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Analysis of Factors Influencing the Buyer Preferences on Goods and Services: Comparing E-Commerce and Retail Stores 6

Analysis of Factors Influencing the Buyer Preferences on Goo...

引用

6th international conference on Cybernetics and Intelligent System, ICORIS 2024

作者： Siek, Michael Tadjoedin, Pasha Business Information Systems Program Information Systems Department Faculty of Computing and Media Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9798331539603

E-commerce is a type of businesses or individuals doing transactions through the internet, which continues to be improved to perform its tasks with more features and facilities compared to physical and brick and mortar stores. Customers is getting used to shop their wanted products in e-commerce due to convenient, practical, and useful. Specifically, during the Covid-19 pandemic, purchasing goods via e-commerce without physical contact and during lockdowns is most preferable. the research aimed at finding the crucial factors influencing the buyer preferences on goods and services by comparing ecommerce and retail stores using quantitative methods. A modified research framework was developed by considering the existing technology acceptance model and other factors related to purchasing cloths and foods. the collected response data was analyzed and modelled using structural equation model with partial least square algorithm. the modelling results showed that most assessed responses indicate a positive perception of ecommerce. the factors of buyer preference on e-commerce are mainly due to faster product searching with competitive pricing. the research results provide important information and strategies for businesses on how to sell particular products to the customers. © 2024 IEEE.

关键词： Marketplaces

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Research on distributed Multi-Dimensional Intelligent Device for Intelligent Cable Well Intrusion Detection 6

Research on Distributed Multi-Dimensional Intelligent Device...

引用

2023 IEEE 6th international conference on Information Systems and Computer Aided Education, ICISCAE 2023

作者： Zhang, Wenwen Zhang, Xinyang Wang, Tao Li, Kaipeng State Grid Zhejiang Electric Power Co. Ltd. Xiangshan County Power Supply Company Ningbo China Xiangshan Electric Power Industry Co. Ltd Ningbo China

ISBN: (纸本)9798350313444

this paper proposes an intelligent monitoring system for 110 kV power cable pipe wells. the system is mainly composed of intelligent sensing system, monitoring host system and real-time monitoring terminal. the LoRa technology is used to communicate wirelessly with the Inoue monitoring host. Using TMS320F2812 as monitoring chip, intelligent monitoring is realized. the remote monitoring equipment is monitored by the internet of things network, and the wireless access to the remote monitoring equipment is realized. the practice proves that the input of this system greatly improves the emergency response ability of underground cable and effectively improves the running condition of the site. © 2023 IEEE.

关键词： cable tube well intelligent perception internet of things intrusion detection Power cable

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Latency-Aware Placement of Stream Processing Operators

Latency-Aware Placement of Stream Processing Operators

引用

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

作者： Ecker, Raphael Karagiannis, Vasileios Sober, Michael Ebrahimi, Elmira Schulte, Stefan TU Wien Vienna Austria Austrian Inst Technol Ctr Digital Safety & Secur Vienna Austria TU Hamburg Christian Doppler Lab Blockchain Technol Internet Hamburg Germany

ISBN: (纸本)9783031506833;9783031506840

the rise of the internet of things and Fog computing has increased substantially the number of interconnected devices at the edge of the network. As a result, a large amount of computations is now performed in the fog generating vast amounts of data. To process this data in near real time, stream processing is typically employed due to its efficiency in handling continuous streams of information in a scalable manner. However, most stream processing approaches do not consider the underlying network devices as candidate resources for processing data. Moreover, many existing works do not take into account the incurred network latency of performing computations on multiple devices in a distributed way. Consequently, the fog computing resources may not be fully exploited by existing stream processing approaches. To avoid this, we formulate an optimization problem for utilizing the existing fog resources, and we design heuristics for solving this problem efficiently. Furthermore, we integrate our heuristics into Apache Storm, and we perform experiments that show latency-related benefits compared to alternatives.

关键词： Stream Processing Fog computing Edge computing internet of things Apache Storm

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Faster Convergence of Adaptive Data Rate in Dynamic LoRa-based IoT Network Applications 25

Faster Convergence of Adaptive Data Rate in Dynamic LoRa-bas...

引用

26th international conference on distributed computing and Networking, ICDCN 2025

作者： Gorrela, Alekhya Choudhury, Nikumani BITS Pilani Hyderabad Hyderabad India

ISBN: (纸本)9798400710629

Low Power Wide Area Network (LPWAN) technology has gained popularity across various internet-of-things (IoT) applications. Among these, the Long Range Wide Area Network (LoRaWAN), primarily used in private outdoor settings, has significantly progressed from conventional wireless sensor networks (WSN) to IoT applications. LoRaWAN implementations follow the fundamental ALOHA protocols, leading to substantial packet loss and limited end device support. this problem increases significantly with dense networks and dynamic channel traffic conditions. the Adaptive Data Rate (ADR) is a key feature of LoRaWAN that allows sensor devices in such IoT applications to adjust the data rate dynamically based on channel conditions. this ensures robust communication and helps increase the sensor device's battery longevity. An enhanced channel access mechanism is necessary to improve efficiency and robustness to solve these issues in congested network situations. In this paper, we propose the TrafFaCon algorithm, which provides a modified Listen-Before-Talk (LBT) mechanism that estimates the channel traffic and leverages Channel Activity Detection (CAD) to assign a wait/transmit flag for end devices based on situations with high traffic density. It also aids in faster convergence by reducing collisions and optimizing transmission timing. Our results show that the proposed methodology significantly improves channel efficiency, utilization, and convergence period. © 2025 Copyright held by the owner/author(s).

关键词： internet of things

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Research on internet of things Signals Acquisition and Processing based on Edge Computation 5

Research on Internet of Things Signals Acquisition and Proce...

引用

5th international conference on Computer Engineering and Intelligent Control, ICCEIC 2024

作者： Zhang, Xiaolong Qiu, Wenheng Yang, Huaping Hou, Aohua College of Electrical Engineering and New Energy China Three Gorges University Yichang Hubei443002 China Hubei University of Arts and Sciences Faculty of Automotive and Traffic Engineering Xiangyang Hubei441053 China

ISBN: (纸本)9798331507992

the proliferation of internet of things (IoT) devices has led to the generation of vast quantities of data, placing considerable strain on conventional cloud computing infrastructure. Edge computing has emerged as a viable solution to address this challenge. In this study, we propose an internet of things (IoT) signal processing framework that is combined with distributed edge nodes. the objective is to improve data transmission efficiency and real-time performance. Firstly, in consideration of the constrained resources of edge devices, we have devised lightweight preprocessing algorithms, including frequency domain filtering based on Fourier transform and a denoising algorithm based on wavelet transform, with the objective of reducing the noise and redundant information present in the original signal. Subsequently, the adaptive compressed sensing technology was employed to compress the preprocessed signal, which resulted in a notable reduction in the bandwidth requirement for data transmission. Subsequently, in order to fully utilise the computing capabilities of edge nodes, we introduce a multi-task learning collaborative computing model. the model permits the sharing of computing tasks between multiple edge nodes, facilitates data collaboration between edge nodes through federated learning, and reduces computing redundancy and communication overhead. the experimental phase employs the Google Edge TPU Dataset to evaluate the dataset pertinent to the internet of things. the results indicate that the proposed methodology exhibits a notable enhancement in data processing latency and transmission efficacy in comparison to the conventional approach. © 2024 IEEE.

关键词： Collaborative computing Edge Computation internet of things Signal Processing

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Minimize Fog Nodes in Double-layer distributed Fog Radio Access Networks 6

Minimize Fog Nodes in Double-layer Distributed Fog Radio Acc...

引用

6th IEEE Advanced Information technology, Electronic and Automation Control conference (IEEE IAEAC)

作者： Cheng, Yanrong Qian, Hongyan Nanjing Univ Aeronaut & Astronaut Coll Comp Sci & Technol Nanjing Peoples R China

ISBN: (数字)9781665458641

ISBN: (纸本)9781665458641

Compared with cloud computing, the architecture adopted by fog computing is more distributed and closer to the edge of the network. Fog computing concentrates data, data processing, and applications in devices at the edge of the network, instead of storing almost all of them in the cloud like cloud computing. Fog computing is implemented as an intermediate platform between terminal equipment and cloud computing data centers. the recent popularity of the internet of things (IoT) has made fog computing a necessary condition for processing various devices. It has been recognized as an important platform for providing efficient, location-aware, and near-edge cloud services. In order to shorten the transmission delay of end-user equipment requesting data, we adopt the idea of greedy algorithm to increase the number of fog nodes in the fog layer. By increasing the number of fog nodes, the storage pressure of each fog node is alleviated, while the transmission delay is shortened, and the data transmission efficiency in the entire cloud center is greatly improved.

关键词： Fog computing Fog node D2D

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Enhancing Visual Inertial Odometry Performance using Deep Learning-based Sensor Fusion 17

Enhancing Visual Inertial Odometry Performance using Deep Le...

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IEEE Congress on Cybermatics: 17th IEEE international conference on internet of things, ithings 2024, 20th IEEE international conference on Green computing and Communications, GreenCom 2024, 17th IEEE international conference on Cyber, Physical and Social computing, CPSCom 2024, 10th IEEE international conference on Smart Data, SmartData 2024

作者： Doorshi, Raoof Saleem, Hajira Malekian, Reza Malmö University Department of Computer Science and Media Technology Malmö20506 Sweden Malmö University Internet of Things and People Research Centre Malmö20506 Sweden

ISBN: (纸本)9798350351637

Odometry estimation plays a key role in facilitating autonomous navigation systems. While significant consideration has been devoted to research on monocular odometry estimation, sensor fusion techniques for Stereo Visual Odometry (SVO) have been relatively neglected due to their demanding computational requirements, posing practical challenges. However, recent advancements in hardware, particularly the integration of CPUs with dedicated artificial intelligence units, have alleviated these concerns. In this paper, we investigate the efficacy of attention mechanisms and the incorporation of stereo input in comparison to monocular odometry, aiming to enhance the performance of SVO. We tested two different types of attention mechanisms, i.e., Triplet Attention (TA) and Convolutional Block Attention Module (CBAM), and their fusion in two stages Early and Late. Our results show that the fusion of the second camera improves the performance of the model, as well as early fusion with TA provided the best results. © 2024 IEEE.

关键词： Deep learning

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SNN Based Neuromorphic computing Towards Healthcare Applications 6th

SNN Based Neuromorphic Computing Towards Healthcare Applicat...

引用

6th IFIP international conference on internet of things, IFIP IoT 2023

作者： Maji, Prasenjit Patra, Ramapati Dhibar, Kunal Mondal, Hemanta Kumar Department of CSD BCREC Durgapur Durgapur India Department of ECE NIT Durgapur Durgapur India Department of CSE BCET Durgapur Durgapur India

ISBN: (纸本)9783031458774

the diagnosis, treatment, and prevention of diseases may be revolutionized by integrating neuromorphic computing, artificial intelligence (AI), and machine learning (ML) into medical services. A novel method of processing complex data that more effectively and quickly mimics how the human brain works is called neuromorphic computing. this paper provides an overview of neuromorphic computing and its uses in AI and ML-based healthcare. We talk about the advantages and disadvantages of using these technologies as well as how it helps to accelerate the entire diagnostic procedure. We also provide case studies of how neuromorphic applications have been successfully used in the medical field to diagnose and predict diseases. Additionally, we provide the medical and healthcare industries with enhanced Spiking Neural network application results with up to 98.5% accuracy. © 2024, IFIP international Federation for Information Processing.

关键词： Neural networks

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Assessment and Analysis of IoT Protocol Effectiveness in Data Exfiltration Scenario 20

Assessment and Analysis of IoT Protocol Effectiveness in Dat...

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20th Annual international conference on distributed computing in Smart Systems and the internet of things, DCOSS-IoT 2024

作者： Adesanya, Olanrewaju Mueez Moradpoor, Naghmeh Maglaras, Leandros Lim, Ik Soo Amine Ferrag, Mohamed University of Greenwich School of Computing and Mathematical Sciences London United Kingdom Edinburgh Napier University School of Computing Engineering and the Built Environment Edinburgh United Kingdom Technology Innovation Institute Artificial Intelligence and Digital Science Research Center Masdar Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350369441

the rapid growth of internet of things technology has introduced an era of numerous interconnected devices, transforming the communication with the physical world. However, the security and privacy of the data generated and stored on these devices have become significant concerns due to the potential risks associated with unauthorized access and data exfiltration. this paper presents a comprehensive study on the characterization and evaluation of IoT protocols for data exfiltration, with a focus on Message Queuing Telemetry Transport versions 3.1.1 and 5.0, Constrained Application Protocol version 1.0, and Websocket, owing to their widespread adoption and diverse characteristics. these protocols are chosen to meet the constraints of IoT devices and networks, where minimal bandwidth utilization and low power consumption are crucial. We employed a multifaceted methodology, incorporating a comprehensive literature review and the Chiton data encapsulation and exfiltration software tool, to assess the security features, vulnerabilities, and performance metrics of these protocols for data exfiltration. Performance evaluations on the three selected protocols were conducted using a live Client-Server network. A laptop served as the server for exfiltrated data collection, while a Raspberry Pi 3 device acted as the IoT Client Publisher. the evaluation included Wireshark as a network protocol analyser and the enhancement of the Chiton Software Tool with custom codes to encapsulate and exfiltrate data within the IoT protocol messages, empirically measuring the selected protocols' performance, including overhead, latency, and throughput for different data exfiltration scenarios, providing a versatile platform for protocol evaluation. Comparative analysis revealed the strengths and weaknesses of MQTT, CoAP, and Websocket in various data exfiltration scenarios, facilitating the selection of MQTT and Websocket over the CoAP protocol for IoT applications. Lastly, ideas and recommend

关键词： Application programs

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Multiple Early-Exits Strategy for distributed Deep Neural Network Inference 19

Multiple Early-Exits Strategy for Distributed Deep Neural Ne...

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19th Annual international conference on distributed computing in Smart Systems and the internet of things, DCOSS-IoT 2023

作者： Sbai, Marion Trigoni, Niki Markham, Andrew University of Oxford Department of Computer Science Oxford United Kingdom

ISBN: (纸本)9798350346497

Existing work on multi-camera network mainly focused on centralized systems, the role of the cameras being limited to capture images and send them to the cloud. However, this approach is impractical when the network connection is limited or variable. Our methodology distributes DNN inference across multiple edge clients and the cloud using early-exits and bottlenecks for time and accuracy requirements. In limited communication scenarios like LoRa, our solution improves average latency by 80 % compared to traditional cloud solutions. © 2023 IEEE.

关键词： Deep neural networks

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