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2017 Mediterranean symposium on Smart City Application, SCAMS 2017

ISBN: (纸本)9781450352116

The proceedings contain 30 papers. The topics discussed include: towards a system for integrating heterogeneous health records;applying text mining to predict learners' cognitive engagement;an adult learner's knowledge model based on ontologies and rule reasoning;big data architecture for decision making in protocols and medications assignment;3D GIS for smart cities;cloud-based integrated information system for medical offices;ICT assessment axes for the smart city approach;XACML policies into Mongodb for privacy access control;implementation of the algorithms of ECG signal processing on embedded architectures: a survey;perception of a new framework for detecting phishing web pages;TV home-box based IoT for smart home;smart adaptive learning based on Moodle platform;SVG image comparison using commands of element path;wireless sensors networks challenges;energy dynamic MANET on-demand with error rate QOS (e-DYMO-Er) routing protocol for wireless sensor networks;towards a big data analytics framework for smart cities;remote controlled human navigational assistance for the blind using intelligent computing;study of the impact of load and density on the behavior of routing protocols AODV and DSDV in the VANET networks;modeling of piezoelectric sensors for feat heart rate signal;first Africa and morocco NB-IoT experimental results and deployment scenario: new approach to improve main 5G KPIs for smart water management;survey on nature inspired algorithm for smart city applications;and detection of driver drowsiness based on the Viola & Jones method and logistic regression analysis.

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Poster Abstract: Analysis and Evaluation of Driving Behavior Recognition Based on a 3-axis Accelerometer Using a Random Forest Approach

Poster Abstract: Analysis and Evaluation of Driving Behavior...

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international symposium on information processing in sensor networks (IPSN)

作者： Wangjing Cao Xin Lin Kai Zhang Yuhan Dong Shaolun Huang Lin Zhang Department of Electronic Engineering Tsinghua University Graduate School at Shenzhen Tsinghua University Tsinghua-Berkeley Shenzhen Institute

ISBN: (纸本)9781467391474

Understanding human drivers' behavior is critical for the self-driving cars, and has been intensively studied in the past decade. We exploit the widely available camera and motion sensor data from car recorders, and propose a hybrid method of recognizing driving events based on the random forest approach. The classification results are analyzed by comparing different features, classifiers and filters. A high accuracy of 98.1% on driving behavior classification is obtained and the robustness is verified on a dataset including 2400 driving events.

关键词： Accelerometers Automobiles Robustness Acceleration Feature extraction Time-domain analysis

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a Traffic Adaptive Asynchronous Media Access Control Protocol of Wireless sensor networks 3

a Traffic Adaptive Asynchronous Media Access Control Protoco...

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3rd international Conference on Systems and Informatics (ICSAI)

作者： Ling, Song Chi, E. Guangxi Univ Sch Comp & Elect Informat Nanning Peoples R China

ISBN: (纸本)9781509055210

The events which are monitored in wireless sensor networks(WSNs) always happens randomly, so the network traffic is dynamic. This paper proposes a traffic adaptive asynchronous media access control(MAC) protocol of wireless sensor network (TAASMAC). TAASMAC gets the number of packets which are waiting to be sent in the queue, according to the number, TAASMAC can get the current information of network traffic, and changes the sleep time. The TAASMAC also solves the broadcasting problem in asynchronous MAC. This paper uses NS2 to validate the TAASMAC, and the results show that the TAASMAC gets lower energy consumption while in low network traffic condition, and gets lower delay while in high network traffic condition.

关键词： wireless sensor networks asynchronous MAC protocol traffic adaptive

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Demo Abstract: Natural Timestamping Using Electrical Power Grid

Demo Abstract: Natural Timestamping Using Electrical Power G...

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international symposium on information processing in sensor networks (IPSN)

作者： Sreejaya Viswanathan Yang Li Rui Tan Advanced Digital Sciences Center Illinois at Singapore Singapore Computer Science and Engineering Nanyang Technological University Singapore

ISBN: (纸本)9781467391474

The continuous fluctuation of electric network frequency (ENF) presents a fingerprint indicative of time, which we call natural timestamp. This live demo demonstrates the accuracy of the natural timestamps obtained by four wired voltage sensors and four wireless electromagnetic radiation (EMR) sensors that are geographically distributed in Singapore. The voltage sensors and the EMR sensors capture the minute fluctuations of the length of each voltage cycle and the average ENF over every 50 voltage cycles, respectively. The evaluation in our prior studies [1, 3] has shown that the natural timestamps recorded by the voltage sensors and the EMR sensors give sub-millisecond and sub-second average time errors, respectively. This demo will also show their time errors.

关键词： Power grids Synchronization Voltage measurement Clocks Time-frequency analysis Protocols information processing

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Target Coverage-Aware Clustering for Directional sensor networks

Target Coverage-Aware Clustering for Directional Sensor Netw...

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IEEE international symposium on Parallel and Distributed processing with Applications and IEEE international Conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Selina Sharmin Fernaz Narin Nur Md. Abdur Razzaque Md. Mustafizur Rahman Department of Computer Science and Engineering University of Dhaka Dhaka Bangladesh Dhaka University Dhaka Dhaka District BD

ISBN: (纸本)9781538637913

In this work, we develop a target coverage-aware clustering algorithm for directional sensor networks, namely,,,, TRACE, that enhances the network lifetime. The TRACE nodes exploit single-hop neighborhood information only to elect cluster heads (CHs) and gateways. Thus, the TRACE is a fully distributed and light-weight clustering algorithm. The TRACE CHs greedily maximize the number of targets covered by as minimum number of sensor nodes as possible. The performances of the proposed TRACE system are studied on Network Simulator version 3 (ns- 3), and the results show that, it outperforms a state-of-the-art- work.

关键词： Logic gates Clustering algorithms sensors Energy states Monitoring Smart cities Clustering methods

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3D Through-Wall Imaging with Unmanned Aerial Vehicles Using WiFi

3D Through-Wall Imaging with Unmanned Aerial Vehicles Using ...

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international symposium on information processing in sensor networks (IPSN)

作者： Chitra R. Karanam Yasamin Mostofi University of California Santa Barbara Santa Barbara California

ISBN: (纸本)9781467391474

In this paper, we are interested in the 3D through-wall imaging of a completely unknown area, using WiFi RSSI and Unmanned Aerial Vehicles (UAVs) that move outside of the area of interest to collect WiFi measurements. It is challenging to estimate a volume represented by an extremely high number of voxels with a small number of measurements. Yet many applications are time-critical and/or limited on resources, precluding extensive measurement collection. In this paper, we then propose an approach based on Markov random field modeling, loopy belief propagation, and sparse signal processing for 3D imaging based on wireless power measurements. Furthermore, we show how to design emcient aerial routes that are informative for 3D imaging. Finally, we design and implement a complete experimental testbed and show high-quality 3D robotic through-wall imaging of unknown areas with less than 4% of measurements.

关键词： Imaging Three-dimensional displays Unmanned aerial vehicles Wireless fidelity Solid modeling Robot sensing systems Joining processes

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Poster Abstract: 3D Activity Localization with Multiple sensors

Poster Abstract: 3D Activity Localization with Multiple Sens...

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international symposium on information processing in sensor networks (IPSN)

作者： Xinyu Li Yanyi Zhang Jianyu Zhang Shuhong Chen Yue Gu Richard A. Farneth Ivan Marsic Randall S. Burd Rutgers University Piscataway New Jersey Children's National Medical Center Washington District of Columbia

ISBN: (纸本)9781467391474

We present a deep learning framework for fast 3D activity localization and tracking in a dynamic and crowded real world setting. Our training approach reverses the traditional activity localization approach, which first estimates the possible location of activities and then predicts their occurrence. Instead, we first trained a deep convolutional neural network for activity recognition using depth video and RFID data as input, and then used the activation maps of the network to locate the recognized activity in the 3D space. Our system achieved around 20cm average localization error (in a 4m × 5m room) which is comparable to Kinect's body skeleton tracking error (10-20cm), but our system tracks activities instead of Kinect's location of people.

关键词： Three-dimensional displays Activity recognition Neurons Passive RFID tags Machine learning Neural networks

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Preface

Advances in Intelligent Systems and Computing

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Advances in Intelligent Systems and Computing 2018年 678卷 v-vi页

作者： Thampi, Sabu M. Krishnan, Sri Rodriguez, Juan Manuel Corchado Das, Swagatam Wozniak͕, Michal Al-Jumeil, Dhiy School of CS/IT Indian Institute of Information Technology and Management TrivandrumKerala India Department of Electrical and Computer Engineering Ryerson University TorontoON Canada Department of Computer Science University of Salamanca SalamancaSalamanca Spain Electronics and Communication Sciences Unit Indian Statistical Institute Kolkata West Bengal India Department of Systems and Computer Networks Wroclaw University of Science and Technology Wroclaw Poland Faculty of Engineering and Technology Liverpool John Moores University Liverpool United Kingdom

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A better range-free localization algorithm in wireless sensor networks

A better range-free localization algorithm in wireless senso...

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3rd international symposium on Computer, Consumer and Control (IS3C)

作者： Liu Yan Zhang Yaming Xian Univ Sci & Technol Sch Commun & Informat Engn Yanta Rd 58 Xian 710054 Shaanxi Peoples R China Xian Shiyou Univ Sch Elect Engn 182nd Dianzi Rd Xian 710065 Shaanxi Peoples R China

ISBN: (纸本)9781509030712

Localization is a fundamental issue for many applications in wireless sensor networks. This paper proposes a better range-free algorithm based on DV-Hop, which increases localization accuracy without increasing hardware or communication costs. First, this algorithm utilizes average hop-size correction to reduce ranging errors. Second, the algorithm uses an improved equation solving method to reduce the impact of errors inherent in distance measurement, and the weighted least square method to improve localization accuracy. Finally, the algorithm uses additional information in the equation solving process to correct node coordinates. Simulation results show that the performance of the proposed algorithm is significantly better than the basic DV-Hop algorithm and other similar algorithms.

关键词： wireless sensor networks node localization range-free maximum likelihood estimation DV-Hop

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Large Scale Surveillance, Detection and Alerts information Management System for Critical Infrastructure 12th

Large Scale Surveillance, Detection and Alerts Information M...

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12th IFIP WG 5.11 international symposium on Environmental Software Systems (ISESS)

作者： Sabeur, Z. Zlatev, Z. Melas, P. Veres, G. Arbab-Zavar, B. Middleton, L. Museux, N. Univ Southampton Dept Elect & Comp Sci IT Innovat Ctr Southampton Hants England THALES Res & Technol Palaiseau France

ISBN: (纸本)9783319899350;9783319899343

A proof-of-concept system for large scale surveillance, detection and alerts information management (SDAIM) is presented in this paper. Various aspects of building the SDAIM software system for large scale critical infrastructure monitoring and decision support are described. The work is currently developped in the large collaborative ZONeSEC project (***). ZONeSEC specializes in the monitoring of so-called Wide-zones. These are large critical infrastructure which require 24/7 monitoring for safety and security. It involves integrated in situ and remote sensing together with large scale stationary sensor networks, that are supported by cross-border communication. In ZONeSEC, the specific deployed sensors around the critical infrastructure may include: Accelerometers that are mounted on perimeter fences;Underground acoustic sensors;Optical, thermal and hyperspectral video cameras or radar systems mounted on strategic areas or on airborne UAVs for mission exploration. The SDAIM system design supports the ingestion of the various types of sensors platform wide-zones' environmental observations and provide large scale distributed data fusion and reasoning with near-real-time messaging and alerts for critical decision-support. On a functional level, the system design is founded on the JDL/DFIG (Joint Directors of Laboratories/Data Fusion information Group) data and information fusion model. Further, it is technologically underpinned by proven Big Data technologies for distributed data storage and processing as well as on-demand access to intelligent data analytics modules. The SDAIM system development will be piloted and alidated at various selected ZONeSEC project wide-zones [1]. These include water, oil and transnational gas pipelines and motorway conveyed in six European countries.

关键词： Big data Data fusion information systems Surveillance of critical infrastructure

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