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共 3239 条记录，以下是411-420 订阅

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User and Event Behavior analytics on Differentially Private data for Anomaly Detection 7

User and Event Behavior Analytics on Differentially Private ...

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7th IEEE international conference on Big data Security on Cloud, 7th IEEE international conference on High Performance and smart computing, and 6th IEEE international conference on intelligent data and Security, BigdataSecurity/HPSC/IDS 2021

作者： Rashid, Fatema Miri, Ali Ryerson University Department of Computer Science Toronto Canada

ISBN: (纸本)9781665439275

In today's world of digitization, anomaly detection has become one of the most important issues in our lives. User and Entity Behavior analytics (UEBA) is a security solution for anomaly detection. UEBA minimizes the impact of attacks on data and decreases the risk of privacy breeches by keeping track of normal user and entity behaviors. Organizations need to deploy security control through UEBA in order to achieve security for their data by detecting attacks in their early stages, but the cost of such security control is often out of reach for many small and medium enterprises. One possible solution for such organizations is to outsource UEBA to third parties. However, such an approach can result in disclosure of private data. In this paper, we propose a novel scheme that integrates differential privacy into UEBA. We will show that by introducing noise to the data before publishing it to the third party for anomaly detection, we can ensure that the privacy of the data remains intact, while allowing the third party to preform accurate UEBA analysis. Our experimental results and security analysis will show the validity of our approach. © 2021 IEEE.

关键词： Anomaly detection

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Leveraging Precision Agriculture and GGE Biplot Analysis to Improve Rice Yield in Diverse Agro-Climatic Conditions

Leveraging Precision Agriculture and GGE Biplot Analysis to ...

引用

Innovative computing, intelligent Communication and smart Electrical Systems (ICSES), international conference on

作者： M. Senthil Kumar Midhunchakkaravarthy Computer Science and Engineering Lincoln University College Malaysia Faculty of Computer Science and Multimedia Lincoln University College Malaysia

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543631

GGE Biplot Analysis together with Precision Agriculture Practices is a useful tool for enhancing rice production under diverse environments. It utilizes modern agricultural data science tools for sustainability by addressing the emerging necessity of rice farming, to do so more efficiently and optimally regarding resource usage. The GGE biplot analysis looks into the interaction of crop genotypes with environmental variables that would indicate stable, high-yielding varieties. Precision agriculture techniques are driven by IoT and data analytics to optimize the use of such resources as water and fertilizers, minimizing environmental impact while maintaining productivity. Building on the challenges posed by climate variability and the demand for sustainable farming, the work herein introduces a data-centric framework integrating GGE biplot analysis with precision farming. The potential benefits include water savings of up to 20% and fertilizer application reductions to 15%, achieving those without yield losses. It shows that merging very advanced analytical tools, smart practices in farming, and activities to enhance productivity and sustainability in rice cultivation may indeed be on the right track.

关键词： Precision agriculture Productivity smart agriculture Electric potential Soil Sustainable development Genotypes Water resources Farming Fertilizers

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Distribution Network Fault Location and Isolation based on Edge computing and 5G

Distribution Network Fault Location and Isolation based on E...

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2023 international conference on intelligent Systems, Communications, and Computer Networks, ISCCN 2023

作者： Lei Dai, Ji Yu Zhang, Qiu Yan Ou, Jia Xiang Deng, Yue Dan Zhou, Honbo Pan, Rong Zhen Electric Power Research Institute Guizhou Power Grid Co. Ltd Guiyang China GuiZhou UbiLink Co Ltd Guiyang China Beijing Kyland Co. Ltd Beijing China

ISBN: (纸本)9781510666238

Some of the traditional power distribution network fault location, isolation, and service restoration (FLISR) tasks were conducted with feeder automation (FA), which is part of the distribution automation (DA) system. Existing FA scheme have issues such as long fault processing time, due to centralized decision making. In this paper, a FLISR scheme for distribution network based on edge computing and 5G is proposed. Three key technologies of the scheme are introduced: Edge computing servers with local terminal units (LTU);FLISR algorithms with software-defined control and edge-cloud collaboration;5G integrated with edge computing (MEC). The proposed scheme is the first case with integrated 5G and MEC in DA applications, which can effectively shorten the fault processing time as evidenced by the deployed system s performance. © 2023 SPIE. All rights reserved.

关键词： Electric power distribution

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Cycling analytics for Urban Environments: From Vertical Models to Horizontal Innovation 5th

Cycling Analytics for Urban Environments: From Vertical Mode...

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5th EAI international conference on intelligent Transport Systems (INTSYS)

作者： Carvalho, Carlos Pessoa, Ricardo Jose, Rui Univ Minho Algoritmi Res Ctr Braga Portugal Bosch Car Multimedia Braga Portugal

ISBN: (纸本)9783030976033;9783030976026

The full potential of intelligent Transport Systems (ITS) can only be achieved by combining the efforts and the knowledge of multiple entities. This is also true for the current efforts towards the application of data, communications and services to improve cycling and its integration into general mobility systems. The currently prevailing paradigm is based on dispersed and self-contained custom processes, which fail to promote distributed and open innovation. These models are hard to reproduce, generalize, recombine or improve outside the context for which they were originally implemented. A digital platform strategy might offer a viable and scalable way to support convergence between multiple models and promote their usage as shared references for cycling ecosystems. In this work, we aim to validate our assumptions about the limitations of current development paradigms and analyse the extent to which a platform strategy could offer a fundamentally different approach to address those limitations. To validate the problem and uncover generalisation opportunities, we study 3 cycling mobility models and make an initial analysis of how the general principles of digital platforms could offer an alternative solution for cycling analytics. The results confirm a high potential for horizontal features and outline a set of key design principles for the development of a digital platform strategy for cycling analytics. This should constitute a contribution to inform the development of a new generation of cycling platforms for urban environments.

关键词： Cycling analytics Mobility models Horizontal innovation Urban cycling smart cycling ITS for smart cities: sustainable transportation New trends in ITS

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Integrated IoT Based smart Agriculture Monitoring System

Integrated IoT Based Smart Agriculture Monitoring System

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Mobile computing and Sustainable Informatics (ICMCSI), international conference on

作者： R. Vijaya Saraswathi L. Rahul S. Lokeswar R.Vathsav Varma U. Ajay Computer Science and Engineering VNR Vignana Jyothi Institute of Engineering and Technology Hyderabad India

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522674

The adoption of IoT technology in agriculture is revolutionizing traditional farming, making it a data-driven and resource-efficient field. Proposed paper introduces an IoTbased smart agriculture monitoring system designed to provide farmers with accurate real-time insights for improved crop and resource management. The system incorporates a network of sensors to monitor essential environmental variables like soil moisture and temperature. These signals are processed by a microcontroller and securely transmitted to a cloud platform for advanced analytics. A mobile-friendly application offers actionable insights, notifications, and remote access, facilitating informed decision-making. Built on a Wi-Fi-based infrastructure, the system ensures reliable communication even in areas with inconsistent internet connectivity. Field implementations reveal notable advancements in resource utilization, crop yields, and labor efficiency. Additionally, an embedded AI module forecasts crop prices with 92% accuracy, enabling farmers to optimize sale timings for increased profitability in competitive markets. This comprehensive solution highlights the transformative potential of IoT in fostering sustainable and profitable agricultural practices.

关键词： Temperature sensors Temperature measurement smart agriculture Weather forecasting Real-time systems Resource management Predictive analytics Monitoring intelligent sensors Crop yield

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Facial Video analytics: An intelligent Approach to Heart Rate Estimation Using AI Framework

Facial Video Analytics: An Intelligent Approach to Heart Rat...

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Emerging smart computing and Informatics (ESCI), conference on

作者： Minal C. Toley Raj Gaurav Mishra Vishal Shirsath School of Engineering ADYPU Pune INDIA

The development of remote sensing of vital signs, which use a camera instead of a skin-contact sensor, has improved the measurement environment. Two ideas form the foundation of the camera-based approach: colour and motion. Remote ballistocardiography (RBCG), a motion-based technique, examines the minute movements of the head caused by heartbeat, whereas remote photoplethysmography (RPPG), a color-based technique, measures the colour variation of the face caused by blood reflection. Accurate heart rate monitoring is vital to collecting valuable physical data from human participants. Because of its ease of use and affordability, face video-based heart rate estimate has gained a lot of attention lately. Its precision, dependability, and computing complexity, however, still fall short of expectations. Our goal in this work has been to create a novel deep learning system that use RGB camera to estimate heart rates in real time. The aim of this research topic is to generating an AI algorithm for Heart Rate monitoring from facial video data and integrate it into a real-time heart rate monitoring system. The system will be designed to be user-friendly and easily deployable in various settings such as hospitals, clinics, and homes.

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Health data analytics Using IoT: Transforming Healthcare Management and Treatment Strategies for Improved Patient Outcomes

Health Data Analytics Using IoT: Transforming Healthcare Man...

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Innovative computing, intelligent Communication and smart Electrical Systems (ICSES), international conference on

作者： Dinh Cong Tuan Paravthy Unnikrishnan Bala Dhandayuthapani M. Vennila M. E Choi Sang Long Deepali Rani Sahoo Faculty of Communication Dai Nam University Vietnam Department of Striroga and Prasuti Tantra (Gynaecology and Obstetrics) Amrita School of Ayurveda Amrita Vishwa Vidyapeetham Amritapuri Department of IT College of Computing and Information Sciences University of Technology and Applied Sciences Shinas Campus Oman Department of Robotics and Automation Karpaga Vinayaga College of Engineering and Technology Chengalpattu Faculty of Business Raffles University Malaysia Symbiosis Law School Noida Symbiosis International (Deemed University) Pune India

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543631

The integration of Web of Things (IoT) innovation within the healthcare segment has revolutionized conventional healthcare administration and treatment procedures, driving progressed quiet results. This paper looks at the transformative effect of well-being information analytics utilizing IoT in upgrading healthcare administrations, optimizing understanding care, and advancing preventive measures. The paper analyzes the key components and applications of IoT in healthcare, emphasizing its part in information collection, real-time observation, and examination of understanding imperative signs, action levels, and pharmaceutical adherence. With the help of IoT-enabled gadgets such as wearables, sensors, and keen checking frameworks, healthcare experts can assemble comprehensive, real-time persistent information, encouraging early discovery and opportune mediation for basic well-being issues. Besides, the utilization of IoT in well-being information analytics empowers the improvement of personalized treatment plans custom-fitted to a person's persistent needs, cultivating a patient-centric approach to healthcare conveyance. By leveraging machine learning calculations and prescient analytics, healthcare suppliers can expect potential well-being complications, in this manner minimizing the chance of antagonistic occasions and clinic readmissions. In addition, the execution of IoT-based healthcare arrangements advances further understanding and observing, empowering healthcare suppliers to offer ceaseless, personalized care past conventional healthcare settings.

关键词： Technological innovation data analysis Medical services Machine learning Real-time systems Internet of Things Wearable devices Mediation Wearable sensors Pharmaceuticals

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Utilization Of data analytics in Analysing Audio and Crowd Video Content

Utilization Of Data Analytics in Analysing Audio and Crowd V...

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international conference on Advanced computing and Communication Systems (ICACCS)

作者： Anshy Singh Manoj Kumar Aditi Saxena Dept. of Computer Engineering and Applications GLA University Mathura India Dept. of Electronics and Communication Engineering GLA University Mathura India

The development of growing variety of useful sources of data, the creation of a number of methods for machine learning, and the development of web of things and advanced analytics enable people and policy maker with new tools for predictive services however an interconnected system also has a deficit that will help in reducing building costs and allow new forms of facilities this is a case in point for an applied big data analysis framework of things and smart grid for web applications, this paper presents a summary and description of big data and the internet of the creation of subjects .This paper provides a comparative analysis of audio and crowd video content an intelligent grid case study that shows the high standards of big data analysis structure .The evaluation processing, analysis and reporting for comprehension and optimization gather and analyzes, of learner data in their contexts and in the condition in which it is generated.

关键词： Structured Query Language Costs smart buildings smart cities Soft sensors Machine learning Interconnected systems

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An intelligent Occupancy Detection System for smart Tourism based on RFID Passive Tag Antenna Array and Random Forest 13

An Intelligent Occupancy Detection System for Smart Tourism ...

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13th IEEE international conference on RFID Technology and Applications (IEEE RFID-TA)

作者： Jiang, Chao Yu Wang, Bo Yu Tai, Tai Oi Tam, Kam Weng Chen, Long Chio, Chi Hou Teng, Cheng Kong, Ngai Univ Macau Macau Peoples R China Laxcen Technol Zhuhai Ltd Zhuhai Peoples R China Crosstech Innovat Grp Ltd Guangzhou Peoples R China

ISBN: (纸本)9798350333534

This paper presents a passive UHF RFID (Ultra High-Frequency Radio Identification) tag array-based occupancy detection of smart tourism using the AI (Artificial Intelligence) method of (RF) Random Forest. To illustrate the randomness of occupancy in different scenarios, this paper compromises UHF RFID tag array sensing and AI computing into an open platform for occupancy detection in different scenarios. Our proposed system aims at predicting population density classification from 0% to 75%. To demonstrate the feasibility of our approach, we conducted a small-scale experiment using a carpet embedded with nine passive UHF RFID tags on average. We deployed two different tag placement patterns, Circular and Square, to assess their impact on classification accuracy. During the experiment, one person walked on the carpet, covering approximately 25% of its area. We assigned each participant to a corresponding occupancy class based on the carpet percentage covered in 4 classes, corresponding to 0, 1, 2, and 3 people walking on the carpet, e.g., class 1 represents 0 individuals, class 2 represents one person, and so on one at a time. We could accurately classify each participant into the appropriate occupancy class by analyzing the data collected from the RFID tags. The employed AI method of RF achieves high classification accuracy of 91.82%, which is much higher than other common classifiers of SVM and BP Neural Network.

关键词： Occupancy Detection RFID Classification RSSI tag smart Tourism AI

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Federated Learning With Dynamic Staleness Correction for Privacy Protection in Vehicular Networks 23

Federated Learning With Dynamic Staleness Correction for Pri...

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23rd IEEE international conference on High Performance computing and Communications, 7th IEEE international conference on data Science and Systems, 19th IEEE international conference on smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big data Systems and Applications, HPCC-DSS-smartCity-DependSys 2021

作者： Liu, Jiajia Wu, Hao Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing China School of Electronics and Information Engineering Beijing Jiaotong University Beijing China Beijing Jiaotong University Frontiers Science Center for Smart High-speed Railway System Beijing China

ISBN: (纸本)9781665494571

Edge intelligence combines mobile edge computing(MEC) with artificial intelligence(AI), which has great potential for improving the security and efficiency of data-driven intelligent transportation systems (ITS) and emerging Internet Of Vehicles (IOV) services. However, when big data and AI empower ITS, the information security issue in vehicular networks needs to be paid more attention. In order to protect the privacy and security of vehicular training data, we propose a privacy protection federated learning scheme with staleness asynchronous update to overcome the differences caused by vehicle heterogeneity. Moreover, unlike the traditional weighted average on the server side only by the number of samples, our solution introduces dynamic time weights according to the calculation and communication capabilities of different vehicles, to make full use of the previously trained local model. The proposed scheme is able to reduce traffic load of the network and improve learning performance while enhancing security and privacy. Experiment results demonstrate that in terms of communication cost and model accuracy, the performance of the proposed asynchronous federated learning is better than the benchmark algorithm, and it also achieves good performance under NIID data. © 2021 IEEE.

关键词： Privacy data privacy Costs smart cities Training data Telecommunication traffic Collaborative work

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