2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)最新文献_第7页

Leveraging IoT solutions as a base for development of the agriculture advisory services 利用物联网解决方案作为发展农业咨询服务的基础

2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS) Pub Date : 2022-08-01 DOI: 10.1109/COINS54846.2022.9854950

Szymon Mueller, M. Plóciennik, Maciej Zacharczuk, Adam Fojud, Michal Blaszczak, Alicja Laskowska, Raúl Palma, M. Jakubowska, Andrzej Wojtowicz

引用次数: 1

ScreenCoin: A Blockchain-Enabled Decentralized Ad Network ScreenCoin:一个支持区块链的分散广告网络

2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS) Pub Date : 2022-08-01 DOI: 10.1109/COINS54846.2022.9854976

Malcolm Smith, Alexander Castro, M. Rahouti, M. Ayyash, Lesther Santana

引用次数: 2

Analyzing the Latency of QUIC over an IoT Gateway 物联网网关QUIC时延分析

2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS) Pub Date : 2022-08-01 DOI: 10.1109/COINS54846.2022.9854951

Ahmed Alqattaa, Daniel Loebenberger, Lukas Moeges

{"title":"Analyzing the Latency of QUIC over an IoT Gateway","authors":"Ahmed Alqattaa, Daniel Loebenberger, Lukas Moeges","doi":"10.1109/COINS54846.2022.9854951","DOIUrl":"https://doi.org/10.1109/COINS54846.2022.9854951","url":null,"abstract":"This paper presents the analysis of an Internet of Things (IoT) cryptographic gateway which sits in-between attached IoT devices and the cloud. The gateway communicates with the cloud using the Message Queuing Telemetry Transport (MQTT) protocol over a Transport Layer Security (TLS) 1.3 connection employing up-to-date asymmetric cryptography at a high security level. On the other side, the gateway allows the IoT devices to connect to the network employing MQTT over the Quick UDP Internet Connections (QUIC) protocol, whereby QUIC has been recently standardized by the IETF.First, we measure the latency of MQTT over QUIC and TCP/TLS without the gateway, once with a Full-Handshake (FH) mode and another time with a Zero-Round Trip Time (0-RTT) mode. Then, we compare the time taken by QUIC with TCP/TLS, in case of a FH with both and in case of a 0-RTT after the first FH connection in QUIC, when using the gateway.This paper shows that MQTT over QUIC reduces the latency of the connection compared to MQTT over TCP/TLS in almost all cases considerably. Since on transport layer the gateway is fully transparent, the (logical) TLS 1.3 connection in QUIC between the IoT devices and the gateway saves time on the IoT devices without compromising security.","PeriodicalId":187055,"journal":{"name":"2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134021543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Developing Object Detection Models for Camera Applications in Smart Poultry Farms 开发智能家禽养殖场中相机应用的目标检测模型

2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS) Pub Date : 2022-08-01 DOI: 10.1109/COINS54846.2022.9854975

Stevan Cakic, Tomo Popović, S. Krco, Daliborka Nedic, Dejan Babic

{"title":"Developing Object Detection Models for Camera Applications in Smart Poultry Farms","authors":"Stevan Cakic, Tomo Popović, S. Krco, Daliborka Nedic, Dejan Babic","doi":"10.1109/COINS54846.2022.9854975","DOIUrl":"https://doi.org/10.1109/COINS54846.2022.9854975","url":null,"abstract":"This paper proposes the use of high-performance computing and deep learning to create prediction models that can be deployed as a part of smart agriculture solutions in the poultry sector. The idea is to create object detection models that can be ported onto edge devices equipped with camera sensors for the use in Internet of Things systems for poultry farms. The object detection prediction models could be used to create smart camera sensors that could evolve into sensors for counting chickens or detecting dead ones. Such camera sensor kits could become a part of digital poultry farm management systems in shortly. The paper discusses the approach to the development and selection of machine learning and computational tools needed for this process. Initial results, based on the use of Faster R-CNN network and high-performance computing are presented together with the metrics used in the evaluation process. The achieved accuracy is satisfactory and allows for easy counting of chickens. More experimentation is needed with network model selection and training configurations to increase the accuracy and make the prediction useful for developing a dead chicken detector.","PeriodicalId":187055,"journal":{"name":"2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","volume":"48 30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117353704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

FPGA-based Deep-Learning Accelerators for Energy Efficient Motor Imagery EEG classification

2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS) Pub Date : 2022-08-01 DOI: 10.1109/COINS54846.2022.9854985

Daniel Flood, Neethu Robinson, Shanker Shreejith

{"title":"FPGA-based Deep-Learning Accelerators for Energy Efficient Motor Imagery EEG classification","authors":"Daniel Flood, Neethu Robinson, Shanker Shreejith","doi":"10.1109/COINS54846.2022.9854985","DOIUrl":"https://doi.org/10.1109/COINS54846.2022.9854985","url":null,"abstract":"In recent years, Deep Learning has emerged as a powerful framework for analysing and decoding bio-signals like Electroencephalography (EEG) with applications in brain computer interfaces (BCI) and motor control. Deep convolutional neural networks have shown to be highly effective in decoding BCI signals for applications like two-class motor imagery decoding. Their deployment in real-time applications, however, requires highly parallel and capable computing platforms like GPUs to achieve high-speed inference, consuming a large amount of energy. In this paper, we explore a custom deep learning accelerator on an off-the-shelf hybrid FPGA device to achieve similar inference performance at a fraction of the energy consumption. We evaluate different optimisations at bit-level, data-path and training using a state-of-the-art deep convolutional neural network as our baseline model to arrive at our custom precision quantised deep learning model, which is implemented using the FINN compiler from Xilinx. The accelerator, deployed on a Xilinx Zynq Ultrascale+ FPGA, achieves a significant reduction in power consumption (≈ 17×), sub 2 ms decoding latency and a near-identical decoding accuracy (statistically insignificant reduction of 2.5% average) as the reported baseline subject-specific classification accuracy on an N (= 54) subject motor imagery EEG (MI-EEG) dataset compared to the Deep CNN model on GPU, making our approach more appealing for low-power real-time BCI applications. Furthermore, this design approach is transferable to other deep learning models reported in BCI research, paving the way for novel applications of real-time portable BCI systems.","PeriodicalId":187055,"journal":{"name":"2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127449874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-Objective Task Allocation for Dynamic IoT Networks 动态物联网网络的多目标任务分配

2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS) Pub Date : 2022-08-01 DOI: 10.1109/COINS54846.2022.9854949

Dominik Weikert, Christoph Steup, Sanaz Mostaghim

引用次数: 2

Sensitive information protection in blockchain-based supply-chain management for aerospace 基于区块链的航空航天供应链管理中的敏感信息保护

2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS) Pub Date : 2022-08-01 DOI: 10.1109/COINS54846.2022.9854974

Davide Martintoni, V. Senni, Ernesto Gomez Marin, Antonio Javier Cabrera Gutiérrez

引用次数: 4

An Accuracy-Driven Compression Methodology to Derive Efficient Codebook-Based CNNs 一种精度驱动的基于码本的高效cnn压缩方法

2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS) Pub Date : 2022-08-01 DOI: 10.1109/COINS54846.2022.9854986

Flavio Ponzina, Miguel Peón-Quirós, G. Ansaloni, David Atienza Alonso

引用次数: 0

How centralized is decentralized? Comparison of wealth distribution in coins and tokens 去中心化是如何实现的?硬币和代币的财富分配比较

2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS) Pub Date : 2022-07-04 DOI: 10.1109/COINS54846.2022.9854972

Bartosz Ku'smierz, R. Overko

{"title":"How centralized is decentralized? Comparison of wealth distribution in coins and tokens","authors":"Bartosz Ku'smierz, R. Overko","doi":"10.1109/COINS54846.2022.9854972","DOIUrl":"https://doi.org/10.1109/COINS54846.2022.9854972","url":null,"abstract":"Rapidly growing distributed ledger technologies (DLTs) have recently received attention among researchers in both industry and academia. While a lot of existing analysis (mainly) of the Bitcoin and Ethereum networks is available, the lack of measurements for other crypto projects is observed. This article addresses questions about tokenomics and wealth distributions in cryptocurrencies. We analyze the time-dependent statistical properties of top cryptocurrency holders for 14 different distributed ledger projects. The provided metrics include approximated Zipf coefficient, Shannon entropy, Gini coefficient, and Nakamoto coefficient. We show that there are quantitative differences between the coins (cryptocurrencies operating on their own independent network) and tokens (which operate on top of a smart contract platform). Presented results show that coins and tokens have different values of approximated Zipf coefficient and centralization levels. This work is relevant for DLTs as it might be useful in modeling and improving the committee selection process, especially in decentralized autonomous organizations (DAOs) and delegated proof-of-stake (DPoS) blockchains.","PeriodicalId":187055,"journal":{"name":"2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128970928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Implementation of Ethereum Accounts and Transactions on Embedded IoT Devices 嵌入式物联网设备上以太坊账户和交易的实现

2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS) Pub Date : 2022-06-29 DOI: 10.1109/COINS54846.2022.9855005

Giulia Rafaiani, P. Santini, M. Baldi, F. Chiaraluce

{"title":"Implementation of Ethereum Accounts and Transactions on Embedded IoT Devices","authors":"Giulia Rafaiani, P. Santini, M. Baldi, F. Chiaraluce","doi":"10.1109/COINS54846.2022.9855005","DOIUrl":"https://doi.org/10.1109/COINS54846.2022.9855005","url":null,"abstract":"The growing interest in Internet of Things (IoT) and Industrial IoT (IIoT) poses the challenge of finding robust solutions for the certification and notarization of data produced and collected by embedded devices. The blockchain and distributed ledger technologies represent a promising solution to address these issues, but rise other questions, for example regarding their practical feasibility. In fact, IoT devices have limited resources and, consequently, may not be able to easily perform all the operations required to participate in a blockchain. In this paper we propose a minimal architecture to allow IoT devices performing data certification and notarization on the Ethereum blockchain. We develop a hardware-software platform through which a lightweight device (e.g., an IoT sensor), holding a secret key and the associated public address, produces signed transactions, which are then submitted to the blockchain network. This guarantees data integrity and authenticity and, on the other hand, minimizes the computational burden on the lightweight device. To show the practicality of the proposed approach, we report and discuss the results of benchmarks performed on ARM Cortex-M4 hardware architectures, sending transactions over the Ropsten testnet. Our results show that all the necessary operations can be performed with small latency, thus proving that an IoT device can directly interact with the blockchain, without apparent bottlenecks.","PeriodicalId":187055,"journal":{"name":"2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129473324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1