2018 14th International Conference on Intelligent Environments (IE)最新文献

Enhancing Mobile Edge Computing Architecture with Human-Driven Edge Computing Model 以人为驱动的边缘计算模型增强移动边缘计算架构

2018 14th International Conference on Intelligent Environments (IE) Pub Date : 2018-06-01 DOI: 10.1109/IE.2018.00023

Dimitri Belli, S. Chessa, L. Foschini, M. Girolami

{"title":"Enhancing Mobile Edge Computing Architecture with Human-Driven Edge Computing Model","authors":"Dimitri Belli, S. Chessa, L. Foschini, M. Girolami","doi":"10.1109/IE.2018.00023","DOIUrl":"https://doi.org/10.1109/IE.2018.00023","url":null,"abstract":"In an increasingly interconnected world, mobile and wearable devices, through short range communication interfaces and sensors, become needful tools for collecting and disseminating information in high population density environments. In this context Mobile Crowdsensing (MCS), leveraging people's roaming and their devices' resources, raised the citizen from mere walk-on parts to active participant in the knowledge building and data dissemination process. At the same time, Mobile Edge Computing (MEC) architecture has recently enhanced the two-layer cloud-device architectural model easing the exchange of information and shifting most computational cost from devices towards middle-layer proxies, namely, network edges. We introduce Human-driven Edge Computing, a new model which melts together the power of MEC platform and the large-scale sensing of MCS to realize a better data spreading and environmental coverage in smart cities. In addition, it will be briefly discussed the main sociological aspects related to human behavior and how they can influence the exchange of data in large-scale sensor networks.","PeriodicalId":237671,"journal":{"name":"2018 14th International Conference on Intelligent Environments (IE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129709376","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

CutiQueue: People Counting in Waiting Lines Using Bluetooth Low Energy Based Passive Presence Detection CutiQueue:使用蓝牙低功耗被动存在检测在等待队列中计数的人

2018 14th International Conference on Intelligent Environments (IE) Pub Date : 2018-06-01 DOI: 10.1109/IE.2018.00009

F. Brockmann, M. Handte, P. Marrón

引用次数: 10

Publisher's Information 出版商的信息

2018 14th International Conference on Intelligent Environments (IE) Pub Date : 2018-06-01 DOI: 10.1109/ie.2018.00028

引用次数: 0

Enabling Driver Feet Gestures Using Capacitive Proximity Sensing 使用电容式接近感应实现驾驶员脚的手势

2018 14th International Conference on Intelligent Environments (IE) Pub Date : 2018-06-01 DOI: 10.1109/IE.2018.00012

Sebastian Frank, Arjan Kuijper

引用次数: 8

Human Activity Prediction in Smart Home Environments with LSTM Neural Networks 基于LSTM神经网络的智能家居环境人类活动预测

2018 14th International Conference on Intelligent Environments (IE) Pub Date : 2018-06-01 DOI: 10.1109/IE.2018.00014

Niek Tax

{"title":"Human Activity Prediction in Smart Home Environments with LSTM Neural Networks","authors":"Niek Tax","doi":"10.1109/IE.2018.00014","DOIUrl":"https://doi.org/10.1109/IE.2018.00014","url":null,"abstract":"In this paper, we investigate the performance of several sequence prediction techniques on the prediction of future events of human behavior in a smart home, as well as the timestamps of those next events. Prediction techniques in smart home environments have several use cases, such as the real-time identification of abnormal behavior, identifying coachable moments for e-coaching, and a plethora of applications in the area of home automation. We give an overview of several sequence prediction techniques, including techniques that originate from the areas of data mining, process mining, and data compression, and we evaluate the predictive accuracy of those techniques on a collection of publicly available real-life datasets from the smart home environments domain. This contrast our work with existing work on prediction in smart homes, which often evaluate their techniques on a single smart home instead of a larger collection of logs. We found that LSTM neural networks outperform the other prediction methods on the task of predicting the next activity as well as on the task of predicting the timestamp of the next event. However, surprisingly, we found that it is very dependent on the dataset which technique works best for the task of predicting a window of multiple next activities.","PeriodicalId":237671,"journal":{"name":"2018 14th International Conference on Intelligent Environments (IE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128998656","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: 28

Choosing Duty-Cycle Parameters for Context Recognition 选择上下文识别的占空比参数

2018 14th International Conference on Intelligent Environments (IE) Pub Date : 2018-06-01 DOI: 10.1109/IE.2018.00020

Vito Janko, M. Luštrek

引用次数: 5

Privacy Challenges for Process Mining in Human-Centered Industrial Environments 以人为中心的工业环境中流程挖掘的隐私挑战

2018 14th International Conference on Intelligent Environments (IE) Pub Date : 2018-06-01 DOI: 10.1109/IE.2018.00017

F. Mannhardt, S. A. Petersen, M. Oliveira

{"title":"Privacy Challenges for Process Mining in Human-Centered Industrial Environments","authors":"F. Mannhardt, S. A. Petersen, M. Oliveira","doi":"10.1109/IE.2018.00017","DOIUrl":"https://doi.org/10.1109/IE.2018.00017","url":null,"abstract":"Operators in industrial manufacturing environments are under pressure to cope with increasing flexibility and complexity of work. The automation of manufacturing requires operators to adopt new techniques and shifts the focus from low-complexity repetitive tasks to dealing with the execution of high-complexity tasks in cooperation with machines. The emergence of wearable technologies makes it possible to equip operators with miniaturized sensors that may be used to determine the physical and mental stress experienced by operators. Process mining technologies are suited to analyze such sensor data in the context of the manufacturing process with the ultimate goal of improving the operator's well-being through re-organization of work and the work place. However, the storage and processing of such highly personalized data comes with many privacy challenges. Whereas there are many potential benefits, such as improve the work environment, there are also many justified reasons for operators to oppose the processing of their data. Apart from employee concerns, data protection regulations, such as EU GDPR (Europe's General Data Protection Regulation), imposes many compliance challenges for the design of a process mining systems dealing with personal data. We contribute an analysis of the privacy challenges of using process mining on data recorded from sensorized operators in human-centered industrial environments. Guided by privacy research and the regulation imposed by the GDPR, we describe guidelines for privacy in process mining systems.","PeriodicalId":237671,"journal":{"name":"2018 14th International Conference on Intelligent Environments (IE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129274394","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: 43

Understanding Visual Impairment: A CA-CV Approach for Cognitive Computer Vision 理解视觉障碍:认知计算机视觉的CA-CV方法

2018 14th International Conference on Intelligent Environments (IE) Pub Date : 2018-06-01 DOI: 10.1109/IE.2018.00024

Emmanuel Ferreyra, Angeliki Balantani

{"title":"Understanding Visual Impairment: A CA-CV Approach for Cognitive Computer Vision","authors":"Emmanuel Ferreyra, Angeliki Balantani","doi":"10.1109/IE.2018.00024","DOIUrl":"https://doi.org/10.1109/IE.2018.00024","url":null,"abstract":"Partially sighted people face multiple challenges in their daily lives. For example, they are not confident about their interactions with other people, mainly because they are not sure of other people's expressions, feelings or intentions. In many cases, this situation results in social issues such as isolation and marginalisation among others. The field of computer vision has attempted to provide solutions to some of the problems people with visual impairment face. Currently, computer vision technologies are able to identify almost any element available in our environment. However, most of the recognition processes are trained based on image classification. The current proposal pushes the boundaries of computer vision (henceforth CV) powered by image categorisation by evolving it to the next stage, namely cognitive computer vision. We aim to develop a computer algorithm to enhance machine vision by incorporating a conversational analytic (henceforth CA) approach. This intelligence will be embedded into a hardware device with the objective of providing real-time feedback to visually impaired users via speech output, thus reducing the gap between technology and human-like augmented senses.","PeriodicalId":237671,"journal":{"name":"2018 14th International Conference on Intelligent Environments (IE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115404722","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

Implementation and Evaluation of Peripheral Light Feedback for Mid-Air Gesture Interaction in the Car 汽车空中手势交互中周边光反馈的实现与评价

2018 14th International Conference on Intelligent Environments (IE) Pub Date : 2018-06-01 DOI: 10.1109/IE.2018.00021

F. Roider, Konstantin Raab

引用次数: 7

Context Feature Learning through Deep Learning for Adaptive Context-Aware Decision Making in the Home 通过深度学习进行上下文特征学习，实现家庭中的自适应上下文感知决策

2018 14th International Conference on Intelligent Environments (IE) Pub Date : 2018-06-01 DOI: 10.1109/IE.2018.00013

Alexis Brenon, François Portet, Michel Vacher

引用次数: 9