Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing最新文献_第7页

Passive and contactless epidermal pressure sensor printed with silver nano-particle ink 用纳米银颗粒油墨印刷的无源非接触式表皮压力传感器

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971705

T. Hashizume, T. Sasatani, Koya Narumi, Yoshiaki Narusue, Y. Kawahara, T. Asami

引用次数: 11

Characterizing the life cycle of point of interests using human mobility patterns 利用人类流动模式描述兴趣点的生命周期

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971749

Xinjiang Lu, Zhiwen Yu, Leilei Sun, Chuanren Liu, Hui Xiong, Chu Guan

{"title":"Characterizing the life cycle of point of interests using human mobility patterns","authors":"Xinjiang Lu, Zhiwen Yu, Leilei Sun, Chuanren Liu, Hui Xiong, Chu Guan","doi":"10.1145/2971648.2971749","DOIUrl":"https://doi.org/10.1145/2971648.2971749","url":null,"abstract":"A Point of Interest (POI) refers to a specific location that people may find useful or interesting. While a large body of research has been focused on identifying and recommending POIs, there are few studies on characterizing the life cycle of POIs. Indeed, a comprehensive understanding of POI life cycle can be helpful for various tasks, such as urban planning, business site selection, and real estate evaluation. In this paper, we develop a framework, named POLIP, for characterizing the POI life cycle with multiple data sources. Specifically, to investigate the POI evolution process over time, we first formulate a serial classification problem to predict the life status of POIs. The prediction approach is designed to integrate two important perspectives: 1) the spatial-temporal dependencies associated with the prosperity of POIs, and 2) the human mobility dynamics hidden in the citywide taxicab data related to the POIs at multiple granularity levels. In addition, based on the predicted life statuses in successive time windows for a given POI, we design an algorithm to characterize its life cycle. Finally, we performed extensive experiments using large-scale and real-world datasets. The results demonstrate the feasibility in automatic characterizing POI life cycle and shed important light on future research directions.","PeriodicalId":303792,"journal":{"name":"Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133730532","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: 19

Predicting user error for ambient systems by integrating model-based UI development and cognitive modeling 通过集成基于模型的UI开发和认知建模来预测环境系统的用户错误

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971667

M. Halbrügge, Michael Quade, Klaus-Peter Engelbrecht, S. Möller, S. Albayrak

引用次数: 4

Genie: a longitudinal study comparing physical and software thermostats in office buildings Genie:一项比较办公大楼中物理和软件恒温器的纵向研究

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971719

Bharathan Balaji, Jason Koh, Nadir Weibel, Yuvraj Agarwal

{"title":"Genie: a longitudinal study comparing physical and software thermostats in office buildings","authors":"Bharathan Balaji, Jason Koh, Nadir Weibel, Yuvraj Agarwal","doi":"10.1145/2971648.2971719","DOIUrl":"https://doi.org/10.1145/2971648.2971719","url":null,"abstract":"Thermostats are the primary interface for occupants of office buildings to express their thermal comfort preferences. However, traditional thermostats are often ineffective due to physical inaccessibility, lack of information or limited responsiveness, which lead to occupant discomfort. Modern thermostat designs do overcome some of these limitations, but retrofitting them to existing buildings is prohibitively expensive. Software thermostats based on web or smartphone apps provide an alternate interaction mechanism with minimal deployment cost. However, their usage and effectiveness have not been studied extensively in real settings. We present Genie, a novel software thermostat that we designed and deployed in our university for over 21 months. We compare the use of Genie to traditional thermostats. Our data and user study show that due to the clarity of information and wider thermal control provided by Genie, users feel more comfortable in their offices. Furthermore, the improved comfort did not affect the overall energy consumption or lead to misuse of HVAC controls.","PeriodicalId":303792,"journal":{"name":"Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116233816","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: 18

Automated estimation of food type and amount consumed from body-worn audio and motion sensors 通过佩戴的声音和运动传感器自动估计食物类型和消耗的数量

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971677

Mark Mirtchouk, Christopher A. Merck, Samantha Kleinberg

{"title":"Automated estimation of food type and amount consumed from body-worn audio and motion sensors","authors":"Mark Mirtchouk, Christopher A. Merck, Samantha Kleinberg","doi":"10.1145/2971648.2971677","DOIUrl":"https://doi.org/10.1145/2971648.2971677","url":null,"abstract":"Determining when an individual is eating can be useful for tracking behavior and identifying patterns, but to create nutrition logs automatically or provide real-time feedback to people with chronic disease, we need to identify both what they are consuming and in what quantity. However, food type and amount have mainly been estimated using image data (requiring user involvement) or acoustic sensors (tested with a restricted set of foods rather than representative meals). As a result, there is not yet a highly accurate automated nutrition monitoring method that can be used with a variety of foods. We propose that multi-modal sensing (in-ear audio plus head and wrist motion) can be used to more accurately classify food type, as audio and motion features provide complementary information. Further, we propose that knowing food type is critical for estimating amount consumed in combination with sensor data. To test this we use data from people wearing audio and motion sensors, with ground truth annotated from video and continuous scale data. With data from 40 unique foods we achieve a classification accuracy of 82.7% with a combination of sensors (versus 67.8% for audio alone and 76.2% for head and wrist motion). Weight estimation error was reduced from a baseline of 127.3% to 35.4% absolute relative error. Ultimately, our estimates of food type and amount can be linked to food databases to provide automated calorie estimates from continuously-collected data.","PeriodicalId":303792,"journal":{"name":"Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123619563","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: 94

Device-free detection of approach and departure behaviors using backscatter communication 利用反向散射通信对接近和离开行为进行无设备检测

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971699

H. Ding, Chen Qian, Jinsong Han, Ge Wang, Zhiping Jiang, Jizhong Zhao, Wei Xi

{"title":"Device-free detection of approach and departure behaviors using backscatter communication","authors":"H. Ding, Chen Qian, Jinsong Han, Ge Wang, Zhiping Jiang, Jizhong Zhao, Wei Xi","doi":"10.1145/2971648.2971699","DOIUrl":"https://doi.org/10.1145/2971648.2971699","url":null,"abstract":"Smart environments and security systems require automatic detection of human behaviors including approaching to or departing from an object. Existing human motion detection systems usually require human beings to carry special devices, which limits their applications. In this paper, we present a system called APID to detect arm reaching by analyzing backscatter communication signals from a passive RFID tag on the object. APID does not require human beings to carry any device. The idea is based on the influence of human movements to the vibration of backscattered tag signals. APID is compatible with commodity off-the-shelf devices and the EPCglobal Class-1 Generation-2 protocol. In APID an commercial RFID reader continuously queries tags through emitting RF signals and tags simply respond with their IDs. A USRP monitor passively analyzes the communication signals and reports the approach and departure behaviors. We have implemented the APID system for both single-object and multi-object scenarios in both horizontal and vertical deployment modes. The experimental results show that APID can achieve high detection accuracy.","PeriodicalId":303792,"journal":{"name":"Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123165760","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: 20

Apps to measure motor skills of vocational workers 测量职业工人运动技能的应用程序

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971739

Bhanu Pratap Singh Rawat, V. Aggarwal

引用次数: 1

EDUM: classroom education measurements via large-scale WiFi networks EDUM:通过大规模WiFi网络进行课堂教育测量

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971657

Mengyu Zhou, Minghua Ma, Yangkun Zhang, Kaixin Sui, Dan Pei, T. Moscibroda

引用次数: 44

WritingHacker: audio based eavesdropping of handwriting via mobile devices WritingHacker:通过移动设备音频窃听笔迹

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971681

Tuo Yu, Haiming Jin, K. Nahrstedt

{"title":"WritingHacker: audio based eavesdropping of handwriting via mobile devices","authors":"Tuo Yu, Haiming Jin, K. Nahrstedt","doi":"10.1145/2971648.2971681","DOIUrl":"https://doi.org/10.1145/2971648.2971681","url":null,"abstract":"When filling out privacy-related forms in public places such as hospitals or clinics, people usually are not aware that the sound of their handwriting leaks personal information. In this paper, we explore the possibility of eavesdropping on handwriting via nearby mobile devices based on audio signal processing and machine learning. By presenting a proof-of-concept system, WritingHacker, we show the usage of mobile devices to collect the sound of victims' handwriting, and to extract handwriting-specific features for machine learning based analysis. WritingHacker focuses on the situation where the victim's handwriting follows certain print style. An attacker can keep a mobile device, such as a common smart-phone, touching the desk used by the victim to record the audio signals of handwriting. Then the system can provide a word-level estimate for the content of the handwriting. To reduce the impacts of various writing habits and writing locations, the system utilizes the methods of letter clustering and dictionary filtering. Our prototype system's experimental results show that the accuracy of word recognition reaches around 50% - 60% under certain conditions, which reveals the danger of privacy leakage through the sound of handwriting.","PeriodicalId":303792,"journal":{"name":"Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126236196","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: 60

Towards area classification for large-scale fingerprint-based system 面向大规模指纹识别系统的区域分类

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Pub Date : 2016-09-12 DOI: 10.1145/2971648.2971689

Suining He, Jiajie Tan, S. Chan

{"title":"Towards area classification for large-scale fingerprint-based system","authors":"Suining He, Jiajie Tan, S. Chan","doi":"10.1145/2971648.2971689","DOIUrl":"https://doi.org/10.1145/2971648.2971689","url":null,"abstract":"In spacious and multi-area buildings, fingerprint-based localization often suffers from expensive location search. Besides, context knowledge like inside/outside-region and floor area is important for complete location service. To address above issues, beyond the algorithms finding the exact location point, we study accurate and efficient indoor area classification for large-scale fingerprint-based system. We first study leveraging the one-class classification to conduct inside/outside-region detection given only the inside fingerprints. Then we discuss different area determination algorithms, and compare their detection accuracy and deployment efficiency. To further enhance accuracy, we also discuss rejecting unclassifiable signals and calibrating heterogeneous devices. We have implemented different algorithms on Android platforms. Experimental trials (totally over 30,000 fingerprints and 15,000 test data) at an international airport, a business building, a premium shopping mall and a university campus have evaluated practicability and deployability of different classification schemes. Our studies can also serve as design guidelines for area classification.","PeriodicalId":303792,"journal":{"name":"Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124731185","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: 20