2021 IEEE International Conference on Smart Computing (SMARTCOMP)最新文献

SMARTCOMP 2021 Technical Program Committee and Additional Reviewers SMARTCOMP 2021技术计划委员会和额外评审员

2021 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2021-08-01 DOI: 10.1109/smartcomp52413.2021.00008

引用次数: 0

Identifying Water Consumption Patterns in Education Buildings Before, During and After COVID-19 Lockdown Periods 确定在COVID-19封锁期间之前，期间和之后的教育建筑用水模式

2021 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2021-08-01 DOI: 10.1109/SMARTCOMP52413.2021.00069

Marco Zecchini, Alessandra Anna Griesi, I. Chatzigiannakis, Dimitrios Amaxilatis, O. Akrivopoulos

引用次数: 1

A Hybrid Recommender System for Cultural Heritage Promotion 文化遗产推广的混合推荐系统

2021 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2021-08-01 DOI: 10.1109/SMARTCOMP52413.2021.00048

V. Agate, Federico Concone, S. Gaglio, A. Giammanco

引用次数: 0

Speeding Up Encryption on IoT Devices Using Homomorphic Encryption 使用同态加密加速物联网设备的加密

2021 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2021-08-01 DOI: 10.1109/SMARTCOMP52413.2021.00059

Marin Matsumoto, M. Oguchi

{"title":"Speeding Up Encryption on IoT Devices Using Homomorphic Encryption","authors":"Marin Matsumoto, M. Oguchi","doi":"10.1109/SMARTCOMP52413.2021.00059","DOIUrl":"https://doi.org/10.1109/SMARTCOMP52413.2021.00059","url":null,"abstract":"What do we need to do to protect our personal information? IoT devices such as smartphones, smart watches, and home appliances are widespread. Encryption is required not only to prevent eavesdropping on communications but also to prevent information leakage from cloud services due to unauthorized access. Therefore, attention is being paid to fully homomorphic encryption (FHE) that allows addition and multiplication between ciphertexts. However, FHE with this convenient function has a drawback that the encryption requires huge volume of calculation and the ciphertext is large. Therefore, if FHE is used on a device with limited computational resources such as an IoT device, the load on the IoT device will be too heavy. In this research, we propose a system that can safely and effectively utilize data without imposing a load on IoT devices. In this system, somewhat homomorphic encryption (SHE), which is a lightweight cryptosystem compared with FHE, is combined with FHE. The results of the experiment confirmed that the load on the IoT device can be reduced to approximately 1/1400 compared to load of the system from previous research.","PeriodicalId":330785,"journal":{"name":"2021 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130194826","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: 5

Message from the General Co-Chairs 一般共同主席的致辞

2021 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2021-08-01 DOI: 10.1109/cgo.2005.20

引用次数: 0

A Smart System for Personal Protective Equipment Detection in Industrial Environments Based on Deep Learning 基于深度学习的工业环境下个人防护装备智能检测系统

2021 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2021-08-01 DOI: 10.1109/SMARTCOMP52413.2021.00051

G. Gallo, F. D. Rienzo, P. Ducange, V. Ferrari, A. Tognetti, C. Vallati

{"title":"A Smart System for Personal Protective Equipment Detection in Industrial Environments Based on Deep Learning","authors":"G. Gallo, F. D. Rienzo, P. Ducange, V. Ferrari, A. Tognetti, C. Vallati","doi":"10.1109/SMARTCOMP52413.2021.00051","DOIUrl":"https://doi.org/10.1109/SMARTCOMP52413.2021.00051","url":null,"abstract":"The adoption of real-time object detection systems via video streaming analysis is currently exploited in several contexts, from security monitoring to safety prevention. In industrial environments, proper usage of Personal Protective Equipment (PPE) is paramount to ensure workers’ safety. However, the use of some types of PPE, such as helmets, is often neglected by workers, especially in indoor areas. Thus, in order to reduce the risks of accidents, real-time video streaming-based monitoring systems may be used to monitor areas in which workers operate and alert them not to wear PPEs via acoustic alarms or visual signals. In case of a remote analysis, there are potential issues related to the high rate of data streams to be transported and analyzed and workers’ privacy. In this work, we propose an embedded smart system for real-time PPE detection based on video streaming analysis and deep learning models. We discuss the deployment of different versions of the YOLOv4 network fine-tuned using a public PPE dataset. In the end, we assess the performance of the proposed system in terms of accuracy and latency and of the overall PPE detection procedure.","PeriodicalId":330785,"journal":{"name":"2021 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130757947","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: 6

Simulation and Test of UAV Tasks With Resource-Constrained Hardware in the Loop 资源受限硬件在环无人机任务仿真与测试

2021 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2021-08-01 DOI: 10.1109/SMARTCOMP52413.2021.00071

Andrea Augello, S. Gaglio, G. Re, D. Peri

引用次数: 1

CARTMAN: Complex Activity Recognition Using Topic Models for Feature Generation from Wearable Sensor Data 从可穿戴传感器数据中使用主题模型生成特征的复杂活动识别

2021 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2021-08-01 DOI: 10.1109/SMARTCOMP52413.2021.00026

kar 2402565399 ku, Walter Gerych, Luke Buquicchio, Abdulaziz Alajaji, E. Agu, Elke A. Rundensteiner

{"title":"CARTMAN: Complex Activity Recognition Using Topic Models for Feature Generation from Wearable Sensor Data","authors":"kar 2402565399 ku, Walter Gerych, Luke Buquicchio, Abdulaziz Alajaji, E. Agu, Elke A. Rundensteiner","doi":"10.1109/SMARTCOMP52413.2021.00026","DOIUrl":"https://doi.org/10.1109/SMARTCOMP52413.2021.00026","url":null,"abstract":"The recognition of complex activities such as \"having dinner\" or \"cooking\" from wearable sensor data is an important problem in various healthcare, security and context-aware mobile and ubiquitous computing applications. In contrast to simple activities such as walking that involve single, indivisible repeated actions, recognizing complex activities such as \"having dinner\" is a harder sub-problem that may be composed of multiple interleaved or concurrent simple activities with different orderings each time. Most of prior work has focused on recognizing simple activities, used hand-crafted features, or did not perform classification using a state-of-the-art neural networks model. In this paper, we propose CARTMAN, a complex activity recognition method that uses Latent Dirichlet allocation (LDA) topic models to generate smartphone sensor features that capture the latent representation of complex activities. These LDA features are then classified using a DeepConvLSTM neural network with self-attention. DeepConvLSTM auto-learns the spatio-temporal features from the sensor data while the self-attention layer identifies and focuses on the predictive points within the time-series sensor data. Our CARTMAN approach outperforms the current state-of-the-art complex activity models and baseline models by 6-23% in macro and weighted F1-scores.","PeriodicalId":330785,"journal":{"name":"2021 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116967040","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

PhD Forum Abstract: Privacy-preserving Data Collection and Sharing in Smart Spaces 摘要:智能空间中保护隐私的数据收集与共享

2021 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2021-08-01 DOI: 10.1109/SMARTCOMP52413.2021.00089

Guoxi Wang

引用次数: 1

Declarative Goal Mediation in Smart Environments 智能环境中的声明性目标调解

2021 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2021-08-01 DOI: 10.1109/SMARTCOMP52413.2021.00079

Giuseppe Bisicchia, Stefano Forti, Antonio Brogi

引用次数: 3