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检索条件"任意字段=13th IEEE/ACM International Conference on Information Processing in Sensor Networks, IPSN 2014"

共 45 条记录，以下是31-40 订阅

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Watching the Grid: Utility-Independent Measurements of Electricity Reliability in Accra, Ghana 20

Watching the Grid: Utility-Independent Measurements of Elect...

引用

20th acm/ieee international conference on information processing in sensor networks (ipsn)

作者： Klugman, Noah Adkins, Joshua Paszkiewicz, Emily Hickman, Molly G. Podolsky, Matthew Taneja, Jay Dutta, Prabal Univ Calif Berkeley Berkeley CA 94720 USA Virginia Tech Blacksburg VA USA Univ Massachusetts Amherst MA 01003 USA

ISBN: (纸本)9781450380980

In much of the world, electricity grids are not instrumented at the customer level, limiting insights into the power quality experienced by utility customers. Moreover, to understand grid performance, regulators and investors must depend on utilities to self-report reliability data. To address these challenges, we introduce PowerWatch, an agile methodology to directly measure customer experience and aggregated grid performance without relying on the utility for deployment or management. PowerWatch employs a system of distributed sensors coupled with cloud-based analytics. We evaluate the PowerWatch methodology by deploying 462 sensors in homes and businesses in Accra, Ghana for over a year, yielding the largest open-source data set on electricity reliability at the customer-level in the region. We describe the architecture, design, and performance of PowerWatch, as well as the data that are collected, explaining how we determine the accuracy and coverage of our methodology without ground truth. Finally, we report on grid performance issues, finding nearly twice as many outages as the utility observed, suggesting a need for better grid performance monitoring.

关键词： sensor deployments Grid reliability metering

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Reducing Multi-Hop Calibration Errors in Large-Scale Mobile sensor networks 14

Reducing Multi-Hop Calibration Errors in Large-Scale Mobile ...

引用

14th ieee/acm international conference on information processing in sensor networks (ipsn)

作者： Saukh, Olga Hasenfratz, David thiele, Lothar Swiss Fed Inst Technol Comp Engn & Networks Lab Zurich Switzerland

ISBN: (纸本)9781450334754

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 (O-3), and carbon monoxide (CO) measurements gathered by our mobile air pollution monitoring network.

关键词： Calibration

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SolarFinder: Automatic Detection of Solar Photovoltaic Arrays 19

SolarFinder: Automatic Detection of Solar Photovoltaic Array...

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19th acm/ieee international conference on information processing in sensor networks (ipsn)

作者： Li, Qi Feng, Yuzhou Leng, Yuyang Chen, Dong Florida Int Univ Miami FL 33199 USA

ISBN: (纸本)9781728154978

Smart cities, utilities, third-parties, and government agencies are having pressure on managing stochastic power generation from distributed rooftop solar photovoltaic (PV) arrays, such as predicting and reacting to the variations in electric grid. Recently, there is a rising interest to identify solar PV arrays automatically and passively. Traditional approaches such as online assessment and utilities interconnection filings are time consuming and costly, and limited in geospatial resolution, and thus do not scale up to every location. Significant recent work focuses on using aerial imagery to train machine learning or deep learning models to automatically detect solar PV arrays. Unfortunately, these approaches typically require Very High Resolution (VHR) images and human handcrafted solar PV array templates for training, which have a minimum cost of $15 per km(2) and are not always available at every location. To address the problem, we design a new system-SolarFinder that can automatically detect: distributed solar PV arrays in a given geospatial region without any extra cost. SolarFinder first automatically fetches regular resolution satellite images within the region using publicly-available imagery APIs. then, SolarFinder leverages multi-dimensional K-means algorithm to automatically segment solar arrays on rooftop images. Eventually, SolarFinder employs hybrid linear regression approach that integrates support vector machine (SVM) modeling with a deep convolutional neural networks (CNNs) approach to accurately identify solar PV arrays and characterize each solar deployment. We evaluate SolarFinder using 269,632 satellite images that include 1,143,636 contours from 13 geospatial regions in U.S. We find that pre-trained-SolarFinder yields a Matthews Correlation Coefficient (MCC) of 0.17, which is 3 times better than the most recent: pre-trained CNNs approach and the same as a re-trained CNNs approach.

关键词： Solar Detection Deep Learning Image processing Energy

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A ENERGY-ORIENTED DISTRIBUTED TDMA SCHEDULING ALGORIthM FOR WIRELESS sensor networks 13

A ENERGY-ORIENTED DISTRIBUTED TDMA SCHEDULING ALGORITHM FOR ...

引用

13th ieee international Computer conference on Wavelet Active Media Technology and information processing (ICCWAMTIP)

作者： Zeng, Jun Zhang, Xiao-Tong Tang, Jing Wang, Peng Bai, Hongying Ma, Fuqiang Zhao, Xuan Univ Sci & Technol Beijing Sch Comp & Commun Engn Beijing 100083 Peoples R China Univ Sci & Technol Beijing Sch Mech Engn Beijing 100083 Peoples R China

ISBN: (纸本)9781509061266

Considering the industrial field, the problems of limited energy and changed topology of the network restrict the development of the centralized resource allocation. Although the traditional distributed resource allocation algorithm solves the network topology change partly, there is still no breakthrough in terms of energy consumption. In this paper, we simulate the Distributed Randomized TDMA scheduling (DRAND) on the OMNeT++ platform, and it was found that the resource allocation algorithm based on random probability leads to a high collision of the message, which results in the waste of energy. According to the above questions, the author propose a dynamic priority allocation algorithm called RE-DRAND. Compared with DRAND, the algorithm can obviously reduce the execution time about 28.6%, and it provides a solution of topology changes and scarce energy problems in the industrial wireless sensor networks and the traditional self-organizing networks.

关键词： Wireless sensor networks(WSNs) media access control distributed residual energy

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the energy endoscope: Real-time detailed energy accounting for wireless sensor nodes

The energy endoscope: Real-time detailed energy accounting f...

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7th international Symposium on information processing sensor networks

作者： Stathopoulos, thancis McIntire, Dustin Kaiser, William J. Univ Calif Los Angeles Dept Elect Engn Los Angeles CA 90024 USA

ISBN: (纸本)9780769531571

this paper describes a new embedded networked sensor platform architecture that combines hardware and software tools providing detailed, fine-grained real-time energy usage information. We introduce the LEAP2 platform, a qualitative step forward over the previously developed LEAP [13] and other similar platforms. LEAP2 is based on a new low power ASIC system and generally applicable supporting architecture that provides unprecedented capabilities for directly observing energy usage of multiple subsystems in real-time. Real-time observation with microsecond-scale time resolution enables direct accounting of energy dissipation for each computing task as well as for each hardware subsystem. the new hardware architecture is exploited with our new software tools, etop and endoscope. A series of experimental investigations provide high-resolution power information in networking, storage, memory and processing for primary embedded networked sensing applications. Using results obtained in real-time we show that for a large class of wireless sensor network nodes, there exist several interdependencies in energy consumption between different subsystems. through the use of our measurement tools we demonstrate that by carefully selecting the system operating points, energy savings of over 60% can be achieved while retaining system performance.

关键词： Endoscopy

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conference organization

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international Symposium on information processing in sensor networks (ipsn)

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Demonstration abstract: Crowdsourced indoor localization and navigation with Anyplace

Demonstration abstract: Crowdsourced indoor localization and...

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international Symposium on information processing in sensor networks (ipsn)

作者： Lambros Petrou George Larkou Christos Laoudias Demetrios Zeinalipour-Yazti Christos G. Panayiotou Department of Computer Science University of Cyprus Nicosia Cyprus KIOS Research Center for Intelligent Systems and Networks University of Cyprus Nicosia Cyprus

In this demonstration paper, we present the Anyplace system that relies on the abundance of sensory data on smartphones (e.g., WiFi signal strength and inertial measurements) to deliver reliable indoor geolocation information. Our system features two highly desirable properties, namely crowdsourcing and scalability. Anyplace implements a set of crowdsourcing-supportive mechanisms to handle the enormous amount of crowdsensed data, filter incorrect user contributions and exploit WiFi data from heterogeneous mobile devices. Moreover, Anyplace follows a big-data architecture for efficient and scalable storage and retrieval of localization and mapping data.

关键词： Navigation ieee 802.11 Standards Buildings Smart phones Crowdsourcing Servers Computer architecture

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PiLoc: A self-calibrating participatory indoor localization system

PiLoc: A self-calibrating participatory indoor localization ...

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international Symposium on information processing in sensor networks (ipsn)

作者： Chengwen Luo Hande Hong Mun Choon Chan School of Computing National University of Singapore Singapore

While location is one of the most important context information in mobile and ubiquitous computing, large-scale deployment of indoor localization system remains elusive. In this work, we propose PiLoc, an indoor localization system that utilizes opportunistically sensed data contributed by users. Our system does not require manual calibration, prior knowledge and infrastructure support. the key novelty of PiLoc is that it merges walking segments annotated with displacement and signal strength information from users to derive a map of walking paths annotated with radio signal strengths. We evaluate PiLoc over 4 different indoor areas. Evaluation shows that our system can achieve an average localization error of 1.5m.

关键词： Trajectory Legged locomotion Correlation Calibration ieee 802.11 Standards Market research Educational institutions

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Demonstration abstract: AirFeed — Indoor real time interactive air quality monitoring system

Demonstration abstract: AirFeed — Indoor real time interact...

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international Symposium on information processing in sensor networks (ipsn)

作者： Kyeong T. Min Andrzej Forys thomas Schmid Department of Computer and Electrical Engineering University of Utah Salt Lake City Utah

Solutions to outdoor air pollution require societal changes; however, we focus on indoor home air quality to allow for individual control over the breathing environment. We present AirFeed: a real time air quality monitoring system that provides measurements on particulate matter, temperature, and humidity. Interactions with users based on data analysis and user/sensor feedback form distinguishable patterns between several types of activities. We can better inform the user how daily habits affect living environments. Several deployments are actively collecting data for future data analysis and improved pattern recognition.

关键词： Temperature sensors Monitoring Temperature measurement Humidity ieee 802.11 Standards Real-time systems Atmospheric measurements

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Poster abstract: MaWi: A hybrid Magnetic and Wi-Fi system for scalable indoor localization

Poster abstract: MaWi: A hybrid Magnetic and Wi-Fi system fo...

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international Symposium on information processing in sensor networks (ipsn)

作者： Chi Zhang Jun Luo Jianxin Wu School of Computer Engineering Nanyang Technological University Singapore Department of Computer Science Technology Nanjing University Nanjing China

We present MaWi - a smart phone based scalable indoor localization system. Central to MaWi is a novel framework combining two self-contained but complementary localization techniques: Wi-Fi and Ambient Magnetic Field. Combining the two techniques, MaWi not only achieves a high localization accuracy, but also effectively reduces human labor in building fingerprint databases: to avoid war-driving, MaWi is designed to work with low quality fingerprint databases that can be efficiently built by only one person. Our experiments demonstrate that MaWi, with a fingerprint database as scarce as one data sample at each spot, outperforms the state-of-the-art proposals working on a richer fingerprint database.

关键词： Databases ieee 802.11 Standards Smart phones Accuracy Fingerprint recognition Educational institutions Buildings

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