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smart Electromagnetic Environments Empowering Future Communication Systems: A Real-World Indoor Experimental Validation 12

Smart Electromagnetic Environments Empowering Future Communi...

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12th international conference on Modern Circuits and Systems Technologies, MOCAST 2023

作者： Capra, Federico Albi, Federico Benoni, Arianna Erricolo, Danilo Oliveri, Giacomo Rocca, Paolo Salucci, Marco Yang, Shiwen Massa, Andrea ELEDIA@UniTN - University of Trento DICAM ELEDIA Research Center Trento Italy ELEDIA@UIC University of Illinois Chicago ELEDIA Research Center ChicagoIL United States ELEDIA@XIDIAN Xidian University ELEDIA Research Center Xi'an China ELEDIA@UESTC - UESTC ELEDIA Research Center Chengdu China ELEDIA@TSINGHUA Tsinghua University ELEDIA Research Center Beijing China

ISBN: (纸本)9798350321074

In the framework of the emerging smart ElectroMagnetic Environment (SEME) paradigm, this work presents a first experimental proof of the feasibility and effectiveness of passive and static electromagnetic skins (PSSs) for improving the coverage within an indoor 5 GHz Wi-Fi network. The goal of this study is to verify that the proper design and installation of a simple/low-cost SEME field manipulating device can boost the received power and the overall quality-of-service (QoS). Towards this end, a preliminary result (drawn from an on-going large-scale measurement campaign mimicking as much as possible a realistic user experience using commodity devices) is shown. © 2023 IEEE.

关键词： Wi-Fi

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Integrating AI-Driven IoT Solutions for Enhanced Predictive analytics in Healthcare a Comprehensive Study on Chronic Disease Management

Integrating AI-Driven IoT Solutions for Enhanced Predictive ...

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intelligent computing and Emerging Communication Technologies (ICEC), international conference on

作者： S. V. N. Sreenivasu Siva Koteswararao Katta Jerlin Priya Lovelin Auguskani Dumpa Vamsi Priya V Jagadish Vedaprada Raghunath Dept of Computer Science and Engineering Narasaraopeta Engineering College Narasaraopet India Department of Mechanical KITEW Kakinada Department of Nursing Jazan University Kingdom of Saudi Arabia Basic Sciences & Humanities (Statistics)Vignan Institute of Information and Technology Visakhapatnam Department of CSE Malla Reddy Engineering College (A) Hyderabad India Visveswaraya Technological University India

ISBN: (数字)9798331508432

ISBN: (纸本)9798331508449

The high incidence of chronic non-communicable diseases (NCDs) places a significant financial strain on public health systems. Brazil is projected to see a rise in mortality rates caused by non-communicable diseases (NCDs) by 2030. These include cancer, cardiovascular disease, respiratory illness, and diabetes. The unique challenge of managing chronic and integrated care for NCDs is well-documented. This study presents an AI-based framework for managing chronic diseases and providing digital health services globally. The suggested platform is constructed and supported by healthcare 4.0 technologies, which enable the implementation of a smart healthcare system. Among these innovations are AI-enabled cloud solutions, the internet of medical things, and wearable technology. Also included in the publication is a case study of diabetes prediction that demonstrates the platform's viability. An initial dataset was created for the research case with many attributes, including bio-impedance, skin impedance, skin temperature, pulse rate, and oxygen concentration. In this study, we investigate how the IoT and Artificial Intelligence (AI) are changing the face of illness detection in connected healthcare systems. AI has quickly become an indispensable tool in the healthcare industry, providing advanced algorithms for evaluating medical data and facilitating forecasting and decision-making. The internet of things (IoT) improves upon this by allowing web-enabled devices, such as implanted sensors and wearables, to continuously gather data. By integrating AI and IoT, smart healthcare systems improve medical procedures, patient experiences, and operational operations. Rapid and reliable disease diagnosis is made possible by combining AI-driven procedures with IoT data streams. This paper aims to overcome the limitations of traditional methods, which are typically influenced by human biases.

关键词： Medical services Skin Diabetes Reliability Medical diagnosis Artificial intelligence Medical diagnostic imaging Monitoring Wearable sensors Diseases

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IoT based Novel Design of intelligent Healthcare Monitoring System with Internet of Things and smart Sensors

IoT based Novel Design of Intelligent Healthcare Monitoring ...

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Applied Artificial Intelligence and computing (ICAAIC), international conference on

作者： Waseem Akhtar Khursheed Ahmad Sajja Suneel L. Nanthini Shambhu Sharan Srivastava M.Sai Veerraju Tejashree Tejpal Moharekar Department of Commerce & Management M.S.G. Arts Science & Commerce College College Road Malegaon Camp Department of CSE(Data Science) Institute of Aeronautical Engineering Dundigal Hyderabad Telangana India AP/CSE(CYBERSECURITY) Nandha Engineering College (Autonomous) Department of Computer Science School of Management Sciences Varanasi Dept. Of EEE S R.K.R. Engineering College Bhimavaram Yashwantrao Chavan School of Rural Development Shivaji University Kolhapur Maharashtra India

ISBN: (数字)9798350375190

ISBN: (纸本)9798350375206

This research study introduces the IoT based Healthcare Monitoring System (LIoTHMS), a revolutionary framework designed to enhance healthcare monitoring through the integration of smart sensors. The proposed system incorporates sensors, including the ECG Shield, Heart Rate Muscle Sensor, Pulse Rate Sensor, KY-037 Sound Sensor, and DS18B20 Digital Temperature Sensor. These sensors collectively form a comprehensive solution for real-time patient monitoring. The ECG Shield ensures continuous electrocardiogram monitoring for early detection of cardiac anomalies, while the Heart Rate Muscle Sensor and Pulse Rate Sensor provide valuable data on cardiovascular health. The KY-037 Sound Sensor captures environmental sounds, contributing to auditory health monitoring, and the DS18B20 Digital Temperature Sensor monitors the patient’s body temperature. This research study details the architecture of LIoTHMS, emphasizing sensor interconnectivity and its role in creating a healthcare monitoring ecosystem. Through advanced data analytics and machine learning algorithms, LIoTHMS processes real-time data, offering healthcare professionals timely and accurate insights into patient health. This implementation signifies a significant advancement in proactive and personalized healthcare, supporting early disease detection and timely medical interventions. LIoTHMS stands as a testament to the potential of IoT in revolutionizing modern healthcare monitoring.

关键词： Temperature sensors Heart rate Medical services Muscles Electrocardiography Sensor systems Real-time systems

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Design and Implementation of Coroutine Management Environment

Design and Implementation of Coroutine Management Environmen...

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2022 international conference on Computer Graphics, Artificial Intelligence, and data Processing, ICCAID 2022

作者： Cai, Bin Qiu, Bingcheng Yao, Jian Fu, Jun Xue, Yunlan Liu, Xiaofei Wu, Ruilong Zhang, Xu Guangdong Guangzhou China Wuhan University Hubei Wuhan China China Hi-Tech Group Co. Ltd. Guangdong Guangzhou China Blue Dot Power Data Technology Co. Ltd. Beijing China

ISBN: (纸本)9781510663350

Advances in network and storage technologies enable data centers to provide high-concurrency and low-latency processing responses. To meet user needs, a variety of low-latency technologies can be used to improve the overall concurrent response capability of the system on the premise of ensuring system stability. User mode thread pool is one of the techniques that can be used. In a multi-core processor system, the scheduling management of the user mode thread pool is much more complicated. At present, the scheduling management of the user mode thread pool mainly focuses on the resource utilization of the user mode thread pool itself and the scheduling management of many user-mode threads, such as dynamically adjusting the number and usage of user mode threads in the user mode thread pool according to the load of the system, and replacing the system thread scheduling with user mode thread scheduling, etc. The existing user mode thread scheduling methods do not distinguish the performance requirements of different data processing tasks, treat all user mode thread tasks in the same way, cannot reflect the performance requirements of different user mode thread tasks, and cannot provide more fine-grained user mode thread execution timing control;the existing user mode thread scheduling methods do not provide more effective scheduling control for the host thread, but instead use the thread scheduling mechanism of the operating system itself to control the execution of all kernel threads which is difficult to isolate the host thread and other kernel threads in the system;The existing user mode thread scheduling methods cannot give full play to the parallel execution advantages of the multi-core processor architecture, and it is difficult to implement unified resource allocation management among multiple user mode thread pools. This paper provides a two-level scheduling management method for user mode thread pools that effectively integrates the operating system scheduling m

关键词： Resource allocation

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Big data analytics Framework for smart City Real-Time Fuzzy Complex Event Processing

Big Data Analytics Framework for Smart City Real-Time Fuzzy ...

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international conference on intelligent and Fuzzy Systems, INFUS 2020

作者： Wadii, Basmi Boulmakoul, Azedine Karim, Lamia Lbath, Ahmed Computer Science Department FSTM Hassan II University of Casablanca Casablanca Morocco LISA Lab. ENSA Berrechid Hassan 1st University Settat Morocco LIG/MRIM CNRS University Grenoble Alpes Grenoble France

ISBN: (纸本)9783030511555

smart cities are urban areas that puts internet technology in use to ease access for its citizens to its different services, using countless different types of electronic devices and applications that constitutes what its known as Internet of things. It is a cyber fona where sensors and actuators interacts to surface a virtual city of rich data, based on multiple phenomenons of diverse nature - natural, industrial, urban and social - occurring in its different areas, that emit meaningful events describing their state as different intervals of time. We chose to call them in this paper, fuzzy complex space time events, due to their fuzzy nature and tight relationship with their geospacial position, time and their values impredictible nature. Portunus is a system that aims to collect and distribute data over sensors and actuators, supporting MQTT and HTTP to communicate over the network, additionally, it was designed as a microservice based system, and uses NoSQL database systems to cop up with the large data volume. However, data collection as a virtue is not enough, but only the first step to benefit from this vague pool of rich data. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： smart city

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A smart Innovation of Business Intelligence Based Analytical Model by Using POS Based Deep Learning Model

A Smart Innovation of Business Intelligence Based Analytical...

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Disruptive Technologies (ICDT), international conference on

作者： Sharath Kumar Jagannathan Gulhan Bizel Thomas Abraham J V G. Kannan Veeramalai Sankaradass Durgaprasad Navulla Frank J. Guarini School of Business Saint Peter’s University Jersey City NJ USA School of Computing Science and Engineering Vellore Institute of Technology Chennai Tamil Nadu India Department of Management Studies St. Peter’s Institute of Higher Education and Research Chennai Tamil Nadu India Department of Computer Science and Engineering Chennai Institute of Technology Chennai Tamil Nadu India KL Business School Koneru Lakshmaiah Education Foundation Guntur Andhra Pradesh India

In analytics and business intelligence, there are a lot of things that can go wrong. Be it a report or a plan in the data based results must be consistent, verifiable, accurate to emerge and most importantly, acceptable to the end user. Contrary to the popular belief that the coexistence of multiple BI tools poses some major impediment to the advancement of high-quality analytics output, allowing multiple tools at the same time has several serious advantages in many ways. These are all examples of BI software and are more intelligent than relatively sophisticated tools. In this paper innovative business intelligence based analytics model was proposed to enhance the point of sale in commercial retail market. The practice of continuous integration, invented by software developers and borrowed by the analytics and business intelligence community, is an attempt to detect mistakes or errors early. The Point of sale systems occupies every retail space. Any company that has employees has some software that manages payroll, Sales reports are almost universal.

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Exploration of Cloud computing and Deep Learning on smart Building Management Platform

Exploration of Cloud Computing and Deep Learning on Smart Bu...

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2021 IEEE international conference on Emergency Science and Information Technology, ICESIT 2021

作者： Hu, Biaobiao Chen, Guorong Wen, Tingting Zhang, Yixuan Wang, Bocheng Rong, Lu School of Intelligent Technology and Engineering Chongqing University of Science and Technology Chongqing China

ISBN: (纸本)9781665435314

As an important pillar of China's national economy, the construction industry promotes the development of China's economy. Due to the late start of China's construction industry and the corresponding construction technology is not advanced enough to make China's construction industry intelligent level is low, for the above problems, this paper proposes a cloud computing and deep learning based intelligent building integrated management platform architecture, the hierarchy is mainly divided into the perception layer, network layer and application layer, the perception layer has intelligent sensors and intelligent controller and other basic components, responsible for the collection of building construction The perception layer is composed of basic components such as smart sensors and smart controllers, which are responsible for collecting data during the construction process, combining cloud computing technology and neural network as the network layer to analyze and process the massive data in the construction project, and finally feeding the data information to the application layer, so that the construction party and supervision department can visualize the progress of the construction project at any time, and also detect the construction condition in real time, thus improving the building intelligence level. © 2021 IEEE.

关键词： Cloud computing

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An intelligent Predictive analytics System for Transportation analytics on Open data Towards the Development of a smart City 13th

An Intelligent Predictive Analytics System for Transportatio...

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13th international conference on Complex, intelligent, and Software Intensive Systems (CISIS)

作者： Audu, Abdul-Rasheed A. Cuzzocrea, Alfredo Leung, Carson K. MacLeod, Keaton A. Ohin, Nibrasul, I Pulgar-Vidal, Nadege C. Univ Manitoba Winnipeg MB Canada Univ Trieste Trieste Italy

ISBN: (纸本)9783030223540;9783030223533

As time is a precious asset, bus riders would desire to get accurate information about bus arrival time. Although different research approaches have been developed to correctly predict bus arrival time, very few of them produce highly precise and accurate results based on open data. In this paper, we present an intelligent system designed for transportation analytics on open data such as bus delay data. Specifically, the system accesses open data to analyze public transport data-such as historical bus arrival time-for urban analytics;it then conducts data analytics and mining to discover frequent patterns. Based on the discovered patterns, the system makes predictions on whether the bus arrives on time or is being late. Evaluation on real-life open data provided by a Canadian city show the effectiveness and prediction accuracy of our intelligent system in transportation analytics on open data. The results are encouraging towards the goal of developing smart cities.

关键词： intelligent system Transportation analytics Open data Public transportation Bus Bus delay data analytics Frequent pattern mining Predictive analytics smart city

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IoT Enabled Real Time Pharmaceutical Quality Monitoring an AI Driven Approach for Ensuring Medicine Safety and Compliance

IoT Enabled Real Time Pharmaceutical Quality Monitoring an A...

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international conference on Trends in Electronics and Informatics (ICEI)

作者： S. Sivaranjani S. Varshini B. Sowmiya S. Sowmiyaa S. Thavanirutha Department of Electronics and Communication Engineering M. Kumarasamy College of Engineering Karur Tamilnadu India

ISBN: (数字)9798331544607

ISBN: (纸本)9798331544614

Effective healthcare depends on guaranteeing the quality and safety of medicines. Traditional approaches of purely using expiration date for product consignment and manual testing to check for problems like contamination, adulteration or degradation failed due to the time and cost involved. This paper presents an IoT based real time medicine quality monitoring system through smart sensors, spectroscopy and cloud-based analytics to monitor the pharmaceutical integrity in storage and transportation continuously. IoT connected spectroscopic devices are used in the system to be able to detect anomalies and chemical compositions and transmit data to a centralised cloud platform for real time assessment. Automated alerts are issued announcing immediate corrective action in the presence of such deviations as impurities or degradation because of improper environmental conditions. This IoT enabled online monitoring framework enables efficiency, reduces manual testing dependence and ensures that only safe and effective drugs are delivered to the consumers. The proposed system enhances pharmaceutical quality assurance through IoT that provide seamless connectivity and automation to enable a scalable, cost effective and real time circumvention of counterfeit and substandard drugs.

关键词： Drugs Cloud computing Spectroscopy Quality assurance Manuals Real-time systems Safety Monitoring intelligent sensors Testing

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Research and Design of Big data Unified Analysis Platform Based on Cloud computing

Research and Design of Big Data Unified Analysis Platform Ba...

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international conference on Multi-modal Information analytics, MMIA 2021

作者： Zhen, Zhiming Science and Technology College Gannan Normal University Ganzhou341000 China

ISBN: (纸本)9783030748104

With the popularity of smart phones, tablet computers and other intelligent handheld terminals, and the gradual promotion of digital campus construction, learning through mobile devices has become an important way for college students to learn. This paper analyzes the needs of mobile learning platform in Colleges and universities, provides the overall design of mobile learning platform based on digital campus and cloud computing technology, and defines the main functional modules of mobile learning platform, which provides a solution for the construction of mobile learning platform integrated with traditional classroom teaching in Colleges and universities. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Big data

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