2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)最新文献_第4页

Poster Abstract: Efficient Visual Positioning with Adaptive Parameter Learning 摘要:基于自适应参数学习的高效视觉定位

2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Pub Date : 2016-04-11 DOI: 10.1109/IPSN.2016.7460701

Hongkai Wen, Sen Wang, R. Clark, Savvas Papaioannou, A. Trigoni

引用次数: 3

Poster Abstract: Improving the BLE Mesh Transmissions with User Collaboration in Smart Spaces Management 摘要:智能空间管理中用户协作改善BLE Mesh传输

2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Pub Date : 2016-04-11 DOI: 10.1109/IPSN.2016.7460705

Diego Hortelano, Vicente López, T. Olivares, M. Ruiz

引用次数: 3

Demonstration Abstract: Real-Time Indoor Localization with TDOA and Distributed Software Defined Radio 摘要:基于TDOA和分布式软件无线电的实时室内定位

2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Pub Date : 2016-04-11 DOI: 10.1109/IPSN.2016.7460671

Johannes Schmitz, M.A.L. Hernandez, R. Mathar

引用次数: 12

WiWho: WiFi-Based Person Identification in Smart Spaces WiWho:基于wifi的智能空间人物识别

2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Pub Date : 2016-04-11 DOI: 10.1109/IPSN.2016.7460727

Yunze Zeng, P. Pathak, P. Mohapatra

{"title":"WiWho: WiFi-Based Person Identification in Smart Spaces","authors":"Yunze Zeng, P. Pathak, P. Mohapatra","doi":"10.1109/IPSN.2016.7460727","DOIUrl":"https://doi.org/10.1109/IPSN.2016.7460727","url":null,"abstract":"There has been a growing interest in equipping the objects and environment surrounding the user with sensing capabilities. Smart indoor spaces such as smart homes and offices can implement the sensing and processing functionality, relieving users from the need of wearing or carrying smart devices. Enabling such smart spaces requires device-free effortless sensing of user's identity and activities. Device-free sensing using WiFi has shown great potential in such scenarios, however, fundamental questions such as person identification have remained unsolved. In this paper, we present WiWho, a framework that can identify a person from a small group of people in a device-free manner using WiFi. We show that Channel State Information (CSI) used in recent WiFi can identify a person's steps and walking gait. The walking gait being distinguishing characteristics for different people, WiWho uses CSI-based gait for person identification. We demonstrate how step and walk analysis can be used to identify a person's walking gait from CSI, and how this information can be used to identify a person. WiWho does not require a person to carry any device and is effortless since it only requires the person to walk for a few steps (e.g. entering a home or an office). We evaluate WiWho using experiments at multiple locations with a total of 20 volunteers, and show that it can identify a person with average accuracy of 92% to 80% from a group of 2 to 6 people. We also show that in most cases walking as few as 2-3 meters is sufficient to recognize a person's gait and identify the person. We discuss the potential and challenges of WiFi- based person identification with respect to smart space applications.","PeriodicalId":137855,"journal":{"name":"2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131388867","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: 316

Topic-Aware Social Sensing with Arbitrary Source Dependency Graphs 基于任意源依赖图的主题感知社会感知

2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Pub Date : 2016-04-11 DOI: 10.1109/IPSN.2016.7460724

Chao Huang, Dong Wang

{"title":"Topic-Aware Social Sensing with Arbitrary Source Dependency Graphs","authors":"Chao Huang, Dong Wang","doi":"10.1109/IPSN.2016.7460724","DOIUrl":"https://doi.org/10.1109/IPSN.2016.7460724","url":null,"abstract":"This work is motivated by the emergence of social sensing as a new paradigm of collecting observations about the physical environment from humans or devices on their behalf. These observations may be true or false, and hence are viewed as binary claims. A fundamental problem in social sensing applications lies in ascertaining the correctness of claims and the reliability of data sources without knowing either of them a priori. We refer to this problem as truth discovery. Prior works have made significant progress to addressing the truth discovery problem, but two significant limitations exist: (i) they ignored the fact that claims reported in social sensing applications can be either relevant or irrelevant to the topic of interests. (ii) They either assumed the data sources to be independent or the source dependency graphs can be represented as a set of disjoint trees. These limitations led to suboptimal truth discovery results. In contrast, this paper presents the first social sensing framework that explicitly incorporates the topic relevance feature of claims and arbitrary source dependency graphs into the solutions of truth discovery problem. The new framework solves a multidimensional maximum likelihood estimation problem to jointly estimate the truthfulness and topic relevance of claims as well as the reliability and topic awareness of sources. We compared our new scheme with the state-of-the-art truth discovery solutions using three real world data traces collected from Twitter in the aftermath of Paris Shooting event (2015), Hurricane Arthur (2014) and Boston Bombing event (2013) respectively. The evaluation results showed that our schemes significantly outperform the compared baselines by identifying more relevant and truthful claims in the truth discovery results.","PeriodicalId":137855,"journal":{"name":"2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130967633","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: 50

Ph.D. Forum Abstract: Tracking Inefficient Power Usages in WSN by Monitoring the Network Firmware 摘要:通过监控网络固件跟踪无线传感器网络中的低效功耗

2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Pub Date : 2016-04-11 DOI: 10.1109/IPSN.2016.7460690

David Hauweele

引用次数: 0

Ph.D. Forum Abstract: Back to the Future - Sustainable Transiently Powered Embedded Systems 博士论坛摘要:回到未来——可持续的瞬态电源嵌入式系统

2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Pub Date : 2016-04-11 DOI: 10.1109/IPSN.2016.7460686

Naveed Anwar Bhatti

引用次数: 0

Ph.D. Forum Abstract: A Scalable Testbed Infrastructure for Embedded Industrial Wireless Sensor and Actuator Networks 摘要:嵌入式工业无线传感器和执行器网络的可扩展测试平台基础设施

2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Pub Date : 2016-04-11 DOI: 10.1109/IPSN.2016.7460682

Albert Potsch

{"title":"Ph.D. Forum Abstract: A Scalable Testbed Infrastructure for Embedded Industrial Wireless Sensor and Actuator Networks","authors":"Albert Potsch","doi":"10.1109/IPSN.2016.7460682","DOIUrl":"https://doi.org/10.1109/IPSN.2016.7460682","url":null,"abstract":"At least since the terms Internet of Things, Factories of the Future or Industrial Internet gave distinction to the modern world of communication, there is a special need for efficient test- and debug tools targeting research and development of embedded wireless sensor and actuator networks (WSAN) in industrial automation technology and other non-consumer application areas in adverse environments. Those networks usually have tighter requirements on dependability, synchronization, and real-time capability as compared applications in environmental monitoring or home automation. For WSAN research and development, testbeds are a valuable tool as they enable controlled and repeatable operation under conditions close to reality. The contribution of this Ph.D. dissertation is to design, implement and set up a test environment for embedded industrial wireless sensor actuator networks, with special focus on energy constrained network nodes. This testbed should offer an previously unattained level of insight in timing characteristics of the network and the energy behavior of a single node. It allows to make statements about limitations of the deployed WSAN technology, or to compare different WSAN solutions in an automated manner. The uniqueness of this testbed setup is due to a scalable, affordable and maintainable organization both in software as well as the structure of the used hardware components.","PeriodicalId":137855,"journal":{"name":"2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)","volume":"61 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115924505","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: 2

Recursive Ground Truth Estimator for Social Data Streams 社会数据流的递归真值估计

2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Pub Date : 2016-04-11 DOI: 10.1109/IPSN.2016.7460719

Shuochao Yao, Md. Tanvir Al Amin, Lu Su, Shaohan Hu, Shen Li, Shiguang Wang, Yiran Zhao, T. Abdelzaher, Lance M. Kaplan, C. Aggarwal, A. Yener

{"title":"Recursive Ground Truth Estimator for Social Data Streams","authors":"Shuochao Yao, Md. Tanvir Al Amin, Lu Su, Shaohan Hu, Shen Li, Shiguang Wang, Yiran Zhao, T. Abdelzaher, Lance M. Kaplan, C. Aggarwal, A. Yener","doi":"10.1109/IPSN.2016.7460719","DOIUrl":"https://doi.org/10.1109/IPSN.2016.7460719","url":null,"abstract":"The paper develops a recursive state estimator for social network data streams that allows exploitation of social networks, such as Twitter, as sensor networks to reliably observe physical events. Recent literature suggested using social networks as sensor networks leveraging the fact that much of the information upload on the former constitutes acts of sensing. A significant challenge identified in that context was that source reliability is often unknown, leading to uncertainty regarding the veracity of reported observations. Multiple truth finding systems were developed to solve this problem, generally geared towards batch analysis of offline datasets. This work complements the present batch approaches by developing an online recursive state estimator that recovers ground truth from streaming data. In this paper, we model physical world state by a set of binary signals (propositions, called assertions, about world state) and the social network as a noisy medium, where distortion, fabrication, omissions, and duplication are introduced. Our recursive state estimator is designed to recover the original binary signal (the true propositions) from the received noisy signal, essentially decoding the unreliable social network output to obtain the best estimate of ground truth in the physical world. Results show that the estimator is both effective and efficient at recovering the original signal with a high degree of accuracy. The estimator gives rise to a novel situation awareness tool that can be used for reliably following unfolding events in real time, using dynamically arriving social network data.","PeriodicalId":137855,"journal":{"name":"2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122850670","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: 39

Ph.D. Forum Abstract: Scalable Wireless Networks for Industrial Control Systems with Time and Reliability Constraints 摘要:具有时间和可靠性约束的工业控制系统的可扩展无线网络

2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Pub Date : 2016-04-11 DOI: 10.1109/IPSN.2016.7460689

F. Meier

引用次数: 0