE Access 2025年 13卷 102109-102132页

作者： Onur Polat Ali Ayid Ahmad Saadin Oyucu Enes Algül Ferdi Doäan Ahmet Aksöz Department of Computer Engineering Bingöl University Bingöl Türkiye Department of Electrical Engineering College of Engineering University of Kirkuk Kirkuk Iraq Department of Computer Engineering Faculty of Technology Gazi University Ankara Türkiye Department of Computer Engineering Adıyaman Üniversitesi Adiyaman Türkiye Department of Electrical and Electronics Engineering Kayseri University Kayseri Türkiye

This research presents a Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) model developed for malware classification from IoT devices in the SCADA system and for detecting anomalies in the network. The developed model identifies complex attacks in the network by taking advantage of the strengths of CNNs that reveal spatial features and LSTMs that detect temporal dependency. CICIoT 2023 is used as the dataset. ADAM optimization algorithm with cross-entropy loss is used to eliminate overfitting and training is performed. Within the scope of the study, the proposed model is compared by applying it with six deep learning architectures (hybrid CNN-LSTM, Non-Local Neural Network (NLNN), Residual Attention Network (RAN), Dual Attention Network (DANet), Transformer-CNN and Attentional CNN). The obtained results show that the proposed CNN-LSTM model outperforms other complex architectures and achieves a high test accuracy of 99.23%. It has demonstrated remarkable performance according to precision, recall and F1 evaluation metrics in detecting distributed denial of service (DDoS) and denial of service (DoS) attacks. The proposed model successfully identifies Mirai botnet variants and fragmentation-based attacks. Although other models, Transformer-CNN (98.81%) and DANet (98.07%), provide high performance, they fall behind the superior temporal modeling capabilities of CNN-LSTM. When the obtained findings are examined, they highlight the relative strengths of various deep learning approaches for IoT security applications. The performances of the implemented deep learning models reached accuracies exceeding 96%, demonstrating the importance of IoT-based SCADA systems against evolving cyber threats. The study revealed the superior successes of deep learning-based approaches for IoT security.

关键词： Security SCADA systems Internet of Things Malware Convolutional neural networks Protocols Long short term memory Feature extraction Access control Real-time systems

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IoT and wireless sensor network -Based Three- Tier Architecture for Continuous Cardiac Health Monitoring and Alert System 4

IoT and wireless sensor network -Based Three- Tier Architect...

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4th International Conference on Expert Clouds and Applications, ICOECA 2024

作者： Gorde, Swapnil Gulabrao Singh, Archana Tamilselvi, M. Ravivarman, G. Rajendiran, M. Maranan, Ramya MIT College of Management MIT Art Design & Technology University Pune India Private University Maharashtra India Roever Engineering College Department of Computer Science and Engineering Tamil Nadu Perambalur India Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Tamil Nadu Coimbatore India Panimalar Engineering College Department of Computer Science and Engineering Poonamallee Tamil Nadu Chennai India Saveetha School of Engineering SIMATS Department of Research and Innovation Tamil Nadu Chennai India

ISBN: (纸本)9798350385793

This study suggests a powerful Three- Tier Architecture that combines machine learning models, Internet of Things (IoT) devices, and sophisticated sensors to provide continuous cardiac health monitoring. A range of physiological data is provided by the sensors in the Data Collection Tier, which measure blood pressure, temperature, acceleration, and electrocardiogram (ECG). In the Data Processing Tier, a local server applies complex algorithms to efficiently assess the gathered data and provide insightful outcomes. By providing easy access, authentication, and alarm production, the Application Tier acts as the interface and guarantees efficient contact with healthcare providers. The unique aspect of the system is the integration of machine learning models, which were trained on recorded data for predictive analysis. k-Nearest Neighbors (KNN), Artificial Neural Networks (ANN), Decision Trees (DT), and Recurrent Neural Networks (RNN) are some examples of these models. Impressive accuracy levels are seen in the results, with ANN leading at 96.44% The measures of accuracy, precision, recall, and F1 score all demonstrate the algorithms' capacity to anticipate possible health risks, which supports the models' effectiveness. This proactive paradigm in healthcare is made possible by the comprehensive approach of continuous heart health monitoring, which enables prompt interventions and customized treatment strategies. This study increases our knowledge of the dynamics of cardiovascular health and the rapidly growing field of health care technology by demonstrating the synergy of sensor-based monitoring, IoT connectivity, and machine learning analytics in a unified architecture. In the end, patient care is improved. © 2024 IEEE.

关键词： Blood pressure

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Revolutionizing Bus Tracking and Arrival Prediction in Real Time for Both Public and Private Sectors, Powered by Firebase

Revolutionizing Bus Tracking and Arrival Prediction in Real ...

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Distributed Computing and Electrical Circuits and electronics (ICDCECE), IEEE International Conference on

作者： Mohammed Shafiulla Abdul Lateef Haroon P S Shaik Mohammed Naveed Suhail Ahmed Mahika Dhar M Utkarsh Kumar Department of Computer Science and Engineering Ballari Institute of Technology & Management Ballari India Department of Electronics and Communication Engineering Ballari Institute of Technology and Management Ballari India Department of Computer Science and Engineering Ballari Institute of Technology and Management Ballari India

ISBN: (数字)9798350318609

ISBN: (纸本)9798350318616

Public transport systems often face challenges related to reliability and efficiency, leading to inconvenience and uncertainty for passengers. Existing solutions for real-time bus monitoring typically rely on expensive Internet of Things (IoT) components. This paper presents Track N Go, a cost-effective alternative for real-time monitoring of public buses and taxis using mobile phone location data. The system utilizes a robust backend system built with Java and *** for the user interface. Integration of GPS via the Map Box API and Firebase database ensures accurate location tracking. Track N Go provides accurate real-time monitoring, addressing challenges associated with public transport and improving overall urban mobility. The system enhances convenience and peace of mind for passengers by delivering reliable and user-centric solutions. The evaluation of Track N Go demonstrates its effectiveness in improving urban mobility and transit services. By offering a reliable and cost-effective solution for real-time bus monitoring, Track N Go aims to streamline daily commutes and make public transport more efficient and predictable.

关键词： Uncertainty Smart cities Scalability User interfaces Real-time systems Mobile handsets Reliability

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