2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)最新文献_第6页

Data-driven method for providing feedback to households on electricity consumption 以数据驱动的方式向住户提供用电情况的反馈

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827661

Matti Mononen, Jukka Saarenpaa, Markus Johansson, Harri Niska

{"title":"Data-driven method for providing feedback to households on electricity consumption","authors":"Matti Mononen, Jukka Saarenpaa, Markus Johansson, Harri Niska","doi":"10.1109/ISSNIP.2014.6827661","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827661","url":null,"abstract":"The building sector is a major energy consumer and CO2 emitter, being responsible for approximately 40% of the total consumption in the EU. Active demand side participation of electricity customers is seen as crucial in the management and reduction of the building sector's CO2 emissions. However, today's electricity markets are often lacking strong incentives for active demand side participation. Understandable customer specific comparison information and easy-to-use energy displays can be used to influence customer behaviour and encourage customer participation. This paper presents a data-driven method for producing household level comparison information, based on hourly interval smart meter data and additional household information. Firstly, the customers are segmented by the heating system and the type of housing, followed by weighted clustering that is used to refine the comparison group. In the weighted clustering, normalized load profiles together with properties of the dwelling and the residents are considered, and weights are assigned to the properties according to how much they contribute to the electricity consumption. In this paper, the initial experimental results are presented and discussed, and future development ideas are laid out. The method is under development and testing as a part of the Finnish SGEM-project.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132738806","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

A P2P streaming system for delivering sensor data streams with different collection cycles 一个P2P流系统，用于传输具有不同采集周期的传感器数据流

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827666

Yoshimasa Ishi, Tomoya Kawakami, T. Yoshihisa, Y. Teranishi

引用次数: 2

Personalising pollution exposure estimates using wearable activity sensors 使用可穿戴活动传感器进行个性化污染暴露评估

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827617

Ke Hu, Yan Wang, Ashfaqur Rahman, V. Sivaraman

引用次数: 21

NEPS: “Narrowband Efficient Positioning System” for delivering resource efficient GNSS receivers NEPS:窄带高效定位系统，用于提供资源高效的GNSS接收器

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827605

Ido Nevat, Ory Eger, G. Peters, F. Septier

{"title":"NEPS: “Narrowband Efficient Positioning System” for delivering resource efficient GNSS receivers","authors":"Ido Nevat, Ory Eger, G. Peters, F. Septier","doi":"10.1109/ISSNIP.2014.6827605","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827605","url":null,"abstract":"We present a new architecture to perform localization (position estimation) in GNSS systems, termed NEPS (Narrowband Efficient Positioning System). The NEPS architecture is composed of three components: a low powered cheap receiver; a communication system which transmits the measurements; and a processing unit which receives the distorted observations (due to quantisation and imperfect transmission medium) and performs the position estimation algorithm. The NEPS is a stand-alone system which is designed to incorporate the quantised measurements as well as the imperfect communication channels between receiver and the backend in order to perform inference on the user's position. Compared with a conventional system, the NEPS consumes less bandwidth, requires lower power consumption and provides faster reporting rates. We derive the joint Maximum Likelihood (ML) for the position and the receiver's clock offset. We then develop an efficient algorithm to solve the resulting non-convex oinferenceptimisation problem. Furthermore, we derive a theoretical performance lower bound on the achievable accuracy via Cramér-Rao lower bound (CRLB). Simulation results show that the performance of the NEPS ML position estimator is close to the theoretical performance bound.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121697622","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: 4

Leveraging application context for efficient sensing 利用应用程序上下文进行有效的感知

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827692

Jinseok Yang, T. Simunic, S. Tilak

{"title":"Leveraging application context for efficient sensing","authors":"Jinseok Yang, T. Simunic, S. Tilak","doi":"10.1109/ISSNIP.2014.6827692","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827692","url":null,"abstract":"Today's platforms for long-term environmental monitoring (e.g. buoys or towers) typically host large solar panels and batteries. Ideally, miniaturized platforms could be used instead, so state of the art power management technique that takes into account battery levels and harvested energy to provide uniform sampling rate. However, the fixed pre-defined intervals is not desirable. The state-of-art adaptive sampling mechanism, optimal adaptive sampling algorithm (OSA) uses data uncertainty and past measurements to determine the optimal sampling rate at the cost of high computational complexity O(n3), thus draining the batteries even further. Even if the sampling were done optimally, there are still significant challenges with data transmission. The state of the art approach for determining optimal transmission policy offers limited control over the energy-delay tradeoff and is not suitable to support wide range of applications ranging from real-time and delay-tolerant. To address these challenges, we have developed a novel power management framework that adapts sampling and transmission rates based on battery level, energy harvesting level and application-context (e.g. characteristics of the gathered data). Our framework is optimal in terms of energy efficiency with low computational complexity. We evaluate the performance of the proposed framework using datasets from two real-world deployments. Our results show that our approach saves significant amounts of energy (between 20% to 60%) by avoiding oversampling when the application does not need it and uses this saved energy to support sampling at high rates to capture event with necessary fidelity when needed.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122403159","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

LPED: Channel diagnostics in WSN through channel coding and symbol error statistics LPED:通过信道编码和符号错误统计在WSN中进行信道诊断

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827630

Filip Barac, M. Gidlund, Tingting Zhang

{"title":"LPED: Channel diagnostics in WSN through channel coding and symbol error statistics","authors":"Filip Barac, M. Gidlund, Tingting Zhang","doi":"10.1109/ISSNIP.2014.6827630","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827630","url":null,"abstract":"Three major obstacles to wireless communication are electromagnetic interference, multipath fading and signal attenuation. The former stems mainly from collocated wireless systems operating in the same frequency band, while the latter two originate from physical properties of the environment. Identifying the source of packet corruption and loss is crucial, since the adequate countermeasures for different types of threats are essentially different. This problem is especially pronounced in industrial monitoring and control applications, where IEEE 802.15.4 communication is expected to deliver data within tight deadlines, with minimal packet loss. This work presents the Lightweight Packet Error Discriminator (LPED) that distinguishes between errors caused by multipath fading and attenuation, and those inflicted by IEEE 802.11 interference. LPED uses Forward Error Correction to determine the symbol error positions inside erroneously received packets and calculates the error density, which is then fed to a discriminator for error source classification. The statistical constituents of LPED are obtained from an extensive measurement campaign in two different types of industrial environments. The classifier incurs no overhead and in ≥90% of cases a single packet is sufficient for a correct channel diagnosis. Experiments show that LPED accelerates link diagnostics by at least 190%, compared to the relevant state-of-the-art approaches.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124749102","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: 6

Critical time parameters for evaluation of body area Wireless Sensor Networks in a Healthcare Monitoring Application 医疗监测应用中身体区域无线传感器网络评估的关键时间参数

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827683

V. Balasubramanian

引用次数: 10

A comparison of two proximity networks 两个邻近网络的比较

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827693

Håkan Jonsson, P. Nugues

引用次数: 0

Robust multi-parametric sensor system for the online detection of microbial biofilms in industrial applications — Preliminary examinations 工业应用中在线检测微生物生物膜的鲁棒多参数传感器系统。初步检验

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827602

M. Ruhnow, Julia Kohser, T. Bley, E. Boschke, M. Bulst, S. Wegner

引用次数: 2

A novel method for benign and malignant characterization of mammographic microcalcifications employing waveatom features and circular complex valued — Extreme Learning Machine 一种利用波原子特征和圆形复合体价值的乳房x线微钙化良恶性表征的新方法-极限学习机

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827660

Malar Elangeeran, Savitha Ramasamy, Kandaswamy Arumugam

引用次数: 11