2018 IEEE International Smart Cities Conference (ISC2)最新文献_第10页

A Methodological Approach for Inferring Urban Indicators Through Computer Vision 基于计算机视觉的城市指标推断方法研究

2018 IEEE International Smart Cities Conference (ISC2) Pub Date : 2018-09-01 DOI: 10.1109/ISC2.2018.8656934

Sara Paiva, D. Santos, R. Rossetti

{"title":"A Methodological Approach for Inferring Urban Indicators Through Computer Vision","authors":"Sara Paiva, D. Santos, R. Rossetti","doi":"10.1109/ISC2.2018.8656934","DOIUrl":"https://doi.org/10.1109/ISC2.2018.8656934","url":null,"abstract":"The physical environment of a community has been proven to have effects on the mental and physical state of a population. As such, the extraction of Urban Indicators (UI) that evaluate the effects of urban development is essential to assert relationships between the surrounding environment and the well-being of a society. Such a relationship, for example, would be the role of green areas in a city on the prevalence of obesity in its population. In addition, these indicators can contribute to the identification and preventive action in risk situations. For instance, a very degraded area with too much waste accumulated may pose serious risks to public health. However, the traditional methods for UI extraction, particularly in the case of physical indicators, are limited due to the lack of standardized data organization and the subjectivity of self-reported responses, while generally being highly resource-intensive and costly. This work aims to create a methodological approach that is capable of applying Computer Vision to automate the extraction of UI, overcoming the limitations of the traditional approaches. This approach takes advantage of tools that offer remote visualization of locations at low cost. Its success depends on the accurate identification of physical urban indicators that can be extracted from an image, and on choosing appropriate Computer Vision techniques to provide the most precise results for such an analysis.","PeriodicalId":344652,"journal":{"name":"2018 IEEE International Smart Cities Conference (ISC2)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127265557","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: 3

Variability Modeling for Smart City Reference Architectures 智慧城市参考架构的可变性建模

2018 IEEE International Smart Cities Conference (ISC2) Pub Date : 2018-09-01 DOI: 10.1109/ISC2.2018.8656967

Mohammad Abu-Matar, R. Mizouni

{"title":"Variability Modeling for Smart City Reference Architectures","authors":"Mohammad Abu-Matar, R. Mizouni","doi":"10.1109/ISC2.2018.8656967","DOIUrl":"https://doi.org/10.1109/ISC2.2018.8656967","url":null,"abstract":"With the convergence of information and telecommunication technologies, the vision of the ‘Smart City’ is fast becoming a reality. City governments in a growing number of countries are capitalizing on these advances to ease the lives of their citizens and to increase efficiency and sustainability. In our previous research, we have proposed a new approach for designing such ultra large and ultra-heterogeneous ecosystems. The approach is manifested as a reference architecture (smartCityRA) that can be used as the starting point, i.e. blue print, for smart city projects. In this paper, we elaborate on the reference architecture by enabling smartCityRA with variability mechanisms to accommodate the instantiations of different smart city software architectures. We do this by using variability modeling and model-driven architecture techniques. The result is smartCityML, a domain specific language (DSL) for modeling smart city systems. We first develop the abstract syntax of the language. Then, we outline the constituent constructs of the language, i.e. the concrete syntax. Finally, we propose tooling ideas for the new language and suggest evaluation criteria and plans.","PeriodicalId":344652,"journal":{"name":"2018 IEEE International Smart Cities Conference (ISC2)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131463554","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: 11

Vizsafe: The Decentralized Crowdsourcing Safety Network Vizsafe:分散的众包安全网络

2018 IEEE International Smart Cities Conference (ISC2) Pub Date : 2018-09-01 DOI: 10.1109/ISC2.2018.8656658

Peter A. Mottur, Nathan R. Whittaker

{"title":"Vizsafe: The Decentralized Crowdsourcing Safety Network","authors":"Peter A. Mottur, Nathan R. Whittaker","doi":"10.1109/ISC2.2018.8656658","DOIUrl":"https://doi.org/10.1109/ISC2.2018.8656658","url":null,"abstract":"Although there is no single definition, a Smart City is a settlement that uses various technologies to optimize the delivery of services to citizens and increase residents’ quality of life. While a vast array of sensors and IoT devices will be deployed to meet the data requirements of a smart approach to public service delivery, any city’s largest and most sophisticated sensor network takes the form of its citizens. As the ones who use the city’s infrastructure and services 24/7, they are uniquely placed to report any issues. What stops most people from doing so is firstly the lack of a platform with the appropriate channels and secondly, the lack of immediate incentives — most of the time, an issue will be seen as someone else’s job to address.To address these issues, the Vizsafe platform has been designed to mobilize the crowd and give them a reason to submit information that is in everyone’s interests. Through the power of blockchain, these reports are stored on a decentralized ledger, and, utilizing smart contracts, SPOT tokens are used as incentive to people that upload incident reports, whether that is a potential security threat or faulty infrastructure. It’s the slight nudge that makes ‘someone else’s problem’ into ‘my opportunity’. Once cities start rewarding participation meaningfully, people cease to be consumers and service users but rather contribute information for their collective benefit, while reducing costs for businesses and service providers. They become active partners in maintaining the communities in which they live and work.","PeriodicalId":344652,"journal":{"name":"2018 IEEE International Smart Cities Conference (ISC2)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122949115","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

A Fast and Accurate Approach for Real-Time Seizure Detection in the IoMT 一种快速准确的IoMT实时癫痫检测方法

2018 IEEE International Smart Cities Conference (ISC2) Pub Date : 2018-09-01 DOI: 10.1109/ISC2.2018.8656713

Md. Abu Sayeed, S. Mohanty, E. Kougianos, H. Zaveri

{"title":"A Fast and Accurate Approach for Real-Time Seizure Detection in the IoMT","authors":"Md. Abu Sayeed, S. Mohanty, E. Kougianos, H. Zaveri","doi":"10.1109/ISC2.2018.8656713","DOIUrl":"https://doi.org/10.1109/ISC2.2018.8656713","url":null,"abstract":"We propose an EEG-based seizure detection method which uses the discrete wavelet transform (DWT), Hjorth parameters and a k-NN classifier. Seizure detection is performed in three stages. In the first stage, EEG signals are decomposed by the DWT into sub-bands and Hjorth parameters are extracted from each of these sub-bands. In the second stage, a k-NN classifier is used to classify the EEG data. The results demonstrate a significant difference in Hjorth parameters between interictal and ictal EEG with ictal EEG being less complex than interictal EEG. We report an accuracy of 100% for a classification of normal vs. ictal EEG and 97.9% for normal and interictal vs. ictal EEG. We propose an Internet of Medical Things (IoMT) platform for performing seizure detection. The proposed framework accommodates the proposed scheme for seizure detection and allows communication of detection results. The IoMT framework also allows the adjustment of seizure detection parameters in response to updated performance evaluations, and possible changes in seizure and signal characteristics as well as the incorporation of other sensor signals to provide an adaptive, multi-modal framework for detecting seizures.","PeriodicalId":344652,"journal":{"name":"2018 IEEE International Smart Cities Conference (ISC2)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125592366","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: 10

Traffic Event Related Blog Post Classification by Using Traffic Related Named Entities 使用与流量相关的命名实体对与流量事件相关的博客文章进行分类

2018 IEEE International Smart Cities Conference (ISC2) Pub Date : 2018-09-01 DOI: 10.1109/ISC2.2018.8656940

A. Dundar Unsal, Hediye Tuydes-Yaman, Pinar Karagoz

{"title":"Traffic Event Related Blog Post Classification by Using Traffic Related Named Entities","authors":"A. Dundar Unsal, Hediye Tuydes-Yaman, Pinar Karagoz","doi":"10.1109/ISC2.2018.8656940","DOIUrl":"https://doi.org/10.1109/ISC2.2018.8656940","url":null,"abstract":"Real-time monitoring of traffic flow requires physical sensors to be deployed on road networks. Development of such systems might be impractical due to deployment costs of sensors on large scale networks. This study presents a method to extract traffic event related tweets from social streams in order to employ users of social media as human sensors of traffic conditions or events. The proposed method offers a cost effective way of monitoring events or conditions affecting traffic flow. The method consists of three steps. The first step involves natural language processing tasks for preprocessing the blog posts. The second step extracts a set of traffic event related named entities from blog post texts using the model that is constructed with Conditional Random Fields. The third step includes classification in order to detect blog posts reporting events or conditions affecting traffic flow. The proposed method is experimentally evaluated on a set of tweets collected in one month under varying feature sets. The results show the potential of the approach for traffic monitoring and reveals that the use of traffic related named entities increases the classification accuracy.","PeriodicalId":344652,"journal":{"name":"2018 IEEE International Smart Cities Conference (ISC2)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126758348","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

Modeling ‘Thriving Communities’ using a Systems Architecture to Improve Smart Cities Technology Approaches 使用系统架构为“繁荣社区”建模以改进智慧城市技术方法

2018 IEEE International Smart Cities Conference (ISC2) Pub Date : 2018-09-01 DOI: 10.1109/ISC2.2018.8656893

Katherine Axel, Inas S. Khayal

引用次数: 2

Using Geographic Information and Point of Interest to Estimate Missing Second-Hand Housing Price of Residential Area in Urban Space 利用地理信息和兴趣点估算城市空间中居住区缺失二手房价格

2018 IEEE International Smart Cities Conference (ISC2) Pub Date : 2018-09-01 DOI: 10.1109/ISC2.2018.8656965

Jiabo Tang, Zhicheng Liu, Yuran Wang, Junyan Yang, Qiao Wang

{"title":"Using Geographic Information and Point of Interest to Estimate Missing Second-Hand Housing Price of Residential Area in Urban Space","authors":"Jiabo Tang, Zhicheng Liu, Yuran Wang, Junyan Yang, Qiao Wang","doi":"10.1109/ISC2.2018.8656965","DOIUrl":"https://doi.org/10.1109/ISC2.2018.8656965","url":null,"abstract":"The real estate market including second-hand real estate market plays an important role in Chinese economy. However, it is not easy to acquire price of the each pieces of residential area in a city, and for instance the data acquired from Internet in our paper can only cover 56% of residential area in Nanjing. To this end, our paper proposed an model to fill the missing price data by using price and locations of second-hand real estates and Point of Interest (POI) information which were acquired from Internet. Our experiment was conducted in Nanjing and Chongqing, and demonstrates that our model is able to perform better than traditional Geographic Information System (GIS) method, such as Kriging interpolation, and general machine learning model, such as K-Nearest Neighbour (KNN). Also, our proposed model can be more interpretable than traditional methods, and able to reveal how the POI information can influence the second-hand real estate price. Our proposed model can help domain experts, e.g. city planners and economists, to better research the second-hand real estate market in the future.","PeriodicalId":344652,"journal":{"name":"2018 IEEE International Smart Cities Conference (ISC2)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129570238","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: 3

Smart Contracts for Incentivizing Sensor Based Mobile Smart City Applications 激励基于传感器的移动智能城市应用的智能合约

2018 IEEE International Smart Cities Conference (ISC2) Pub Date : 2018-09-01 DOI: 10.1109/ISC2.2018.8656959

J. Lindsay

引用次数: 9

A Machine Learning Approach to Short-Term Traffic Flow Prediction: A Case Study of Interstate 64 in Missouri 短期交通流量预测的机器学习方法:以密苏里州64号州际公路为例

2018 IEEE International Smart Cities Conference (ISC2) Pub Date : 2018-09-01 DOI: 10.1109/ISC2.2018.8656924

Osama Mohammed, J. Kianfar

{"title":"A Machine Learning Approach to Short-Term Traffic Flow Prediction: A Case Study of Interstate 64 in Missouri","authors":"Osama Mohammed, J. Kianfar","doi":"10.1109/ISC2.2018.8656924","DOIUrl":"https://doi.org/10.1109/ISC2.2018.8656924","url":null,"abstract":"Proactive traffic management is a subset of smart mobility applications in which traffic control strategies are implemented in advance to respond to anticipated roadway conditions. Predicted traffic flows are a key input to proactive traffic control systems, such as proactive freeway ramp metering, proactive variable speed limits, and proactive incident management systems. This paper proposes a machine learning approach for short-term traffic flow prediction where prevailing conditions, such as the traffic volume, speed, and occupancy of roadway segments, are used to predict traffic flow in short-term intervals. Four categories of predictive methods for traffic flow prediction were investigated: deep neural networks, a distributed random forest, a gradient boosting machine, and a generalized linear model. Data from Interstate 64 in St. Louis, Missouri, in the United States were used to calibrate and evaluate the models. The results obtained by the four predictive methods were very similar, with the distributed random forest model slightly outperforming the models obtained by the other three methods. The case study showed that the inclusion of traffic flow, speed, occupancy, and time of day in the traffic prediction process reduces the traffic prediction error. However, the two-sample Kolmogorov-Smirnov test did not show a statistically significant benefit from the inclusion of upstream traffic data in the distributed random forest, and gradient boosting machine models.","PeriodicalId":344652,"journal":{"name":"2018 IEEE International Smart Cities Conference (ISC2)","volume":"161 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113998747","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: 27

Competitive Swarm Optimization with Dynamic Opposition-based Learning 基于动态对立学习的竞争群优化

2018 IEEE International Smart Cities Conference (ISC2) Pub Date : 2018-09-01 DOI: 10.1109/ISC2.2018.8656787

Yangfan Zhang, Jun Sun

引用次数: 1