Proceedings of the 14th International Conference on Information Processing in Sensor Networks最新文献_第2页

Samba

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI: 10.1145/2737095.2737100

Yu Wang, R. Tan, G. Xing, Jianxun Wang, Xiaobo Tan, Xiaoming Liu

{"title":"Samba","authors":"Yu Wang, R. Tan, G. Xing, Jianxun Wang, Xiaobo Tan, Xiaoming Liu","doi":"10.1145/2737095.2737100","DOIUrl":"https://doi.org/10.1145/2737095.2737100","url":null,"abstract":"Monitoring aquatic environment is of great interest to the ecosystem, marine life, and human health. This paper presents the design and implementation of Samba -- an aquatic surveillance robot that integrates an off-the-shelf Android smartphone and a robotic fish to monitor harmful aquatic processes such as oil spill and harmful algal blooms. Using the built-in camera of on-board smartphone, Samba can detect spatially dispersed aquatic processes in dynamic and complex environments. To reduce the excessive false alarms caused by the non-water area (e.g., trees on the shore), Samba segments the captured images and performs target detection in the identified water area only. However, a major challenge in the design of Samba is the high energy consumption resulted from the continuous image segmentation. We propose a novel approach that leverages the power-efficient inertial sensors on smartphone to assist the image processing. In particular, based on the learned mapping models between inertial and visual features, Samba uses real-time inertial sensor readings to estimate the visual features that guide the image segmentation, significantly reducing energy consumption and computation overhead. Samba also features a set of lightweight and robust computer vision algorithms, which detect harmful aquatic processes based on their distinctive color features. Lastly, Samba employs a feedback-based rotation control algorithm to adapt to spatiotemporal evolution of the target aquatic process. We have implemented a Samba prototype and evaluated it through extensive field experiments, lab experiments, and trace-driven simulations. The results show that Samba can achieve 94% detection rate, 5% false alarm rate, and a lifetime up to nearly two months.","PeriodicalId":318992,"journal":{"name":"Proceedings of the 14th International Conference on Information Processing in Sensor Networks","volume":"126 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":"115256294","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: 7

How hot is piping hot?: lower energy consumption with smarter hot water delivery 滚烫有多热?:更智能的热水输送，降低能源消耗

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI: 10.1145/2737095.2737112

Yong Sun, Md Anindya Prodhan, Erin Griffiths, K. Whitehouse

{"title":"How hot is piping hot?: lower energy consumption with smarter hot water delivery","authors":"Yong Sun, Md Anindya Prodhan, Erin Griffiths, K. Whitehouse","doi":"10.1145/2737095.2737112","DOIUrl":"https://doi.org/10.1145/2737095.2737112","url":null,"abstract":"In typical US homes, water heating is the largest energy consumer besides space heating and cooling, and it accounts for approximately 17% of residential energy consumption on average. In this paper, we propose and evaluate a new technique to reduce energy waste due to pipe loss: delivering lower temperature water whenever possible. We created a Smarter Water Heater (SWH) that uses data fusion techniques to infer 1) the fixture being used 2) the mixed water temperature at the fixture 3) the pipe volume for that fixture. After learning a model for each fixture, it solves a control optimization problem to decide when and at what temperature to deliver water to minimize energy use without sacrificing comfort of the user. We evaluated the SWH in three stages. First, we built a physical prototype and measured energy efficiency. We then deployed 18 sensors into a home's piping system for a 50-day in-situ study to stress test the SWH's sensing sub-system. Finally, we collected traces of hot water use from 5 different homes over 10 days each to determine how different water usage habits and piping structures affect energy savings. The results indicate that the SWH reduces total water heating energy by 8--14% with little to no effect on user comfort.","PeriodicalId":318992,"journal":{"name":"Proceedings of the 14th International Conference on Information Processing in Sensor Networks","volume":"114 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":"134341593","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: 3

Structural sensing system with networked dynamic sensing configuration 具有网络化动态传感配置的结构传感系统

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI: 10.1145/2737095.2737147

Shijia Pan, Mostafa Mirshekari, H. Noh, Pei Zhang

引用次数: 5

Proceedings of the 14th International Conference on Information Processing in Sensor Networks 第十四届传感器网络信息处理国际会议论文集

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI: 10.1145/2737095

Suman Nath, B. Krishnamachari, Anthony G. Rowe

引用次数: 0

Wake-up flooding: an asynchronous network flooding primitive 唤醒泛洪:一个异步网络泛洪原语

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI: 10.1145/2737095.2737159

Felix Sutton, L. Thiele

引用次数: 2

SiCILIA: a smart sensor system for clothing insulation inference using heat exchange SiCILIA:一种智能传感器系统，用于通过热交换推断服装绝缘

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI: 10.1145/2737095.2742934

A. Shaabana, Rong Zheng, Zhipeng Xu

引用次数: 2

Radio signature based posture recognition using WBSN 基于无线信号的WBSN姿态识别

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI: 10.1145/2737095.2737141

A. Aulery, C. Roland, J. Diguet, Zhongwei Zheng, O. Sentieys, P. Scalart

引用次数: 2

Predictable wireless embedded platforms 可预测的无线嵌入式平台

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI: 10.1145/2737095.2737156

Felix Sutton, Reto Da Forno, Marco Zimmerling, R. Lim, Tonio Gsell, F. Ferrari, J. Beutel, L. Thiele

引用次数: 0

RAMP: accelerating wireless sensor hardware design with a reconfigurable analog/mixed-signal platform RAMP:通过可重构的模拟/混合信号平台加速无线传感器硬件设计

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI: 10.1145/2737095.2737107

B. Rumberg, D. Graham, Spencer Clites, Brandon M. Kelly, M. M. Navidi, Alexander T. Dilello, V. Kulathumani

{"title":"RAMP: accelerating wireless sensor hardware design with a reconfigurable analog/mixed-signal platform","authors":"B. Rumberg, D. Graham, Spencer Clites, Brandon M. Kelly, M. M. Navidi, Alexander T. Dilello, V. Kulathumani","doi":"10.1145/2737095.2737107","DOIUrl":"https://doi.org/10.1145/2737095.2737107","url":null,"abstract":"The requirements of many wireless sensing applications approach, or even exceed, the limited hardware capabilities of energy-constrained sensing platforms. To achieve such demanding requirements, some sensing platforms have included low-power application-specific hardware---at the expense of generality---to pre-process the sensor data for reduction to only the relevant information. While this additional hardware can save power by reducing the activity of the microcontroller and radio, a unique hardware solution is required for each application, which presents an unrealistic burden in terms of design time, cost, and ease of integration. To diminish these burdens, we present a reconfigurable analog/mixed-signal sensing platform in this work. At the hardware-level, this platform consists of a reconfigurable integrated circuit containing many commonly used signal-processing blocks and circuit components that can be connected in any configuration. At the software level, this platform provides a framework for abstracting this underlying hardware. We demonstrate how to quickly develop new applications on this platform, ranging from standard sensor interfacing techniques to more complicated intelligent pre-processing and wake-up detection. We also demonstrate how to integrate this platform with commonly used wireless sensor nodes and embedded-system platforms.","PeriodicalId":318992,"journal":{"name":"Proceedings of the 14th International Conference on Information Processing in Sensor Networks","volume":"42 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":"133625418","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: 9

SIFT: building an internet of safe things SIFT:构建安全物联网

Proceedings of the 14th International Conference on Information Processing in Sensor Networks Pub Date : 2015-04-13 DOI: 10.1145/2737095.2737115

C. Liang, Börje F. Karlsson, N. Lane, Feng Zhao, Junbei Zhang, Zheyi Pan, Zhao Li, Yong Yu

引用次数: 77