2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)最新文献_第6页

Poster Abstract: DeGas - Toxic Gas Boundary Area Detection in Industrial Wireless Sensor Networks 海报摘要:DeGas -工业无线传感器网络中的有毒气体边界区域检测

2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Pub Date : 2016-04-11 DOI: 10.1109/IPSN.2016.7460700

Lei Shu, M. Mukherjee, Yuanfang Chen

引用次数: 4

Demonstration Abstract: Research Platform for Visible Light Communication and Sensing Systems 摘要:可见光通信与传感系统研究平台

2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Pub Date : 2016-04-11 DOI: 10.1109/IPSN.2016.7460672

Qing Wang, Danilo De Donno, D. Giustiniano

{"title":"Demonstration Abstract: Research Platform for Visible Light Communication and Sensing Systems","authors":"Qing Wang, Danilo De Donno, D. Giustiniano","doi":"10.1109/IPSN.2016.7460672","DOIUrl":"https://doi.org/10.1109/IPSN.2016.7460672","url":null,"abstract":"OpenVLC (www.openvlc.org) is an open-source project for research in Visible Light Communication (VLC) systems. It has the potential to help create a new type of infrastructure, an Internet of Lights (IoL), where LED- based devices (e.g., car lights, city lights, billboards, toy, etc) and photodetectors become inter- connected. OpenVLC is built upon an embedded platform and adopts off-the-shelf optical devices and essential electronic components. It has been proved to be a starter kit for VLC research, thanks to its deployments by tens of top universities/research centers in the world (www.openvlc.org/list-of-users.html). This demo introduces its latest version: OpenVLC1.1. The new features include: (1) higher resilience to ambient light noise, e.g., indoor interfering lighting; (2) interface for sensor application. A new board (OpenVLC1.1 cape) is designed and the printed circuit is developed. The cape is plugged directly into the main embedded board and external sensors can be easily connected to the cape. This demo demonstrates OpenVLC1.1's networking performance through standard networking diagnostic tools and shows an application wherein temperature and humidity sensed data are transmitted through VLC links.","PeriodicalId":137855,"journal":{"name":"2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131649250","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: 2

Poster Abstract: An Extremely Long Standby Time Wireless Sensor System for Debris Flow Monitoring 摘要:用于泥石流监测的超长待机时间无线传感器系统

2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Pub Date : 2016-04-11 DOI: 10.1109/IPSN.2016.7460695

Teng-Chieh Chan, Kai-Hsiang Ke, Yao-Min Fang, Bing-Jean Lee, Huang-Chen Lee

引用次数: 1

Poster Abstract: Node Deployment Mechanism for Quick, Indoor, and Device-Free Localization 摘要:快速、室内、无设备定位的节点部署机制

2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Pub Date : 2016-04-11 DOI: 10.1109/IPSN.2016.7460709

Jinjun Liu, Ning An, Md. Tanbir Hassan, Guilin Chen, Yanyong Zhang

引用次数: 2

Poster Abstract: LocaLight - A Battery-Free Passive Localization System Using Visible Light 海报摘要:LocaLight -一个使用可见光的无电池被动定位系统

2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Pub Date : 2016-04-11 DOI: 10.1109/IPSN.2016.7460707

E. D. Lascio, Ambuj Varshney, T. Voigt, C. Pérez-Penichet

引用次数: 17

DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices DeepX:移动设备上低功耗深度学习推理的软件加速器

2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Pub Date : 2016-04-11 DOI: 10.1109/IPSN.2016.7460664

N. Lane, S. Bhattacharya, Petko Georgiev, Claudio Forlivesi, Lei Jiao, Lorena Qendro, F. Kawsar

{"title":"DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices","authors":"N. Lane, S. Bhattacharya, Petko Georgiev, Claudio Forlivesi, Lei Jiao, Lorena Qendro, F. Kawsar","doi":"10.1109/IPSN.2016.7460664","DOIUrl":"https://doi.org/10.1109/IPSN.2016.7460664","url":null,"abstract":"Breakthroughs from the field of deep learning are radically changing how sensor data are interpreted to extract the high-level information needed by mobile apps. It is critical that the gains in inference accuracy that deep models afford become embedded in future generations of mobile apps. In this work, we present the design and implementation of DeepX, a software accelerator for deep learning execution. DeepX signif- icantly lowers the device resources (viz. memory, computation, energy) required by deep learning that currently act as a severe bottleneck to mobile adoption. The foundation of DeepX is a pair of resource control algorithms, designed for the inference stage of deep learning, that: (1) decompose monolithic deep model network architectures into unit- blocks of various types, that are then more efficiently executed by heterogeneous local device processors (e.g., GPUs, CPUs); and (2), perform principled resource scaling that adjusts the architecture of deep models to shape the overhead each unit-blocks introduces. Experiments show, DeepX can allow even large-scale deep learning models to execute efficently on modern mobile processors and significantly outperform existing solutions, such as cloud-based offloading.","PeriodicalId":137855,"journal":{"name":"2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115565146","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: 459

Frame Counter: Achieving Accurate and Real-Time Link Estimation in Low Power Wireless Sensor Networks 帧计数器:在低功耗无线传感器网络中实现准确和实时的链路估计

2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Pub Date : 2016-04-11 DOI: 10.1109/IPSN.2016.7460673

Daibo Liu, Zhichao Cao, Mengshu Hou, Yi Zhang

{"title":"Frame Counter: Achieving Accurate and Real-Time Link Estimation in Low Power Wireless Sensor Networks","authors":"Daibo Liu, Zhichao Cao, Mengshu Hou, Yi Zhang","doi":"10.1109/IPSN.2016.7460673","DOIUrl":"https://doi.org/10.1109/IPSN.2016.7460673","url":null,"abstract":"Link estimation is a fundamental component of forwarding protocols in wireless sensor networks. In low power forwarding, however, the asynchronous nature of widely adopted duty-cycled radio control brings new challenges to achieve accurate and real- time estimation. First, the repeatedly transmitted frames (called wake-up frame) increase the complexity of accurate statistic, especially with bursty channel contention and coexistent interference. Second, frequent update of every link status exhausts the limited energy supply due to long duration of beacon broadcast. In this paper, we propose meter (Distributed Frame Counter), which takes the opportunities of link overhearing to update link status in real time. Furthermore, meter does not only depend on counting the successfully decoded wake-up frames, but also counts the corrupted ones by exploiting the feasibility of ZigBee identification based on short-term sequence of the received signal strength. We implement meter in TinyOS and further evaluate the performance through extensive experiments on indoor and outdoor testbeds. The results demonstrate that meter can significantly improve the performance of the state-of-the-art link estimation schemes.","PeriodicalId":137855,"journal":{"name":"2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127194236","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

Poster Abstract: Architecture Proposal for Heterogeneous, BLE-Based Sensor and Actuator Networks for Easy Management of Smart Homes 摘要:异构、基于ble的传感器和执行器网络架构方案，便于智能家居的管理

2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Pub Date : 2016-04-11 DOI: 10.1109/IPSN.2016.7460697

Celia Garrido, Vicente López, T. Olivares, M. Ruiz

引用次数: 5

Ph.D. Forum Abstract: Accurate and Robust Low-Cost GNSS Localization 摘要:精确鲁棒的低成本GNSS定位

2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Pub Date : 2016-04-11 DOI: 10.1109/IPSN.2016.7460683

Rueben A. Banalagay

引用次数: 2

Poster Abstract: Sleep Scheduling with Toxic Gas Coverage Requirement in Large-Scale Industry 摘要:大型工业中有毒气体覆盖要求下的睡眠调度

2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) Pub Date : 2016-04-11 DOI: 10.1109/IPSN.2016.7460713

M. Mukherjee, Lei Shu, Yuanfang Chen

引用次数: 1