Although, gaze-based interaction has been investigated since the 1980s and remains a promising concept to support universal interaction within distributed IoT environments, main challenges like the Midas touch problem [6] or calibration are still frequent topics of research. In this work we present Natural Pursuit Calibration, a comfortable, unobtrusive technique enabling ongoing attention detection and eye tracker calibration in a real-world context. The user is able to perform calibration, without a digital user interface, artificial annotation of the environment and without assistance, by simply following any arbitrary moving target. Due to the characteristics of the calibration process it can be executed simultaneously to any primary task, without active user participation, resulting in a frequently updated calibration model.
{"title":"Natural pursuit calibration: using motion trajectories for unobtrusive calibration of mobile eye trackers","authors":"Michaela Murauer, Michael Haslgrübler, A. Ferscha","doi":"10.1145/3131542.3140271","DOIUrl":"https://doi.org/10.1145/3131542.3140271","url":null,"abstract":"Although, gaze-based interaction has been investigated since the 1980s and remains a promising concept to support universal interaction within distributed IoT environments, main challenges like the Midas touch problem [6] or calibration are still frequent topics of research. In this work we present Natural Pursuit Calibration, a comfortable, unobtrusive technique enabling ongoing attention detection and eye tracker calibration in a real-world context. The user is able to perform calibration, without a digital user interface, artificial annotation of the environment and without assistance, by simply following any arbitrary moving target. Due to the characteristics of the calibration process it can be executed simultaneously to any primary task, without active user participation, resulting in a frequently updated calibration model.","PeriodicalId":166408,"journal":{"name":"Proceedings of the Seventh International Conference on the Internet of Things","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131815642","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}
Yuhong Li, X. Hao, Hang Zheng, Xiang Su, J. Riekki, Chao Sun, Hanyu Wei, Hao Wang, Lei Han
With the popularization of intelligent transport and mobile internet services, vehicles and people on board generate increasing amounts of data. To match future networks with this use case, tools are needed to analyze the requirements set for the network. In this paper, we study the characteristics of data traffic in the context of networked vehicles. We generate data traffic based on real-world vehicle traces and reported data patterns of end-user applications and vehicles. Based on this, we propose a two-level hidden Markov model to describe both large and small temporal characteristics of data traffic from vehicles aggregated on base stations. We evaluate the proposed model by comparing the original and synthesized data. The results show that the proposed model can well characterize the data traffic from vehicles.
{"title":"A two-level hidden Markov model for characterizing data traffic from vehicles","authors":"Yuhong Li, X. Hao, Hang Zheng, Xiang Su, J. Riekki, Chao Sun, Hanyu Wei, Hao Wang, Lei Han","doi":"10.1145/3131542.3131556","DOIUrl":"https://doi.org/10.1145/3131542.3131556","url":null,"abstract":"With the popularization of intelligent transport and mobile internet services, vehicles and people on board generate increasing amounts of data. To match future networks with this use case, tools are needed to analyze the requirements set for the network. In this paper, we study the characteristics of data traffic in the context of networked vehicles. We generate data traffic based on real-world vehicle traces and reported data patterns of end-user applications and vehicles. Based on this, we propose a two-level hidden Markov model to describe both large and small temporal characteristics of data traffic from vehicles aggregated on base stations. We evaluate the proposed model by comparing the original and synthesized data. The results show that the proposed model can well characterize the data traffic from vehicles.","PeriodicalId":166408,"journal":{"name":"Proceedings of the Seventh International Conference on the Internet of Things","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130301098","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}
Aron Laszka, A. Dubey, Michael A. Walker, D. Schmidt
Power grids are undergoing major changes due to rapid growth in renewable energy resources and improvements in battery technology. While these changes enhance sustainability and efficiency, they also create significant management challenges as the complexity of power systems increases. To tackle these challenges, decentralized Internet-of-Things (IoT) solutions are emerging, which arrange local communities into transactive microgrids. Within a transactive microgrid, "prosumers" (i.e., consumers with energy generation and storage capabilities) can trade energy with each other, thereby smoothing the load on the main grid using local supply. It is hard, however, to provide security, safety, and privacy in a decentralized and transactive energy system. On the one hand, prosumers' personal information must be protected from their trade partners and the system operator. On the other hand, the system must be protected from careless or malicious trading, which could destabilize the entire grid. This paper describes Privacy-preserving Energy Transactions (PETra), which is a secure and safe solution for transactive microgrids that enables consumers to trade energy without sacrificing their privacy. PETra builds on distributed ledgers, such as blockchains, and provides anonymity for communication, bidding, and trading.
{"title":"Providing privacy, safety, and security in IoT-based transactive energy systems using distributed ledgers","authors":"Aron Laszka, A. Dubey, Michael A. Walker, D. Schmidt","doi":"10.1145/3131542.3131562","DOIUrl":"https://doi.org/10.1145/3131542.3131562","url":null,"abstract":"Power grids are undergoing major changes due to rapid growth in renewable energy resources and improvements in battery technology. While these changes enhance sustainability and efficiency, they also create significant management challenges as the complexity of power systems increases. To tackle these challenges, decentralized Internet-of-Things (IoT) solutions are emerging, which arrange local communities into transactive microgrids. Within a transactive microgrid, \"prosumers\" (i.e., consumers with energy generation and storage capabilities) can trade energy with each other, thereby smoothing the load on the main grid using local supply. It is hard, however, to provide security, safety, and privacy in a decentralized and transactive energy system. On the one hand, prosumers' personal information must be protected from their trade partners and the system operator. On the other hand, the system must be protected from careless or malicious trading, which could destabilize the entire grid. This paper describes Privacy-preserving Energy Transactions (PETra), which is a secure and safe solution for transactive microgrids that enables consumers to trade energy without sacrificing their privacy. PETra builds on distributed ledgers, such as blockchains, and provides anonymity for communication, bidding, and trading.","PeriodicalId":166408,"journal":{"name":"Proceedings of the Seventh International Conference on the Internet of Things","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132878244","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}
Badraddin Alturki, S. Reiff-Marganiec, Charith Perera
The vision of the Internet of Things is to allow currently unconnected physical objects to be connected to the internet. There will be an extremely large number of internet connected devices that will be much more than the number of human being in the world all producing data. These data will be collected and delivered to the cloud for processing, especially with a view of finding meaningful information to then take action. However, ideally the data needs to be analysed locally to increase privacy, give quick responses to people and to reduce use of network and storage resources. To tackle these problems, distributed data analytics can be proposed to collect and analyse the data either in the edge or fog devices. In this paper, we explore a hybrid approach which means that both in-network level and cloud level processing should work together to build effective IoT data analytics in order to overcome their respective weaknesses and use their specific strengths. Specifically, we collected raw data locally and extracted features by applying data fusion techniques on the data on resource constrained devices to reduce the data and then send the extracted features to the cloud for processing. We evaluated the accuracy and data consumption over network and thus show that it is feasible to increase privacy and maintain accuracy while reducing data communication demands.
{"title":"A hybrid approach for data analytics for internet of things","authors":"Badraddin Alturki, S. Reiff-Marganiec, Charith Perera","doi":"10.1145/3131542.3131558","DOIUrl":"https://doi.org/10.1145/3131542.3131558","url":null,"abstract":"The vision of the Internet of Things is to allow currently unconnected physical objects to be connected to the internet. There will be an extremely large number of internet connected devices that will be much more than the number of human being in the world all producing data. These data will be collected and delivered to the cloud for processing, especially with a view of finding meaningful information to then take action. However, ideally the data needs to be analysed locally to increase privacy, give quick responses to people and to reduce use of network and storage resources. To tackle these problems, distributed data analytics can be proposed to collect and analyse the data either in the edge or fog devices. In this paper, we explore a hybrid approach which means that both in-network level and cloud level processing should work together to build effective IoT data analytics in order to overcome their respective weaknesses and use their specific strengths. Specifically, we collected raw data locally and extracted features by applying data fusion techniques on the data on resource constrained devices to reduce the data and then send the extracted features to the cloud for processing. We evaluated the accuracy and data consumption over network and thus show that it is feasible to increase privacy and maintain accuracy while reducing data communication demands.","PeriodicalId":166408,"journal":{"name":"Proceedings of the Seventh International Conference on the Internet of Things","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122322977","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}
{"title":"Proceedings of the Seventh International Conference on the Internet of Things","authors":"","doi":"10.1145/3131542","DOIUrl":"https://doi.org/10.1145/3131542","url":null,"abstract":"","PeriodicalId":166408,"journal":{"name":"Proceedings of the Seventh International Conference on the Internet of Things","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133715744","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：