{"title":"Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks","authors":"Pei Zhang, P. Dutta, G. Xing","doi":"10.1145/3055031","DOIUrl":"https://doi.org/10.1145/3055031","url":null,"abstract":"It is my great pleasure to welcome you to the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN 2017). This year, IPSN continues a tradition of being one of the premier events that brings together researchers and professionals from academia, industry, and government to address the array of current challenges, to discover new challenges, and expand the concepts of sensor networks. This year is the 10th year that IPSN has been part of CPS Week. Together with our four sister conferences---HSCC, ICCPS, IoTDI, and RTAS---and an array of workshops, all participants can explore various aspects of research and development in Cyber-Physical Systems including Embedded Systems, Hybrid Systems, Real-Time Systems, Internet of Things, and Sensor Networks.","PeriodicalId":206082,"journal":{"name":"Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130968653","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}
Mahdi Pedram, Seyed Ali Rokni, Ramin Fallahzadeh, Hassan Ghasemzadeh
{"title":"A beverage intake tracking system based on machine learning algorithms, and ultrasonic and color sensors: poster abstract","authors":"Mahdi Pedram, Seyed Ali Rokni, Ramin Fallahzadeh, Hassan Ghasemzadeh","doi":"10.1145/3055031.3055065","DOIUrl":"https://doi.org/10.1145/3055031.3055065","url":null,"abstract":"We present a novel approach for monitoring beverage intake. Our system is composed of an ultrasonic sensor, an RGB color sensor, and machine learning algorithms. The system not only measures beverage volume but also detects beverage types. The sensor unit is lightweight that can be mounted on the lid of any drinking bottle. Our experimental results demonstrate that the proposed approach achieves more than 97% accuracy in beverage type classification. Furthermore, our regression-based volume measurement has a nominal error of 3%.","PeriodicalId":206082,"journal":{"name":"Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124955662","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":"Empirical research on behavior change promoted by information technology: poster abstract","authors":"Yutaka Arakawa","doi":"10.1145/3055031.3055068","DOIUrl":"https://doi.org/10.1145/3055031.3055068","url":null,"abstract":"This paper shows the concept and design of an ongoing project about \"behavior change\", that is one of the keywords for realizing a sustainable society based on information technology such as IoT and AI. \"Stand\" function that Apple Watch has is a touchstone of the arrival of a new age. The watch commands a human to stand up or meditate. It is a start of intervention to our behavior from AI. However, it is not so bad because we know that this suggestion must be good for our health. Based on this experience, we started an empirical research on behavior change that consists of activity recognition, just-in-time intervention, and gamification.","PeriodicalId":206082,"journal":{"name":"Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126359715","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":"Zoning by mobility: evaluating city administrative regions by taxi data: poster abstract","authors":"Liandong Zhou, Shao-Lun Huang, Lin Zhang","doi":"10.1145/3055031.3055053","DOIUrl":"https://doi.org/10.1145/3055031.3055053","url":null,"abstract":"The accelerating urbanization procedure is putting increasing pressure on the management of cities. The administrative zones by which a city is managed are setup based on historical or political reasons, while the dynamics of people is hardly considered in the context. We exploit the widely available mobility data to divide the urban areas into zones by the joint K-mean clustering in origin and destination spaces. The method is evaluated with the New York City and Shenzhen taxi data, and the created zones are compared with the current static zoning plans of the city to evaluate the effectiveness.","PeriodicalId":206082,"journal":{"name":"Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115627904","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}
S. Preum, M. A. S. Mondol, Meiyi Ma, Hongning Wang, J. Stankovic
{"title":"Conflict detection in online textual health advice: demo abstract","authors":"S. Preum, M. A. S. Mondol, Meiyi Ma, Hongning Wang, J. Stankovic","doi":"10.1145/3055031.3055038","DOIUrl":"https://doi.org/10.1145/3055031.3055038","url":null,"abstract":"Textual health advice generated from different online sources (e.g., health apps and websites) can be conflicting. Conflicts can occur due to lexical features, (such as, negation, antonyms, or numerical mismatch) or can be conditioned upon time and/or physiological status. Detecting conflicts from textual health advice poses several challenges, including, large structural variation between text and hypothesis pairs, finding conceptual overlap between pairs of advice, and inference of the semantics of an advice (i.e., what to do, why, and how). In this demonstration, we present a semantic rule-based system to detect different types of conflicts in online textual health advice statements in a context-aware and interpretable manner.","PeriodicalId":206082,"journal":{"name":"Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks","volume":"213 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114358492","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}
Philipp H. Kindt, Nils Heitmann, Daniel Yunge, S. Chakraborty
{"title":"Understanding slotless neighbor discovery: demo abstract","authors":"Philipp H. Kindt, Nils Heitmann, Daniel Yunge, S. Chakraborty","doi":"10.1145/3055031.3055036","DOIUrl":"https://doi.org/10.1145/3055031.3055036","url":null,"abstract":"The process of two wireless devices meeting over-the-air for the first time is referred to as neighbor discovery. In mobile ad-hoc networks, battery powered devices duty-cycle their radios during neighbor discovery. As a result, they transmit and receive for very short durations of time and sleep at other times. Energy-efficient protocols, which guarantee short, bounded latencies while achieving low energy-consumptions are highly important for long battery lifetimes. In the past, neighbor discovery has been carried out mostly using slotted protocols, which subdivide time into multiple, equal length periods, called slots. An alternative are slotless protocols, which decouple beaconing from listening and can potentially achieve lower latency-duty-cycle-relations. As in slotted protocols, they also guarantee bounded latencies. However, understanding the mechanisms that ensure these deterministic bounds is more complex than for slotted protocols, since they rely on less intuitive concepts. In this demo, we propose a setup that visualizes the operation of two radios with slotless protocols in real-time, thereby providing insights that help in understanding slotless neighbor discovery. This demo is supposed to accompany the paper entitled \"Griassdi: Mutually Assisted Slotless Neighbor Discovery Protocols\", which appeared at IPSN 2017 as a regular paper.","PeriodicalId":206082,"journal":{"name":"Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks","volume":"278 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116199167","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":"An adaptive-delay transmission strategy of a fixed-interval wireless reporting application: poster abstract","authors":"Pai-Kun Huang, K. Cheng, Huang-Chen Lee","doi":"10.1145/3055031.3055055","DOIUrl":"https://doi.org/10.1145/3055031.3055055","url":null,"abstract":"Low-power wireless technology, i.e., IEEE 802.15.4, consumes less energy and is suitable for battery-powered applications; fixed-interval data reporting is a common characteristic of these applications, e.g., a wireless sensor needs to report its temperature or air quality every minute. However, data-receiving failure occurs frequently because the output power of such wireless technology is low, typically 1 mW in 2.4 GHz IEEE 802.15.4; also, crowd wireless traffic on ISM 2.4 GHz usually has serious radio interference. Meanwhile, data sent from a wireless transmitter but is not received by a receiver is not only wasted energy but also causes potential radio interference with other wireless devices. Based on the observation of radio interference, we proposed an adaptive-delay transmission mechanism for increasing the energy efficiency and the packet delivery ratio of the fixed-interval reporting application. The timing of data reporting is adaptively postponed if the recent transmissions fail. By integrating this method, the number of data packet been sent is reduced by up to 42.7% in a high-interference period; therefore, the power consumption of the wireless transmitter is reduced.","PeriodicalId":206082,"journal":{"name":"Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132575323","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":"Range-based localization in underwater wireless sensor networks using deep neural network: poster abstract","authors":"Yuhan Dong, Zheng Li, Rui Wang, Kai Zhang","doi":"10.1145/3055031.3055069","DOIUrl":"https://doi.org/10.1145/3055031.3055069","url":null,"abstract":"In underwater wireless sensor networks (USWNs), localizing unknown nodes is essential for most applications while is more complex than that of terrestrial WSNs. In this paper, we propose a range-based localization scheme using deep neural network (DNN). Numerical results suggest that the proposed DNN localization algorithm outperforms traditional schemes using least squares support vector machines (LS-SVM) or generalized least squares (GLS) in terms of localization accuracy and efficiency. Moreover, the proposed algorithm requires a small number of anchor nodes, which is plausible for practical applications.","PeriodicalId":206082,"journal":{"name":"Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126581621","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}
Kin Sum Liu, Sirajum Munir, Jonathan M Francis, Charles Shelton, Shan Lin
{"title":"Long term occupancy estimation in a commercial space: an empirical study: poster abstract","authors":"Kin Sum Liu, Sirajum Munir, Jonathan M Francis, Charles Shelton, Shan Lin","doi":"10.1145/3055031.3055062","DOIUrl":"https://doi.org/10.1145/3055031.3055062","url":null,"abstract":"Understanding occupancy patterns in a building is very useful to control HVAC systems for improving energy efficiency of the building and occupant comfort. There has been a very little attempt to understand long term occupancy patterns in a commercial space. In this work, we leverage depth sensors (Kinect for XBOX One) to collect occupancy count from an 11,000 square foot commercial space (Bosch office) for nine months. We analyze the collected data and describe key findings that provide deep insights about how a commercial space is used and serve as a guideline to formulate novel and efficient control strategies.","PeriodicalId":206082,"journal":{"name":"Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121506816","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":"Heart and sole - shoe-based heart monitoring: demo abstract","authors":"Amelie Bonde, Shijia Pan, H. Noh, Pei Zhang","doi":"10.1145/3055031.3055048","DOIUrl":"https://doi.org/10.1145/3055031.3055048","url":null,"abstract":"We present Heart and Sole, a shoe-based system that can track a subject's pulse through their feet. Heart rate monitoring can be used to enhance athletic training and assess risk for several health conditions, such as cardiovascular risk and Parkinson's Disease. Many solutions have been proposed to track people's heart rates in their daily lives, but none of them follow the user around without requiring the user to wear special devices. By incorporating sensors into shoes that the user already wears in everyday life, we can create a ubiquitous heart-monitoring system that follows the user around but also remains ambient in the environment. The sensors lie against the foot as part of the tongue of the shoe. The challenge is to differentiate the weak signal induced by arterial motion from the signal noise caused by musculoskeletal movement. Heart and Sole addresses this by amplifying the signal and identifying low motion points where we can more easily extract the signal. Our demo will have a demonstrator wearing a shoe with such a sensor in it, and demonstrating that their measured pulse matches up with the one being measured by our ground truth, a pulse oximeter.","PeriodicalId":206082,"journal":{"name":"Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127264961","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}