Pub Date : 2014-04-15DOI: 10.1109/IPSN.2014.6846744
C. Boano, Marco Zúñiga, James Brown, U. Roedig, C. Keppitiyagama, K. Römer
Temperature has a strong impact on the operations of all electrical and electronic components. In wireless sensor nodes, temperature variations can lead to loss of synchronization, degradation of the link quality, or early battery depletion, and can therefore affect key network metrics such as throughput, delay, and lifetime. Considering that most outdoor deployments are exposed to strong temperature variations across time and space, a deep understanding of how temperature affects network protocols is fundamental to comprehend flaws in their design and to improve their performance. Existing testbed infrastructures, however, do not allow to systematically study the impact of temperature on wireless sensor networks. In this paper we present TempLab, an extension for wireless sensor network testbeds that allows to control the on-board temperature of sensor nodes and to study the effects of temperature variations on the network performance in a precise and repeatable fashion. TempLab can accurately reproduce traces recorded in outdoor environments with fine granularity, while minimizing the hardware costs and configuration overhead. We use TempLab to analyse the detrimental effects of temperature variations (i) on processing performance, (ii) on a tree routing protocol, and (iii) on CSMA-based MAC protocols, deriving insights that would have not been revealed using existing testbed installations.
{"title":"TempLab: A testbed infrastructure to study the impact of temperature on wireless sensor networks","authors":"C. Boano, Marco Zúñiga, James Brown, U. Roedig, C. Keppitiyagama, K. Römer","doi":"10.1109/IPSN.2014.6846744","DOIUrl":"https://doi.org/10.1109/IPSN.2014.6846744","url":null,"abstract":"Temperature has a strong impact on the operations of all electrical and electronic components. In wireless sensor nodes, temperature variations can lead to loss of synchronization, degradation of the link quality, or early battery depletion, and can therefore affect key network metrics such as throughput, delay, and lifetime. Considering that most outdoor deployments are exposed to strong temperature variations across time and space, a deep understanding of how temperature affects network protocols is fundamental to comprehend flaws in their design and to improve their performance. Existing testbed infrastructures, however, do not allow to systematically study the impact of temperature on wireless sensor networks. In this paper we present TempLab, an extension for wireless sensor network testbeds that allows to control the on-board temperature of sensor nodes and to study the effects of temperature variations on the network performance in a precise and repeatable fashion. TempLab can accurately reproduce traces recorded in outdoor environments with fine granularity, while minimizing the hardware costs and configuration overhead. We use TempLab to analyse the detrimental effects of temperature variations (i) on processing performance, (ii) on a tree routing protocol, and (iii) on CSMA-based MAC protocols, deriving insights that would have not been revealed using existing testbed installations.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125423453","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 : 2014-04-15DOI: 10.1109/IPSN.2014.6846740
Iyswarya Narayanan, Arunchandar Vasan, V. Sarangan, A. Sivasubramaniam
Leak localization is a major issue faced by water utilities worldwide. Leaks are ideally detected and localized by a network-wide metering infrastructure. However, in many utilities, in-network metering is minimally present at just the inlets of subnetworks called District Metering Area (DMA). We consider the problem of leak localization using data from a single flow meter placed at the inlet of a DMA. We use standard time-series based modeling to detect if a current meter reading is a leak or not, and if so, to estimate the excess flow. Conventional approaches use an a-priori fully calibrated hydraulic model to map the excess flow back to a set of candidate leak locations. However, obtaining an accurate hydraulic model is expensive and hence, beyond the reach of many water utilities. We present an alternate approach that exploits the network structure and static properties in a novel way. Specifically, we extend the use of centrality metrics to infrastructure domains and use these metrics to map from the excess leak flow to the candidate leak location(s). We evaluate our approach on benchmark water utility network topologies as well as on real data obtained from an European water utility. On benchmark topologies, the localization obtained by our method is comparable to that obtained from a complete hydraulic model. On a real-world network, we were able to localize two out of the three leaks whose data we had access to. Of these two cases, we find that the actual leak location was in the candidate set identified by our approach; further, the approach pruned as much as 78% of the DMA locations, indicating a high degree of localization.
{"title":"One meter to find them all-water network leak localization using a single flow meter","authors":"Iyswarya Narayanan, Arunchandar Vasan, V. Sarangan, A. Sivasubramaniam","doi":"10.1109/IPSN.2014.6846740","DOIUrl":"https://doi.org/10.1109/IPSN.2014.6846740","url":null,"abstract":"Leak localization is a major issue faced by water utilities worldwide. Leaks are ideally detected and localized by a network-wide metering infrastructure. However, in many utilities, in-network metering is minimally present at just the inlets of subnetworks called District Metering Area (DMA). We consider the problem of leak localization using data from a single flow meter placed at the inlet of a DMA. We use standard time-series based modeling to detect if a current meter reading is a leak or not, and if so, to estimate the excess flow. Conventional approaches use an a-priori fully calibrated hydraulic model to map the excess flow back to a set of candidate leak locations. However, obtaining an accurate hydraulic model is expensive and hence, beyond the reach of many water utilities. We present an alternate approach that exploits the network structure and static properties in a novel way. Specifically, we extend the use of centrality metrics to infrastructure domains and use these metrics to map from the excess leak flow to the candidate leak location(s). We evaluate our approach on benchmark water utility network topologies as well as on real data obtained from an European water utility. On benchmark topologies, the localization obtained by our method is comparable to that obtained from a complete hydraulic model. On a real-world network, we were able to localize two out of the three leaks whose data we had access to. Of these two cases, we find that the actual leak location was in the candidate set identified by our approach; further, the approach pruned as much as 78% of the DMA locations, indicating a high degree of localization.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114104597","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 : 2014-04-15DOI: 10.1109/IPSN.2014.6846764
Yixin Zheng, Linglong Li, Lin Zhang
PiMiair.org is a participatory indoor air quality data sharing project we launched in January 2014. Over 200 PiMi air boxes, a low-cost indoor air quality monitor, were given out to volunteer users across China. The PiMi air boxes measure the approximate indoor particulate matter concentration, and the ambient temperate and humidity. When a user accesses the PiMi air box for his personal air quality data on his smartphone, the data is relayed to the backend PiMi cloud server for analysis. Accumulating large amount of indoor air quality data under different circumstances, the PiMi cloud server is able to use statistical learning methodologies to detect point of interests (POIs) in the data series, and asks users to label their activities or events at the POIs. Together with the user-reported physicality information on the indoor environments, PiMiair.org is able to quantitatively evaluate the impacts of the environment physicality and human behaviors on the indoor air quality, and mine the knowledges on how to alleviate indoor air pollution. We believe that by sharing these knowledge among the community, healthier breathing environments could be nurtured for the well-being of the public.
{"title":"Poster abstract: PiMi air community: Getting fresher indoor air by sharing data and know-hows","authors":"Yixin Zheng, Linglong Li, Lin Zhang","doi":"10.1109/IPSN.2014.6846764","DOIUrl":"https://doi.org/10.1109/IPSN.2014.6846764","url":null,"abstract":"PiMiair.org is a participatory indoor air quality data sharing project we launched in January 2014. Over 200 PiMi air boxes, a low-cost indoor air quality monitor, were given out to volunteer users across China. The PiMi air boxes measure the approximate indoor particulate matter concentration, and the ambient temperate and humidity. When a user accesses the PiMi air box for his personal air quality data on his smartphone, the data is relayed to the backend PiMi cloud server for analysis. Accumulating large amount of indoor air quality data under different circumstances, the PiMi cloud server is able to use statistical learning methodologies to detect point of interests (POIs) in the data series, and asks users to label their activities or events at the POIs. Together with the user-reported physicality information on the indoor environments, PiMiair.org is able to quantitatively evaluate the impacts of the environment physicality and human behaviors on the indoor air quality, and mine the knowledges on how to alleviate indoor air pollution. We believe that by sharing these knowledge among the community, healthier breathing environments could be nurtured for the well-being of the public.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124270957","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 : 2014-04-15DOI: 10.1109/IPSN.2014.6846782
Dong Yang, Hongchao Wang, T. Zheng, Hongke Zhang, M. Gidlund, Youzhi Xu
Despite lots of research efforts in the area of Industrial Wireless Sensor Networks (IWSNs), there is a lack of really practical IWSN implementations, deployments and in-field experiments. This demo presents the design and implementation of an IWSN for welder machine systems based on the first IWSN standard WirelessHART. The goal of this work is to find the problems and challenges from IWSN standard to implementation, and motivate other designers to explore more IWSN applications.
{"title":"Demonstration abstract: Applying industrial wireless sensor networks to welder machine system","authors":"Dong Yang, Hongchao Wang, T. Zheng, Hongke Zhang, M. Gidlund, Youzhi Xu","doi":"10.1109/IPSN.2014.6846782","DOIUrl":"https://doi.org/10.1109/IPSN.2014.6846782","url":null,"abstract":"Despite lots of research efforts in the area of Industrial Wireless Sensor Networks (IWSNs), there is a lack of really practical IWSN implementations, deployments and in-field experiments. This demo presents the design and implementation of an IWSN for welder machine systems based on the first IWSN standard WirelessHART. The goal of this work is to find the problems and challenges from IWSN standard to implementation, and motivate other designers to explore more IWSN applications.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125616331","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 : 2014-04-15DOI: 10.1109/IPSN.2014.6846798
Jian Wu, Zhanyu Wang, S. Raghuraman, B. Prabhakaran, R. Jafari
Motion capture plays an important role in interactive gaming, animation, film industry and navigation. The existing camera-based motion capture studios are expensive and require a clear line of sight; hence they cannot be applied to ubiquitous applications. With the rapid development of low-cost MEMS sensors and sensor fusion techniques, the inertial sensor based motion capture systems are attracting a lot of attention because of the seamless deployment, low system cost and the comparable accuracy they provide. In this paper, we demonstrate a wireless real-time inertial motion capture system.
{"title":"Demonstration abstract: Upper body motion capture system using inertial sensors","authors":"Jian Wu, Zhanyu Wang, S. Raghuraman, B. Prabhakaran, R. Jafari","doi":"10.1109/IPSN.2014.6846798","DOIUrl":"https://doi.org/10.1109/IPSN.2014.6846798","url":null,"abstract":"Motion capture plays an important role in interactive gaming, animation, film industry and navigation. The existing camera-based motion capture studios are expensive and require a clear line of sight; hence they cannot be applied to ubiquitous applications. With the rapid development of low-cost MEMS sensors and sensor fusion techniques, the inertial sensor based motion capture systems are attracting a lot of attention because of the seamless deployment, low system cost and the comparable accuracy they provide. In this paper, we demonstrate a wireless real-time inertial motion capture system.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133895781","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 : 2014-04-15DOI: 10.1109/IPSN.2014.6846786
Linglong Li, Yixin Zheng, Lin Zhang
Ultra-fine particles with aerodynamic diameter smaller than 2.5 microns, namely Particulate Matter 2.5 (PM 2.5), are capable of penetrating the lung cells and circulating the circulatory system, and compose a major health threat to people. Although the government is publishing the outdoor PM2.5 concentration on an hourly basis, the indoor PM 2.5 concentration, to which most people expose for most of their everyday life time, remains unsupervised. The high cost of the professional PM 2.5 measuring equipments, which utilize filtering and direct mass measuring methodology, prevents the indoor air quality to be monitored pervasively. We designed and implemented PiMi air box, a cost-effective portable sensor, which is able to estimate the PM 2.5 mass concentration with satisfactory accuracy. The PiMi air boxes adopt the low-cost optical particle counting technology and convert the particle counts into PM 2.5 mass concentration via empirical diameter-distribution and density of particulate matters. The errors introduced by the individuality of the low-cost particle counters are offset during a machine-learning-based calibration procedure for each single unit. The PiMi air box enjoys a stunning cost reduction by a factor of 1,000 comparing to professional equipments, and still maintains an satisfactory level of accuracy for everyday life air quality measurement. Together with embedded Bluetooth connectivity and SmartPhone APPs, PiMi air box is well-suited for massive crowd-sourced indoor air-quality monitoring research.
{"title":"Demonstration abstract: PiMi air box — A cost-effective sensor for participatory indoor quality monitoring","authors":"Linglong Li, Yixin Zheng, Lin Zhang","doi":"10.1109/IPSN.2014.6846786","DOIUrl":"https://doi.org/10.1109/IPSN.2014.6846786","url":null,"abstract":"Ultra-fine particles with aerodynamic diameter smaller than 2.5 microns, namely Particulate Matter 2.5 (PM 2.5), are capable of penetrating the lung cells and circulating the circulatory system, and compose a major health threat to people. Although the government is publishing the outdoor PM2.5 concentration on an hourly basis, the indoor PM 2.5 concentration, to which most people expose for most of their everyday life time, remains unsupervised. The high cost of the professional PM 2.5 measuring equipments, which utilize filtering and direct mass measuring methodology, prevents the indoor air quality to be monitored pervasively. We designed and implemented PiMi air box, a cost-effective portable sensor, which is able to estimate the PM 2.5 mass concentration with satisfactory accuracy. The PiMi air boxes adopt the low-cost optical particle counting technology and convert the particle counts into PM 2.5 mass concentration via empirical diameter-distribution and density of particulate matters. The errors introduced by the individuality of the low-cost particle counters are offset during a machine-learning-based calibration procedure for each single unit. The PiMi air box enjoys a stunning cost reduction by a factor of 1,000 comparing to professional equipments, and still maintains an satisfactory level of accuracy for everyday life air quality measurement. Together with embedded Bluetooth connectivity and SmartPhone APPs, PiMi air box is well-suited for massive crowd-sourced indoor air-quality monitoring research.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"56 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120868777","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 : 2014-04-15DOI: 10.1109/IPSN.2014.6846792
Georgios Larkou, Marios Mintzis, Stefano Taranto, Andreas Konstantinidis, P. Andreou, D. Zeinalipour-Yazti
In this demonstration paper we present SmartLab1, an architecture for managing a cluster of both Android Real Devices (ARDs) and Android Virtual Devices (AVDs) via an intuitive web-based interface. Our architecture consists of several exciting components for re-programming and instrumenting smartphones to perform application testing and data gathering in a facile manner, as well as executing mockup experiments by “feeding” the devices with GPS/sensor readings. We will particularly demonstrate the various components of our architecture that encompasses smartphone sensor data collected by mobile users and organized in our distributed NoSQL document store. The given datasets can then be replayed on our testbed comprising of real and virtual smartphones accessible to developers through our Web 2.0 user interface. We present the applicability of our architecture through various mockup experiments over different application scenarios.
{"title":"Demonstration abstract: Sensor mockup experiments with SmartLab","authors":"Georgios Larkou, Marios Mintzis, Stefano Taranto, Andreas Konstantinidis, P. Andreou, D. Zeinalipour-Yazti","doi":"10.1109/IPSN.2014.6846792","DOIUrl":"https://doi.org/10.1109/IPSN.2014.6846792","url":null,"abstract":"In this demonstration paper we present SmartLab1, an architecture for managing a cluster of both Android Real Devices (ARDs) and Android Virtual Devices (AVDs) via an intuitive web-based interface. Our architecture consists of several exciting components for re-programming and instrumenting smartphones to perform application testing and data gathering in a facile manner, as well as executing mockup experiments by “feeding” the devices with GPS/sensor readings. We will particularly demonstrate the various components of our architecture that encompasses smartphone sensor data collected by mobile users and organized in our distributed NoSQL document store. The given datasets can then be replayed on our testbed comprising of real and virtual smartphones accessible to developers through our Web 2.0 user interface. We present the applicability of our architecture through various mockup experiments over different application scenarios.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"53 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120922182","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 : 2014-04-15DOI: 10.1109/IPSN.2014.6846770
Kamyar Niroumand, L. McNamara, Kiril Goguev, E. Ngai
People's moods and activities are heavily affected by their environment, which changes significantly throughout the year. The variable of daylight hours is huge for countries in extreme latitudes, impacting the population's health and well-being. In this paper, we present a smartphone application that efficiently and accurately measures a person's light exposure, mood and activity levels. We performed a preliminary study to show effective data collection using on-board sensors in the mobile phones.
{"title":"Poster abstract: SADSense: Personalized mobile sensing for seasonal effects on health","authors":"Kamyar Niroumand, L. McNamara, Kiril Goguev, E. Ngai","doi":"10.1109/IPSN.2014.6846770","DOIUrl":"https://doi.org/10.1109/IPSN.2014.6846770","url":null,"abstract":"People's moods and activities are heavily affected by their environment, which changes significantly throughout the year. The variable of daylight hours is huge for countries in extreme latitudes, impacting the population's health and well-being. In this paper, we present a smartphone application that efficiently and accurately measures a person's light exposure, mood and activity levels. We performed a preliminary study to show effective data collection using on-board sensors in the mobile phones.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125794916","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 : 2014-04-15DOI: 10.1109/IPSN.2014.6846785
Kyeong T. Min, A. Forys, T. Schmid
Solutions to outdoor air pollution require societal changes; however, we focus on indoor home air quality to allow for individual control over the breathing environment. We present AirFeed: a real time air quality monitoring system that provides measurements on particulate matter, temperature, and humidity. Interactions with users based on data analysis and user/sensor feedback form distinguishable patterns between several types of activities. We can better inform the user how daily habits affect living environments. Several deployments are actively collecting data for future data analysis and improved pattern recognition.
{"title":"Demonstration abstract: AirFeed — Indoor real time interactive air quality monitoring system","authors":"Kyeong T. Min, A. Forys, T. Schmid","doi":"10.1109/IPSN.2014.6846785","DOIUrl":"https://doi.org/10.1109/IPSN.2014.6846785","url":null,"abstract":"Solutions to outdoor air pollution require societal changes; however, we focus on indoor home air quality to allow for individual control over the breathing environment. We present AirFeed: a real time air quality monitoring system that provides measurements on particulate matter, temperature, and humidity. Interactions with users based on data analysis and user/sensor feedback form distinguishable patterns between several types of activities. We can better inform the user how daily habits affect living environments. Several deployments are actively collecting data for future data analysis and improved pattern recognition.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126129480","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 : 2014-04-01DOI: 10.1109/IPSN.2014.6846747
Zhuoling Xiao, Hongkai Wen, A. Markham, A. Trigoni
Indoor tracking and navigation is a fundamental need for pervasive and context-aware smartphone applications. Although indoor maps are becoming increasingly available, there is no practical and reliable indoor map matching solution available at present. We present MapCraft, a novel, robust and responsive technique that is extremely computationally efficient (running in under 10 ms on an Android smartphone), does not require training in different sites, and tracks well even when presented with very noisy sensor data. Key to our approach is expressing the tracking problem as a conditional random field (CRF), a technique which has had great success in areas such as natural language processing, but has yet to be considered for indoor tracking. Unlike directed graphical models like Hidden Markov Models, CRFs capture arbitrary constraints that express how well observations support state transitions, given map constraints. Extensive experiments in multiple sites show how MapCraft outperforms state-of-the art approaches, demonstrating excellent tracking error and accurate reconstruction of tortuous trajectories with zero training effort. As proof of its robustness, we also demonstrate how it is able to accurately track the position of a user from accelerometer and magnetometer measurements only (i.e. gyro- and WiFi-free). We believe that such an energy-efficient approach will enable always-on background localisation, enabling a new era of location-aware applications to be developed.
{"title":"Lightweight map matching for indoor localisation using conditional random fields","authors":"Zhuoling Xiao, Hongkai Wen, A. Markham, A. Trigoni","doi":"10.1109/IPSN.2014.6846747","DOIUrl":"https://doi.org/10.1109/IPSN.2014.6846747","url":null,"abstract":"Indoor tracking and navigation is a fundamental need for pervasive and context-aware smartphone applications. Although indoor maps are becoming increasingly available, there is no practical and reliable indoor map matching solution available at present. We present MapCraft, a novel, robust and responsive technique that is extremely computationally efficient (running in under 10 ms on an Android smartphone), does not require training in different sites, and tracks well even when presented with very noisy sensor data. Key to our approach is expressing the tracking problem as a conditional random field (CRF), a technique which has had great success in areas such as natural language processing, but has yet to be considered for indoor tracking. Unlike directed graphical models like Hidden Markov Models, CRFs capture arbitrary constraints that express how well observations support state transitions, given map constraints. Extensive experiments in multiple sites show how MapCraft outperforms state-of-the art approaches, demonstrating excellent tracking error and accurate reconstruction of tortuous trajectories with zero training effort. As proof of its robustness, we also demonstrate how it is able to accurately track the position of a user from accelerometer and magnetometer measurements only (i.e. gyro- and WiFi-free). We believe that such an energy-efficient approach will enable always-on background localisation, enabling a new era of location-aware applications to be developed.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128767947","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}
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