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The Intensive Model Design using FL for smart HC System Design 4

The Intensive Model Design using FL for Smart HC System Desi...

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4th IEEE international conference on Advance computing and Innovative Technologies in Engineering, ICACITE 2024

作者： Raman, Ramakrishnan Verma, Apurv Kumar, Vikram Rastogi, Shailesh Pillai, Biju G. Meenakshi, R. India Parul Institute of Technology Parul University Computer Science and Engineering Faculty of Engineering and Technology India Srv Media Pvt. Limited India India Sri Balaji University Faculty of Management It & Business Analytics Pune India Chennai Institute of Technology Computer Science and Engineering India

ISBN: (纸本)9798350360165

Using cutting-edge technology like wearables, internet access of Things, and smartphones, smart healthcare has become a crucial component of health policy services. This revolutionary method enables seamless connection and ongoing information access between patients, medical equipment, the facilities, allowing for intelligent responses to a variety of demands within the medical ecosystem. No matter when or where they are, patients may get urgent assistance, diagnostic services, and monitoring via the digital platform of the smart Health care Management Systems (SHMS). This research emphasizes innovation with direct healthcare services and suggests the use of the smart the management of healthcare Examination using Fuzzy Decision-Taking (SHME-FDM) technique to measure the effectiveness of technology integration. Furthermore, the Fuzzy Asymmetric Hierarchy Process-Technique for Orders of Preference by The sameness to Ideal Solution (Fuzzy AHP-TOPSIS) is used to evaluate the privacy protection and healthcare data inside the SHMS. In order to make predictions about healthcare, the research uses a fuzzy-based neural network. Through experimental analysis, reliability, accuracy, and error rates are evaluated. Notably, a security risk analysis highlights the proposed fuzzy model's potential for protecting healthcare data by demonstrating its improved risk assessment performance when compared to current methods. © 2024 IEEE.

关键词： Risk assessment

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Analysis of Digital Twins Implementation in smart City using Big data and Deep Learning 7

Analysis of Digital Twins Implementation in Smart City using...

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7th international conference on intelligent computing and Control Systems, ICICCS 2023

作者： Nayak, Chinmaya Kumar Karunakaran, S. Yamunaa, P. Kayalvili, S. Tiwari, Mohit Unni, Manu Vasudevan Sri Sri University Faculty of Emerging Technologies Sri Sri Vihar Ward No - 3 Godi Sahi Odisha Barang754006 India Computer Technology Kongu Engineering College Erode Tamilnadu Perundurai India Peri Institue of Technology Department of EEE India Computer Science & Engineering Velalar College of Engineering and Technology Erode Tamil Nadu Thindal638012 India Computer Science and Engineering Bharati Vidy Ap Eeth's College of Engineering A-4 Rohtak Road Paschim Vihar Delhi110063 India St. Claret College P. O. Box 1355 MES Ring Rd Sharadhamba Nagar Jalahalli Karnataka Bengaluru560013 India

ISBN: (纸本)9798350397253

Digital twins are becoming more relevant for business and academic users due to advances in IoT, AI, and Big data. Due to global urbanization, pollution, public safety, traffic congestion, and other challenges have arisen. New technologies make cities smarter to keep up with growth. In the Internet of Things (IoT) age, many sensing devices acquire and/or produce a broad range of sensory data over long periods of time for a variety of businesses and applications. The use case determines the device's data stream volume and speed. The efficacy of the analytics process used to analyze these streams of data to learn, predict, and act determines IoT's worth as a business paradigm changer and quality-of-life technology. This study introduces Deep Learning (DL), a family of advanced machine learning techniques, to enhance IoT analytics and teaching. Introducing new results, challenges, and research opportunities. This study may assist academics and newbies comprehend how to use DL to smart cities. Analyzing and summarizing major IoT DL research initiatives. Check out smart IoT devices with DL embedded into their AI. Ultimately, the study will identify issues and suggest additional research. Each chapter concludes with experimental findings and the newest literature review. © 2023 IEEE.

关键词： smart city

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A Demo of a Software Platform for Ubiquitous Big data Engineering, Visualization, and analytics, via Reconfigurable Micro-Services, in smart Factories 8

A Demo of a Software Platform for Ubiquitous Big Data Engine...

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8th IEEE international conference on smart computing (smartCOMP)

作者： Soderi, Mirco Kamath, Vignesh Breslin, John G. Natl Univ Ireland Data Sci Inst Galway Ireland

ISBN: (纸本)9781665481526

intelligent, smart, Cloud, reconfigurable manufacturing, and remote monitoring, all intersect in modern industry and mark the path toward more efficient, effective, and sustainable factories. Many obstacles are found along the path, including legacy machineries and technologies, security issues, and software that is often hard, slow, and expensive to adapt to face unforeseen challenges and needs in this fast-changing ecosystem. Lightweight, portable, loosely coupled, easily monitored, variegated software components, supporting Edge, Fog and Cloud computing, that can be (re)created, (re)configured and operated from remote through Web requests in a matter of milliseconds, and that rely on libraries of ready-to-use tasks also extendable from remote through sub-second Web requests, constitute a fertile technological ground on top of which fourth-generation industries can be built. In this demo it will be shown how starting from a completely virgin Docker Engine, it is possible to build, configure, destroy, rebuild, operate, exclusively from remote, exclusively via API calls, computation networks that are capable to (i) raise alerts based on configured thresholds or trained ML models, (ii) transform Big data streams, (iii) produce and persist Big datasets on the Cloud, (iv) train and persist ML models on the Cloud, (v) use trained models for one-shot or stream predictions, (vi) produce tabular visualizations, line plots, pie charts, histograms, at real-time, from Big data streams. Also, it will be shown how easily such computation networks can be upgraded with new functionalities at real-time, from remote, via API calls.

关键词： Software Platform Micro-service API Edge Fog Cloud Big data data Engineering data Visualization data analytics intelligent Manufacturing smart Manufacturing Reconfigurable Manufacturing Remote Monitoring

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Greensense: IoT-Enabled smart Monitoring And Early Detection System For Optimal Plant Health In Greenhouse

Greensense: IoT-Enabled Smart Monitoring And Early Detection...

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2024 international conference on Advances in data Engineering and intelligent computing Systems, ADICS 2024

作者： Venkatesh, R. Aadhira, K.R. Kathiravan, M. Hindustan Institute Of Technology And Science Department Of Computer Science & Engineering Chennai India

ISBN: (纸本)9798350364828

The emergence of Agriculture 4.0 signifies a transformative shift in traditional farming practices, integrating cutting-edge technologies like IoT, machine learning, and robotics to support productivity and sustainability. This era leverages real-time data and automation for precision farming, predictive analytics, and resource optimization, crucial for addressing global food security challenges while minimizing environmental impact. GreenSense represents progress within Agriculture 4.0. It seeks to revolutionize greenhouse management by integrating IoT and advanced machine learning algorithms. Through sensors, actuators, and a Raspberry Pi 4 board, this system offers a comprehensive solution for monitoring and optimizing plant health in controlled environments. The motivation behind this system stems from the imperative to enhance agricultural practices sustainably in the face of population growth. By enabling real-time monitoring and swift anomaly detection through application, this paper empowers proactive intervention to mitigate risks and optimize growing conditions. Integration of the YOLOv5 algorithm with 97% accuracy enhances precision in leaf disease and pest detection using OpenCV, reducing crop losses effectively. Beyond greenhouse management, this paper contributes to advancing sustainable agriculture. Its scalable and adaptable nature promotes resource-efficient practices and environmental care. Finally, a user-friendly interface is tailored to facilitate efficient data collection from sensors, enabling comprehensive monitoring of crop conditions, including pest and disease detection. © 2024 IEEE.

关键词： Learning algorithms

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Transitioning to smart Sustainable Cities Based on Cutting-Edge Technological Improvements

Transitioning to Smart Sustainable Cities Based on Cutting-E...

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29th international conference on Parallel and Distributed computing (Euro-Par)

作者： Andreou, Andreas Mavromoustakis, Constandinos X. Univ Nicosia Dept Comp Sci Nicosia Cyprus Univ Nicosia Res Fdn Nicosia Cyprus

ISBN: (纸本)9783031488023;9783031488030

A smart city is a concept that has been gaining momentum in recent years as cities worldwide seek to improve their efficiency, sustainability, and quality of life for their residents. smart cities are constructed atop smart data. Therefore, this research work focuses on the optimization of data acquisition, data sharing and data analysis. Aiming towards this evolution, the research elaborates on the advancement of smart healthcare, a novel approach for energy consumption, preparedness for a potential pandemic, innovative data encryption techniques, and vehicle-to-everything (V2X) connectivity to enable smart mobility. However, developing an intelligent ecosystem is paramount to providing citywide, reliable, high multi-Gbps peak data speeds with ultra-lowlatency. Hence, we finally focused our research on Unmanned Aerial Vehicles (UAV) assisted network optimization.

关键词： smart Cities UAV Healthcare Consumption V2X

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SecSCS: A User-Centric Secure smart Camera System Based on Blockchain 44

SecSCS: A User-Centric Secure Smart Camera System Based on B...

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44th IEEE international conference on Distributed computing Systems (ICDCS)

作者： Qian, Xinyuan Li, Hongwei Wang, Haoyong Xu, Guowen Xu, Shengmin Ren, Ju Univ Elect Sci & Technol China Sch Comp Sci & Engn Chengdu Peoples R China Chongqing Key Lab Automated Reasoning & Cognit Chongqing Peoples R China City Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China Fujian Normal Univ Coll Comp & Cyber Secur Fuzhou Peoples R China Tsinghua Univ Dept Comp Sci & Technol Beijing Peoples R China

ISBN: (纸本)9798350386066;9798350386059

smart cameras have gained immense popularity in commercial markets for their safety and security capabilities. Yet, the prevalent design of these intelligent camera systems often compels users to cede control of their data to potentially untrusted service providers, such as cloud services. This relinquishment can lead to unauthorized data access by these intermediaries, posing significant security and privacy risks. The conventional solutions have been to employ privacy-enhancing technologies to bypass these intermediaries, but at the cost of increased overhead for video streaming and sharing. In our study, we introduce SecSCS, a user-centric, blockchain-based secure camera system that incorporates essential features like video streaming, sharing, deletion, and permission restoration. SecSCS integrates a blockchain-enabled user login protocol with a secure device pairing mechanism that combines visual authorization with blockchain to flexibly manage the device ownership. We utilize blockchain to provide integrity protection for the video clips stored remotely, ensuring the video data remains tamper-proof. Furthermore, we present a video frame compression and a fast video encryption method aimed at boosting the efficiency of smart camera systems. Our evaluations show that, in comparison to the leading decentralized scheme, CaCTUs, SecSCS improves the computational and communication overhead for live streaming by a factor of 12.58 and 11.29, respectively, at a frame rate of 24 fps and a resolution of 720p.

关键词： smart camera system Privacy-preserving Video Encryption Access Control

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smart Sensory Approach for Soil Health Tracking based Precision Farming 3

Smart Sensory Approach for Soil Health Tracking based Precis...

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3rd international conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Bhattacharyya, Avilasha Saini, Tanisha Sharma, Vandana Mishra, Sushruta Deemed to Be University Kalinga Institute of Industrial Technology India Department of Computational Sciences Delhi NCR India

ISBN: (纸本)9798350343632

Internet of Things (IoT) technology will have an impact on every area in the future as it will make everything intelligent, which will affect everyone's daily lives. It is a network composed of many devices that can configure themselves. The use of IoT in smart farming is transforming traditional agricultural practices by reducing crop loss, improving them, and making them more cost-effective for farmers. The study's goal is to propose a technological model for soil health monitoring that uses smart sensors and intelligent methods to communicate with farmers through a variety of channels. Farmers will benefit from the real-time farm data (temperature, humidity, soil moisture, UV index, and IR) that allows them to practice smart farming while increasing crop yields and conserving resources. © 2023 IEEE.

关键词： humidity Internet of Things Precision farming predictive analytics remote sensing Sensory computing

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Real-Time Traffic Flow Optimization using Adaptive IoT and data analytics: A Novel DeepStreamNet Model 4

Real-Time Traffic Flow Optimization using Adaptive IoT and D...

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4th international conference on Sustainable Expert Systems, ICSES 2024

作者： Saranya, V.S. Subbarao, Garimidi Balakotaiah, Dega Bhavsingh, Maloth Babu, K. Suresh Dhanikonda, Srinivasa Rao School of Computing Srm Institute of Science and Technology Department of Computing Technologies Chennai603 203 India India Department of Computer Science and Engineering India Ashok: Womens Engineering College Department of Computer Science and Engineering Andhra Pradesh Kurnool India Department of Computer Science and Engineering A.P Narasaraopet India Department of Artificial Intelligence and Data Science Telangana Hyderabad India

ISBN: (纸本)9798331540364

Thisstudy introduces the DeepStreamNet model, an advanced framework for enhancing real-time traffic management in urban environments using adaptive IoT and sophisticated big data analytics. Central to our approach is the integration of convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) units, which synergize with IoT devices to facilitate dynamic adaptation to fluctuating traffic conditions. The model excels in operational performance, achieving a notable accuracy of 94.7% in congestion prediction with an exceptionally low latency of only 45 ms per decision cycle and the capability to process up to 50,000 data points per second. These technical achievements have marked significant improvements over traditional traffic management systems, enhancing traffic flow efficiency and reducing congestion effectively. The results underscore the transformative potential of the DeepStreamNet model in urban traffic management and public safety, offering actionable insights for intelligent transportation systems and setting the stage for more informed urban planning. Looking forward, we suggest extending the application of our model to areas such as logistics and broader smart city initiatives, highlighting its adaptability and broad utility in various urban contexts © 2024 IEEE.

关键词： Convolutional neural networks

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IoT Based Soil Nutrient Monitoring and Analysis System 5

IoT Based Soil Nutrient Monitoring and Analysis System

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5th international conference on IoT Based Control Networks and intelligent Systems, ICICNIS 2024

作者： Sushma, Yarra Lakshmi, Ch Jaya Rajesh, Karra Hemanth, Vanamala Sowmyarao, Ventrapragada VR Siddhartha Engineering College Deemed to Be University Department of EIE A.P Vijayawada India

ISBN: (纸本)9798331518097

Traditional soil nutrient monitoring methods are time-consuming and inefficient, relying on manual sampling and delayed laboratory testing, which hinders timely interventions and leads to resource wastage in agricultural practices. This paper presents an IoT-based soil nutrient monitoring and analysis system designed to address these inefficiencies by enabling real-time data collection and analysis. The proposed system utilizes a network of advanced soil sensors that measure key parameters such as nitrogen, phosphorus, potassium (NPK), moisture, and pH levels. The data is wirelessly transmitted to a cloud platform for continuous processing and analysis, providing real-time insights into soil health. The innovation of this system lies in the integration of IoT sensors, cloud computing, and data analytics, which enables precise and timely decision-making for optimal soil management. Compared to recent soil monitoring systems that either lack real-time capabilities or require costly infrastructure, this IoT-based solution offers a more affordable, scalable, and efficient approach. By offering actionable insights, this system significantly improves crop management, reduces overuse of fertilizers, and enhances resource efficiency, ultimately leading to higher yields and more sustainable agricultural practices. © 2024 IEEE.

关键词： smart agriculture

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intelligent Medication Vending Machine for Enhanced Adherence 2

Intelligent Medication Vending Machine for Enhanced Adherenc...

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2nd international conference on computing and data analytics, ICCDA 2024

作者： Sowndarya, K. Linda Hepsiba, C. Department of Data Science Tiruchirappalli India

ISBN: (纸本)9798331542573

In the field of healthcare, non-adherence to medications is still a big issue, which greatly influences the patients' outcomes and the efficacy of the prescribed medications. This paper proposes a smart solution to ensure patients adhere to health practitioners prescribed medication regimen, the intelligent Medication Vending Machine. The one proposed here has a fairly friendly UI, especially when entering prescription schedules and doses. It also arranges the spatial storage of pills and releases them at appropriate cycles throughout the day. A detailed reminder system incorporated into the system provides timely alarms at the scheduled time and 15 minutes to the appointment at the clinic. In this case, the dissemination of the results is handled via phone and email to the corresponding guardians if the patient has not ingested a medication within 15 minutes of the set time. Moreover, it monitors the quantity of medication stock and sends email alert to the guardians a week before stock exhaustion and followed by the reminder three days to the stock exhaustion and this ensures rapid restocking. By means of the convenient and intuitive GUI, the users can edit prescription details, dosage information, and schedules swiftly. This device is expected to increase the usage of drugs significantly by patients and in the process, improve the patient's condition, therefore, reducing health costs. © 2024 IEEE.

关键词： Vending machines

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