Pub Date : 2019-10-01DOI: 10.1109/ISC246665.2019.9071692
P. Santos, Luís M. Sousa, Ana Aguiar
Smart Cities will leverage the Internet-of-Things (IoT) paradigm to enable cyber-physical loops over urban processes. Vehicular backhauls contribute to IoT platforms by allowing sensor/actuator nodes near roads to explore opportunistic connections to passing vehicles when other communication backhauls are unavailable. A placement process of nodes that includes vehicular networks as a connectivity backhaul requires estimates of infrastructure-to-vehicle (I2V) wireless service at potential deployment sites. However, carrying out I2V measurement campaigns at all potential locations can be very expensive; so, predictive models are necessary. To this end, qualitative characteristics of a potential site, such as infrastructural points-of-interest (POI) relating to traffic (i.e., traffic lights, crosswalks) and fleet activities (i.e., bus stops, garbage bins) can inform about the vehicles’ mobility patterns and quality of the I2V service. In this paper, we show the contribution of POI (and site-specific information) to I2V transfers, leveraging a real-world dataset of geo-referenced I2V WiFi link measurements in urban settings. We present the distributions of throughput with respect to distance per POI class and site, and apply exponential regression to obtain practical throughput/distance models. We then use these models to compare I2V transfer estimation methodologies with different levels of POI-specific data and data resolution. We observe that I2V transfer estimate accuracy can improve from an average over-estimation of 18.3% with respect to measured values, if site or POI-specific information metrics are not used, to 9.3% in case such information is used.
{"title":"Experimental Evaluation of Urban Points-of-Interest as Predictors of I2V 802.11 Data Transfers","authors":"P. Santos, Luís M. Sousa, Ana Aguiar","doi":"10.1109/ISC246665.2019.9071692","DOIUrl":"https://doi.org/10.1109/ISC246665.2019.9071692","url":null,"abstract":"Smart Cities will leverage the Internet-of-Things (IoT) paradigm to enable cyber-physical loops over urban processes. Vehicular backhauls contribute to IoT platforms by allowing sensor/actuator nodes near roads to explore opportunistic connections to passing vehicles when other communication backhauls are unavailable. A placement process of nodes that includes vehicular networks as a connectivity backhaul requires estimates of infrastructure-to-vehicle (I2V) wireless service at potential deployment sites. However, carrying out I2V measurement campaigns at all potential locations can be very expensive; so, predictive models are necessary. To this end, qualitative characteristics of a potential site, such as infrastructural points-of-interest (POI) relating to traffic (i.e., traffic lights, crosswalks) and fleet activities (i.e., bus stops, garbage bins) can inform about the vehicles’ mobility patterns and quality of the I2V service. In this paper, we show the contribution of POI (and site-specific information) to I2V transfers, leveraging a real-world dataset of geo-referenced I2V WiFi link measurements in urban settings. We present the distributions of throughput with respect to distance per POI class and site, and apply exponential regression to obtain practical throughput/distance models. We then use these models to compare I2V transfer estimation methodologies with different levels of POI-specific data and data resolution. We observe that I2V transfer estimate accuracy can improve from an average over-estimation of 18.3% with respect to measured values, if site or POI-specific information metrics are not used, to 9.3% in case such information is used.","PeriodicalId":306836,"journal":{"name":"2019 IEEE International Smart Cities Conference (ISC2)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114964842","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}
Pub Date : 2019-10-01DOI: 10.1109/ISC246665.2019.9071722
A. Elmouatamid, R. Ouladsine, M. Bakhouya, N. E. Kamoun, K. Zine-dine, M. Khaidar
Balancing production and demand of energy is the main challenge to integrate renewable energy sources (RES) in micro-grid (MG) systems. However, the variability and the uncertainty nature of the production and the consumption make the system more difficult to control. In fact, weather conditions influence on the production of renewable energy sources while occupancy influences on the power consumption. Therefore, the development of accurate short term forecasts are needed for a seamless integration of RES (e.g. photovoltaic system, wind turbine) together with the traditional electrical grid in MG systems. This paper presents a forecasting model for predicting the power production and consumption in MG systems together with the battery state of charge (SoC). A control strategy is then implemented to balance the Demand/Response by taking into account the forecasted and real-time values. Based on the data collected from a real MG system, simulation results are presented to show the effectiveness of power forecasting for MG control.
{"title":"A Control Strategy Based on Power Forecasting for Micro-Grid Systems","authors":"A. Elmouatamid, R. Ouladsine, M. Bakhouya, N. E. Kamoun, K. Zine-dine, M. Khaidar","doi":"10.1109/ISC246665.2019.9071722","DOIUrl":"https://doi.org/10.1109/ISC246665.2019.9071722","url":null,"abstract":"Balancing production and demand of energy is the main challenge to integrate renewable energy sources (RES) in micro-grid (MG) systems. However, the variability and the uncertainty nature of the production and the consumption make the system more difficult to control. In fact, weather conditions influence on the production of renewable energy sources while occupancy influences on the power consumption. Therefore, the development of accurate short term forecasts are needed for a seamless integration of RES (e.g. photovoltaic system, wind turbine) together with the traditional electrical grid in MG systems. This paper presents a forecasting model for predicting the power production and consumption in MG systems together with the battery state of charge (SoC). A control strategy is then implemented to balance the Demand/Response by taking into account the forecasted and real-time values. Based on the data collected from a real MG system, simulation results are presented to show the effectiveness of power forecasting for MG control.","PeriodicalId":306836,"journal":{"name":"2019 IEEE International Smart Cities Conference (ISC2)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114989507","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}
Pub Date : 2019-10-01DOI: 10.1109/ISC246665.2019.9071657
Matteo Mazzamurro, Yue Wu, Weisi Guo
Geo-tagged social media data is a key input to many smart city application areas, ranging from mapping consumer demand to understanding location dependent well-being. The sparsity in geo-tagged data, especially in certain cities, means that there is a lack of dynamic spatial point process models for social media data. Having statistically representative spatial models can enable proxy models that improve our understanding of human patterns in urban and suburban areas. Here, we analyse a data set of more than 400,000 Tweets in London to create a spatial point process model of Tweet clusters. We model Tweet clusters as a Poisson Cluster Process. We then track how the point process parameter and spatial entropy evolve over time to create a generative model usable for others, as well as discuss its relevance to urban dynamics and smart city applications.
{"title":"Dynamic Spatial Cluster Process Model of Geo-Tagged Tweets in London","authors":"Matteo Mazzamurro, Yue Wu, Weisi Guo","doi":"10.1109/ISC246665.2019.9071657","DOIUrl":"https://doi.org/10.1109/ISC246665.2019.9071657","url":null,"abstract":"Geo-tagged social media data is a key input to many smart city application areas, ranging from mapping consumer demand to understanding location dependent well-being. The sparsity in geo-tagged data, especially in certain cities, means that there is a lack of dynamic spatial point process models for social media data. Having statistically representative spatial models can enable proxy models that improve our understanding of human patterns in urban and suburban areas. Here, we analyse a data set of more than 400,000 Tweets in London to create a spatial point process model of Tweet clusters. We model Tweet clusters as a Poisson Cluster Process. We then track how the point process parameter and spatial entropy evolve over time to create a generative model usable for others, as well as discuss its relevance to urban dynamics and smart city applications.","PeriodicalId":306836,"journal":{"name":"2019 IEEE International Smart Cities Conference (ISC2)","volume":"233 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127493001","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}
Pub Date : 2019-10-01DOI: 10.1109/ISC246665.2019.9071699
Steven Vanden Broucke, N. Deligiannis
As the size and dimensionality of big heterogeneous data increases, finding patterns and anomalies with existing visualization methods and tools poses a significant challenge. The majority of open data platforms that offer smart city data visualizations use browser-based two-dimensional (2D) visualizations as 2D displays are widely adopted. These displays are however ineffective in depicting multi-dimensional heterogeneous data. The recent growth in the virtual reality (VR) consumer market resulted in an affordable alternative for 3D visualizations. In this paper, we propose a VR system capable of visualizing real-time smart city data concerning the city of Brussels. A subset of external data sources that is already visualized in existing web platforms is incorporated in the VR application. A user study is conducted to assess perceived workloads and data immersion parameters for a set of data exploration tasks in three existing web platforms and in the proposed VR system. Results indicate significantly lower levels of perceived frustration and significantly higher levels of data intuitivity, immersion, overview in data, and intuitive interaction. However, no significant difference in total perceived workload is observed.
{"title":"Visualization of Real-Time Heterogeneous Smart City Data Using Virtual Reality","authors":"Steven Vanden Broucke, N. Deligiannis","doi":"10.1109/ISC246665.2019.9071699","DOIUrl":"https://doi.org/10.1109/ISC246665.2019.9071699","url":null,"abstract":"As the size and dimensionality of big heterogeneous data increases, finding patterns and anomalies with existing visualization methods and tools poses a significant challenge. The majority of open data platforms that offer smart city data visualizations use browser-based two-dimensional (2D) visualizations as 2D displays are widely adopted. These displays are however ineffective in depicting multi-dimensional heterogeneous data. The recent growth in the virtual reality (VR) consumer market resulted in an affordable alternative for 3D visualizations. In this paper, we propose a VR system capable of visualizing real-time smart city data concerning the city of Brussels. A subset of external data sources that is already visualized in existing web platforms is incorporated in the VR application. A user study is conducted to assess perceived workloads and data immersion parameters for a set of data exploration tasks in three existing web platforms and in the proposed VR system. Results indicate significantly lower levels of perceived frustration and significantly higher levels of data intuitivity, immersion, overview in data, and intuitive interaction. However, no significant difference in total perceived workload is observed.","PeriodicalId":306836,"journal":{"name":"2019 IEEE International Smart Cities Conference (ISC2)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125819672","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}
Pub Date : 2019-10-01DOI: 10.1109/ISC246665.2019.9071782
N. K. Twum-Duah, Manar Amayri, F. Wurtz, S. Ploix
According to experts, the average temperature of the planet has increased at an unprecedented and alarmingly high rate over the last fifty (50) years. Carbon emissions have been found to be a major catalyst for climate change and the energy sector one of the highest emitters globally. Thus any significant reduction in energy related emissions would have a significant impact on global carbon emissions and consequently global warming. UN-Habitat estimates that approximately 56% of energy produced in most African nations is consumed in buildings. There is a need for energy efficiency and possibly conservation in buildings since they represent the single largest consumer of energy on the continent. Net Zero Energy Buildings (NZEBs), a possible solution for reducing the energy footprint of buildings, represents the evolution of buildings in the near future. The Zero energy concept has a major impact on the design and construction of future buildings. This paper focuses on the review and development of existing Load Match Indicators for zero energy buildings. Four indicators are provided and discussed (i.e. self-consumption, self-production, loss of load probability, and coverage rate indicators). For the purpose of this paper, Predis-MHI (a platform of G2ELab) was used as a case study. Data was collected from the platform’s living lab and was used in the calculation and evaluation of these indicators. The results indicate the relevance of each indicator in evaluating the energetic performance of a building and also highlight the practical difficulties faced in evaluating the platform.
{"title":"Indicators for Evaluation of Energetic Performance of Net Zero Energy Buildings","authors":"N. K. Twum-Duah, Manar Amayri, F. Wurtz, S. Ploix","doi":"10.1109/ISC246665.2019.9071782","DOIUrl":"https://doi.org/10.1109/ISC246665.2019.9071782","url":null,"abstract":"According to experts, the average temperature of the planet has increased at an unprecedented and alarmingly high rate over the last fifty (50) years. Carbon emissions have been found to be a major catalyst for climate change and the energy sector one of the highest emitters globally. Thus any significant reduction in energy related emissions would have a significant impact on global carbon emissions and consequently global warming. UN-Habitat estimates that approximately 56% of energy produced in most African nations is consumed in buildings. There is a need for energy efficiency and possibly conservation in buildings since they represent the single largest consumer of energy on the continent. Net Zero Energy Buildings (NZEBs), a possible solution for reducing the energy footprint of buildings, represents the evolution of buildings in the near future. The Zero energy concept has a major impact on the design and construction of future buildings. This paper focuses on the review and development of existing Load Match Indicators for zero energy buildings. Four indicators are provided and discussed (i.e. self-consumption, self-production, loss of load probability, and coverage rate indicators). For the purpose of this paper, Predis-MHI (a platform of G2ELab) was used as a case study. Data was collected from the platform’s living lab and was used in the calculation and evaluation of these indicators. The results indicate the relevance of each indicator in evaluating the energetic performance of a building and also highlight the practical difficulties faced in evaluating the platform.","PeriodicalId":306836,"journal":{"name":"2019 IEEE International Smart Cities Conference (ISC2)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121188457","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}
Pub Date : 2019-10-01DOI: 10.1109/ISC246665.2019.9071669
Chayanit Chotbenjamaporn, Achiraya Chutisilp, Panuwat Threethanuchai, Sarun Poolkrajang, Methasit Tuwawit, Pamaree Laowong, Apisara Tirajitto, Ekkawit Wang, Rada Muangsiri, Arocha Compeecharoenporn, Vasant Srichawla, N. Prompoon, C. Ratanamahatana, M. Pipattanasomporn
In a typical university campus, many transportation methods are available in addition to personal vehicles and walking. For example, at Chulalongkorn University, on-campus transportation means are CU Pop Bus, Ha:mo, MuvMi and CU Bike. Existing navigation tools do not take into account all available transportation means into the routing. The objective of this work is to develop a prototype navigation system for a smart campus that suggests shortest/fastest routes based on all available on-campus transportation methods. In addition, the database containing course information has also been developed for students to search for their classrooms by inputting course ID or course name. Moreover, this web-based application provides the ability to view real-time PM2.5 level, which is the issue of great concern in many Asian countries. The case study of Chulalongkorn University, Thailand, is used as an example to demonstrate the developed prototype. This paper discusses overview of the developed system, its functional and non-functional requirements, system architecture, software quality assurance tests/results, and prototype implementation. It is worth noting that the work and method presented herein can be implemented at any other university campuses elsewhere.
在一个典型的大学校园里，除了私家车和步行之外，还有许多交通方式可供选择。例如，在朱拉隆功大学，校园交通工具是CU Pop Bus, Ha:mo, MuvMi和CU Bike。现有的导航工具并没有考虑到所有可用的交通工具的路线。这项工作的目的是为智能校园开发一个原型导航系统，该系统可以根据所有可用的校园交通方式建议最短/最快的路线。此外，还开发了包含课程信息的数据库，供学生通过输入课程ID或课程名称来搜索他们的教室。此外，这个基于网络的应用程序提供了实时查看PM2.5水平的能力，这是许多亚洲国家非常关注的问题。以泰国朱拉隆功大学为例，演示了开发的原型。本文讨论了开发系统的概述，它的功能和非功能需求，系统架构，软件质量保证测试/结果，以及原型实现。值得注意的是，本文提出的工作和方法可以在其他任何大学校园实施。
{"title":"A Web-based Navigation System for a Smart Campus with Air Quality Monitoring","authors":"Chayanit Chotbenjamaporn, Achiraya Chutisilp, Panuwat Threethanuchai, Sarun Poolkrajang, Methasit Tuwawit, Pamaree Laowong, Apisara Tirajitto, Ekkawit Wang, Rada Muangsiri, Arocha Compeecharoenporn, Vasant Srichawla, N. Prompoon, C. Ratanamahatana, M. Pipattanasomporn","doi":"10.1109/ISC246665.2019.9071669","DOIUrl":"https://doi.org/10.1109/ISC246665.2019.9071669","url":null,"abstract":"In a typical university campus, many transportation methods are available in addition to personal vehicles and walking. For example, at Chulalongkorn University, on-campus transportation means are CU Pop Bus, Ha:mo, MuvMi and CU Bike. Existing navigation tools do not take into account all available transportation means into the routing. The objective of this work is to develop a prototype navigation system for a smart campus that suggests shortest/fastest routes based on all available on-campus transportation methods. In addition, the database containing course information has also been developed for students to search for their classrooms by inputting course ID or course name. Moreover, this web-based application provides the ability to view real-time PM2.5 level, which is the issue of great concern in many Asian countries. The case study of Chulalongkorn University, Thailand, is used as an example to demonstrate the developed prototype. This paper discusses overview of the developed system, its functional and non-functional requirements, system architecture, software quality assurance tests/results, and prototype implementation. It is worth noting that the work and method presented herein can be implemented at any other university campuses elsewhere.","PeriodicalId":306836,"journal":{"name":"2019 IEEE International Smart Cities Conference (ISC2)","volume":"145 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114310465","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}
Pub Date : 2019-10-01DOI: 10.1109/ISC246665.2019.9071725
A. Davenport, S. Shetty
In this paper we consider the threat surface and security of air gapped wallet schemes for permissioned blockchains as preparation for a Markov based mathematical model, and quantify the risk associated with private key leakage. We identify existing threats to the wallet scheme and existing work done to both attack and secure the scheme. We provide an overview the proposed model and outline justification for our methods. We follow with next steps in our remaining work and the overarching goals and motivation for our methods.
{"title":"Modeling Threat of Leaking Private Keys from Air-Gapped Blockchain Wallets","authors":"A. Davenport, S. Shetty","doi":"10.1109/ISC246665.2019.9071725","DOIUrl":"https://doi.org/10.1109/ISC246665.2019.9071725","url":null,"abstract":"In this paper we consider the threat surface and security of air gapped wallet schemes for permissioned blockchains as preparation for a Markov based mathematical model, and quantify the risk associated with private key leakage. We identify existing threats to the wallet scheme and existing work done to both attack and secure the scheme. We provide an overview the proposed model and outline justification for our methods. We follow with next steps in our remaining work and the overarching goals and motivation for our methods.","PeriodicalId":306836,"journal":{"name":"2019 IEEE International Smart Cities Conference (ISC2)","volume":"41 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125910541","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}
Pub Date : 2019-10-01DOI: 10.1109/ISC246665.2019.9071789
S. I. Lopes, P. M. Moreira, António M. Cruz, Pedro M. N. Martins, F. Pereira, A. Curado
IoT-based monitoring (i.e. smart monitoring) technologies have been recently used for on-line monitoring in many application fields, such as home, environmental and industrial process monitoring. People spend at least half of their life inside buildings, therefore, Indoor Air Quality (IAQ) plays an important role both on human health and on buildings’ sustainability. Radon gas is one of the most important parameters regarding IAQ assessment, being considered by the World Health Organization (WHO) as the second largest risk factor associated with lung cancer. This paper aims to present RnMonitor, a WebGIS-based platform developed for effective Radon Risk Management and expedite in situ deployment of IoT-based sensors. Given the fact that the spatial context is key for visual and data analytics, the proposed platform takes advantage of a hierarchy of spatially related entities (buildings/rooms/devices) that are natively georeferenced in the system, and thus providing spatial context to acquired data, and other relevant metrics, by means of a simple, responsive and intuitive web-based application.
近年来，基于物联网的监测(即智能监测)技术已被用于许多应用领域的在线监测，如家庭、环境和工业过程监测。人的一生中至少有一半时间是在建筑物内度过的，因此，室内空气质量(Indoor Air Quality, IAQ)对人体健康和建筑物的可持续性都起着重要的作用。氡气是室内空气质量评估最重要的参数之一，被世界卫生组织(世卫组织)视为与肺癌有关的第二大危险因素。本文旨在介绍RnMonitor，这是一个基于webgis的平台，用于有效的氡风险管理，并加快基于物联网的传感器的现场部署。考虑到空间环境是视觉和数据分析的关键，该平台利用了系统中本地地理参考的空间相关实体(建筑物/房间/设备)的层次结构，从而通过简单、响应迅速和直观的基于web的应用程序为获取的数据和其他相关指标提供空间环境。
{"title":"RnMonitor: a WebGIS-based platform for expedite in situ deployment of IoT edge devices and effective Radon Risk Management","authors":"S. I. Lopes, P. M. Moreira, António M. Cruz, Pedro M. N. Martins, F. Pereira, A. Curado","doi":"10.1109/ISC246665.2019.9071789","DOIUrl":"https://doi.org/10.1109/ISC246665.2019.9071789","url":null,"abstract":"IoT-based monitoring (i.e. smart monitoring) technologies have been recently used for on-line monitoring in many application fields, such as home, environmental and industrial process monitoring. People spend at least half of their life inside buildings, therefore, Indoor Air Quality (IAQ) plays an important role both on human health and on buildings’ sustainability. Radon gas is one of the most important parameters regarding IAQ assessment, being considered by the World Health Organization (WHO) as the second largest risk factor associated with lung cancer. This paper aims to present RnMonitor, a WebGIS-based platform developed for effective Radon Risk Management and expedite in situ deployment of IoT-based sensors. Given the fact that the spatial context is key for visual and data analytics, the proposed platform takes advantage of a hierarchy of spatially related entities (buildings/rooms/devices) that are natively georeferenced in the system, and thus providing spatial context to acquired data, and other relevant metrics, by means of a simple, responsive and intuitive web-based application.","PeriodicalId":306836,"journal":{"name":"2019 IEEE International Smart Cities Conference (ISC2)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131464537","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}
Pub Date : 2019-10-01DOI: 10.1109/ISC246665.2019.9071663
Adnane Founoun, A. Hayar, A. Haqiq
This paper comes to present the interest in the regulation tools and laws of smart city as well as how the artificial intelligence can help to diagnose the level of maturity of the local regulation through the textual data analysis. Secondly, we address the assessment of the orientation of the regulatory efforts within the cities through the analysis of diagnosis results.
{"title":"The Textual Data Analysis Approach to Assist the Diagnosis of Smart Cities Initiatives","authors":"Adnane Founoun, A. Hayar, A. Haqiq","doi":"10.1109/ISC246665.2019.9071663","DOIUrl":"https://doi.org/10.1109/ISC246665.2019.9071663","url":null,"abstract":"This paper comes to present the interest in the regulation tools and laws of smart city as well as how the artificial intelligence can help to diagnose the level of maturity of the local regulation through the textual data analysis. Secondly, we address the assessment of the orientation of the regulatory efforts within the cities through the analysis of diagnosis results.","PeriodicalId":306836,"journal":{"name":"2019 IEEE International Smart Cities Conference (ISC2)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115722389","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}
Pub Date : 2019-10-01DOI: 10.1109/ISC246665.2019.9071726
M. Manjutha, P. Subashini, M. Krishnaveni
All over the world millions of people were affected by speech disorders in which one of the significant speech disorders is stuttering. Over the past two decade immense number of research is going on in the field of fluency disorder, and still it is necessary to enhance the analysis of stuttering disorder regional-wise. The speech signal tempo will vary with each individual where the specific fluctuation in the velocity of stutter speech is typical and it is due to the intervals in the speech rate which has a significant difference in normal stuttered speech. In this paper, Regularity of Speech Energy (RSE) was analyzed as normal, moderate and severe through Tamil speaking stuttered dataset. The analysis was done based on the energy threshold obtained during the irregular release of energy which is henceforth analyzed using optimal thresholding based on Particle Swam optimization (PSO) and Synergistic Fibroblast optimization (SFO) techniques. In order to evaluate the experimental analysis on RSE, statistical measures such as mean, standard deviation, Mean Square Error (MSE) and Root Mean Square Error (RMSE) were calculated. The experimental results of analysis on RSE have proved that stuttered speaker’s signal releases low energy when compared to the normal speaker where the optimal threshold energy enhances the detection of hidden speech energy.
全世界数以百万计的人受到语言障碍的影响，其中最重要的语言障碍之一就是口吃。在过去的二十年里，人们对言语流利障碍进行了大量的研究，但仍有必要加强对区域口吃障碍的分析。言语信号的节奏因人而异，其中口吃言语速度的特定波动是典型的，这是由于言语速率的间隔在正常口吃言语中具有显著差异。本文通过泰米尔语口吃数据集，分析了正常、中度和重度三种语言能量的规律性。该分析是基于不规则能量释放过程中获得的能量阈值进行的，随后使用基于粒子游优化(PSO)和协同成纤维细胞优化(SFO)技术的最优阈值进行分析。为了评价RSE的实验分析结果，计算了均数、标准差、均方误差(mean Square Error, MSE)和均方根误差(Root mean Square Error, RMSE)等统计指标。RSE分析的实验结果证明，与正常说话人相比，口吃者信号释放的能量较低，最优阈值能量增强了对隐藏语音能量的检测。
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