Proceedings of the 14th International Conference on Information Processing in Sensor Networks最新文献_第3页

Towards enabling concurrent transmissions in heterogeneous networks 在异构网络中实现并发传输

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI: 10.1145/2737095.2737164

Martina Brachmann, Dennis Becker, S. Santini

引用次数: 3

Health-optimal routing in urban areas 城市地区最健康的路线

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI: 10.1145/2737095.2737135

David Hasenfratz, Tabita Arn, Ivo de Concini, O. Saukh, L. Thiele

引用次数: 10

Hand hygiene duration and technique recognition using wrist-worn sensors 使用腕戴式传感器的手部卫生持续时间和技术识别

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI: 10.1145/2737095.2737106

V. Galluzzi, Ted Herman, P. Polgreen

{"title":"Hand hygiene duration and technique recognition using wrist-worn sensors","authors":"V. Galluzzi, Ted Herman, P. Polgreen","doi":"10.1145/2737095.2737106","DOIUrl":"https://doi.org/10.1145/2737095.2737106","url":null,"abstract":"Hand washing is an effective countermeasure to the spread of many types of infection. Recently, sensing technology has automated the sampling and study of hand hygiene rates. Surprisingly, many questions about the area are unresolved, motivating further exploration based on wrist-worn commodity sensors (accelerometer and MEMS gyroscope). This paper describes initial work on techniques for measuring the duration of washing events and classifying different scrubbing motions. The work compares different sensor types and their fusion, compares sensing from one wrist to measuring both wrists, and explains results of experiments on a range of hand washing motions in a variety of subject populations, some in clinics of a teaching hospital. Machine learning is used to explore such questions: the paper investigates numerous features extracted from sensor data, looking at sampling rates, windowing, and platform details that affect classification. In training and classification experiments, data collection starts on the wrist, activated by a message from a disinfectant dispenser; data is then transferred by radio to a base station for subsequent reduction, analysis and characterization. Results show that hand hygiene motions can be classified with up to 93% accuracy.","PeriodicalId":318992,"journal":{"name":"Proceedings of the 14th International Conference on Information Processing in Sensor Networks","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125255739","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: 30

A participatory transport trip quality measurement system 参与式交通出行质量测评体系

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI: 10.1145/2737095.2742013

Zhe Xiao, Lucien Loiseau, H. Lim

引用次数: 3

Reducing multi-hop calibration errors in large-scale mobile sensor networks 减少大规模移动传感器网络中的多跳校准误差

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI: 10.1145/2737095.2737113

O. Saukh, David Hasenfratz, L. Thiele

{"title":"Reducing multi-hop calibration errors in large-scale mobile sensor networks","authors":"O. Saukh, David Hasenfratz, L. Thiele","doi":"10.1145/2737095.2737113","DOIUrl":"https://doi.org/10.1145/2737095.2737113","url":null,"abstract":"Frequent sensor calibration is essential in sensor networks with low-cost sensors. We exploit the fact that temporally and spatially close measurements of different sensors measuring the same phenomenon are similar. Hence, when calibrating a sensor, we adjust its calibration parameters to minimize the differences between co-located measurements of previously calibrated sensors. In turn, freshly calibrated sensors can now be used to calibrate other sensors in the network, referred to as multi-hop calibration. We are the first to study multi-hop calibration with respect to a reference signal (micro-calibration) in detail. We show that ordinary least squares regression---commonly used to calibrate noisy sensors---suffers from significant error accumulation over multiple hops. In this paper, we propose a novel multi-hop calibration algorithm using geometric mean regression, which (i) highly reduces error propagation in the network, (ii) distinctly outperforms ordinary least squares in the multi-hop scenario, and (iii) requires considerably fewer ground truth measurements compared to existing network calibration algorithms. The proposed algorithm is especially valuable when calibrating large networks of heterogeneous sensors with different noise characteristics. We provide theoretical justifications for our claims. Then, we conduct a detailed analysis with artificial data to study calibration accuracy under various settings and to identify different error sources. Finally, we use our algorithm to accurately calibrate 13 million temperature, ground ozone (O3), and carbon monoxide (CO) measurements gathered by our mobile air pollution monitoring network.","PeriodicalId":318992,"journal":{"name":"Proceedings of the 14th International Conference on Information Processing in Sensor Networks","volume":" 20","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113949445","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: 98

CleanHands: an integrated monitoring system for control of hospital acquired infections 清洁之手:控制医院获得性感染的综合监测系统

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI: 10.1145/2737095.2742928

P. Misra, V. Rajaraman, Aishwarya S N, Bharat Dwivedi, J. Warrior

引用次数: 4

Radio-based device-free activity recognition with radio frequency interference 基于无线电的无设备活动识别与无线电频率干扰

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI: 10.1145/2737095.2737117

Bo Wei, W. Hu, Mingrui Yang, C. Chou

{"title":"Radio-based device-free activity recognition with radio frequency interference","authors":"Bo Wei, W. Hu, Mingrui Yang, C. Chou","doi":"10.1145/2737095.2737117","DOIUrl":"https://doi.org/10.1145/2737095.2737117","url":null,"abstract":"Activity recognition is an important component of many pervasive computing applications. Device-free activity recognition has the advantage that it does not have the privacy concern of using cameras and the subjects do not have to carry a device on them. Recently, it has been shown that channel state information (CSI) can be used for activity recognition in a device-free setting. With the proliferation of wireless devices, it is important to understand how radio frequency interference (RFI) can impact on pervasive computing applications. In this paper, we investigate the impact of RFI on device-free CSI-based location-oriented activity recognition. We conduct experiments in environments without and with RFI. We present data to show that RFI can have a significant impact on the CSI vectors. In the absence of RFI, different activities give rise to different CSI vectors that can be differentiated visually. However, in the presence of RFI, the CSI vectors become much noisier and activity recognition also becomes harder. Our extensive experiments shows that the performance of state-of-the-art classification methods may degrade significantly with RFI. We then propose a number of counter measures to mitigate the impact of RFI and improve the location-oriented activity recognition performance. Our evaluation shows the proposed method can improve up to 10% true detection rate in the presence of RFI. We also study the impact of bandwidth on activity recognition performance. We show that with a channel bandwidth of 20 MHz (which is used by WiFi), it is possible to achieve a good activity recognition accuracy when RFI is present.","PeriodicalId":318992,"journal":{"name":"Proceedings of the 14th International Conference on Information Processing in Sensor Networks","volume":"73 Pt B 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116527568","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: 69

Detecting malicious morphological alterations of ECG signals in body sensor networks 在人体传感器网络中检测心电信号的恶意形态改变

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI: 10.1145/2737095.2742930

Hang Cai, K. Venkatasubramanian

引用次数: 7

Debiasing crowdsourced quantitative characteristics in local businesses and services 消除本地企业和服务的众包数量特征

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI: 10.1145/2737095.2737116

W. Ouyang, Lance M. Kaplan, Paul D. Martin, Alice Toniolo, M. Srivastava, T. Norman

{"title":"Debiasing crowdsourced quantitative characteristics in local businesses and services","authors":"W. Ouyang, Lance M. Kaplan, Paul D. Martin, Alice Toniolo, M. Srivastava, T. Norman","doi":"10.1145/2737095.2737116","DOIUrl":"https://doi.org/10.1145/2737095.2737116","url":null,"abstract":"Information about quantitative characteristics in local businesses and services, such as the number of people waiting in line in a cafe and the number of available fitness machines in a gym, is important for informed decision, crowd management and event detection. In this paper, we investigate the potential of leveraging crowds as sensors to report such quantitative characteristics and investigate how to recover the true quantity values from noisy crowdsourced information. Through experiments, we find that crowd sensors have both bias and variance in quantity sensing, and task difficulties impact the sensing accuracy. Based on these findings, we propose an unsupervised probabilistic model to jointly assess task difficulties, ability of crowd sensors and true quantity values. Our model differs from existing categorical truth finding models as ours is specifically designed to tackle quantitative truth. In addition to devising an efficient model inference algorithm in a batch mode, we also design an even faster online version for handling streaming data. Experimental results in various scenarios demonstrate the effectiveness of our model.","PeriodicalId":318992,"journal":{"name":"Proceedings of the 14th International Conference on Information Processing in Sensor Networks","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129373729","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: 38

Design insights for a mobile based sensor application framework: for aiding platform independent algorithm design 基于移动传感器应用框架的设计见解:用于辅助平台无关算法设计

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI: 10.1145/2737095.2737149

Avik Ghose, S. Alam, Nasimuddin Ahmed, Santa Maiti, A. Choudhury, A. Pal

引用次数: 3