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Multi-Sensor Data Fusion with Deep Learning in Semantic Segmentation
, M.Sc. Thesis Sharif University of Technology ; Kasaei, Shohreh (Supervisor)
Abstract
In image processing applications, sensors (Camera, LiDAR and Stereo) are essential for scene perception and Deep learning methods outperform most of the image processing tasks like 3D and 2D object detection and semantic segmentation. Different sensors are used in image processing tasks. Sensor fusion is using multiple sensors data to get better performance. Each sensor captures different data (e.g, color, texture, and depth). Some of them are distorted in inclement weather, intense illuminance changes, and dark environments which multi-sensor data fusion is used to overcome sensor weaknesses. One of the most important fields that sensor fusion used is Auto Driving cars (AD). Different...
NSSSD: A new semantic hierarchical storage for sensor data
, Article 20th IEEE International Conference on Computer Supported Cooperative Work in Design, 4 May 2016 through 6 May 2016 ; 2016 , Pages 174-179 ; 9781509019151 (ISBN) ; Movassagh, A. A ; Qin, Y ; Yong, J ; Tao, X ; Zhang, J ; Shen, H ; Liu, X. P ; Yong, J ; Barthes, J. P ; Shen, W ; Yang, C ; Luo, J ; Chen, L ; IEEE Systems, Man, and Cybernetics Society; International Working Group on Computer Supported Cooperative Work in Design (CSCWD) ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
Abstract
Sensor networks usually generate mass of data, which if not structured for future applications, will require much effort on analytical processing and interpretations. Thus, storing sensor data in an effective and structured format is a key issue in the area of sensor networks. In the meantime, even a little improvement on data storing structure may lead to a significant effect on the lifetime and performance of the sensor network. This paper describes a new method for sensor storage that combines semantic web concepts, a data aggregation method along with aligning sensors in hierarchical form. This solution is able to reduce the amount of data stored at the sink nodes significantly. At the...
Secure consensus averaging in sensor networks using random offsets
, Article 2007 IEEE International Conference on Telecommunications and Malaysia International Conference on Communications, ICT-MICC 2007, Penang, 14 May 2007 through 17 May 2007 ; 2007 , Pages 556-560 ; 1424410940 (ISBN); 9781424410941 (ISBN) ; Talebi, M. S ; Hossein Khalaj, B ; Rabiee, H. R ; Sharif University of Technology
2007
Abstract
In this work, we have examined the distributed consensus averaging problem from a novel point of view considering the need for privacy and anonymity. We have proposed a method for incorporating security into the scalable average consensus mechanisms proposed in the literature. Random Offsets Method (ROM) is lightweight, transparent and flexible since it is not based on cryptography, does not require any change in the fusion system and can be used optionally by some nodes who care about their privacy. In this method, which is based on noisiflcation of nodes' information, we achieve robustness against n - 1 colluding adversaries in a network of n nodes, which is maximum level of robustness...
Transmit power reduction by adapting rate or power for single carrier wireless systems
, Article 25th IEEE International Performance, Computing, and Communications Conference, 2006, IPCCC 2006, Phoenix, AZ, 10 April 2006 through 12 April 2006 ; Volume 2006 , 2006 , Pages 103-109 ; 1424401976 (ISBN); 9781424401970 (ISBN) ; Pakravan, M. R ; Khalaj, B. H ; Sharif University of Technology
2006
Abstract
Adaptive modulation with the goal of minimizing the average transmit power is investigated. This is the dual problem of the well-known problem of maximizing the average spectral efficiency. This is desirable in power limited systems such as mobile and sensor networks. Two main cases are considered: adapting only transmit power and adapting only rate. Appropriate expressions for rate or power control policies are derived for different cases. For rate adaptation, we consider both continuous and discrete rate policies. Then, we will apply these methods to a special case of M-QAM modulation over Rayleigh fading channel. We will show that by using rate or power adaptation schemes, between 7dB and...
Estimation error minimization in sensor networks with mobile agents
, Article 2006 3rd IEEE Consumer Communications and Networking Conference, CCNC 2006, Las Vegas, NV, 8 January 2006 through 10 January 2006 ; Volume 2 , 2006 , Pages 964-968 ; 1424400856 (ISBN); 9781424400850 (ISBN) ; Arbab, V. R ; Pakravan, M. R ; Sharif University of Technology
2006
Abstract
In a SEnsor Network with Mobile Agents (SENMA) is an architecture proposed for large scale sensor networks. In sensor networks, a fraction of the packets generated by only part of the sensors is sufficient to provide a good estimation of all network information. SENMA uses this inherent redundancy. However, the performance of such system is limited by estimation errors and packet errors due to collision. Estimation error is a major problem in applications such as habitat monitoring in which information is a function of node position. In this paper, we first derive the equations of distortion in a general scenario and use this model to compare the estimation error for regular networks. Then...
Energy conserving movement-assisted deployment of Ad hoc sensor networks
, Article IEEE Communications Letters ; Volume 10, Issue 4 , 2006 , Pages 269-271 ; 10897798 (ISSN) ; Nayyeri, A ; Yazdani, N ; Lucas, C ; Sharif University of Technology
2006
Abstract
Sensor network deployment is very challenging due to hostile and unpredictable nature of usage environments. In this letter, we propose two methods for the self-deployment of mobile sensors. The first one is a randomized solution that provides both simplicity and applicability to different environments. Inspired by simulated annealing, it improves both speed and energy conservation of the deployment process. The other method is suggested for environments where sensors form a connected graph, initially. At the cost of this extra limitation, we gain considerable improvements. © 2006 IEEE
Human arm motion tracking by inertial/magnetic sensors using unscented kalman filter and relative motion constraint
, Article Journal of Intelligent and Robotic Systems: Theory and Applications ; 2017 , Pages 1-10 ; 09210296 (ISSN) ; Salarieh, H ; Alasty, A ; Abediny, M ; Sharif University of Technology
Abstract
Human motion tracking has many applications in biomedical and industrial services. Low-cost inertial/magnetic sensors are widely used in human motion capture systems to obtain the orientation of the human body segments. In this paper, we have presented a quaternion-based unscented Kalman filter algorithm to fuse inertial/magnetic sensors measurements for tracking human arm movements. In order to have a better estimation of the orientation of the forearm and the upper arm, a constraint equation was developed based on the relative velocity of the elbow joint with respect to the inertial sensors attached to the forearm and the upper arm. Also to compensate for fast body motions, we adapted the...
Abnormality detection and monitoring in multi-sensor molecular communication
, Article IEEE Transactions on Molecular, Biological, and Multi-Scale Communications ; Volume 5, Issue 2 , 2019 , Pages 68-83 ; 23327804 (ISSN) ; Mirmohseni, M ; Nasiri Kenari, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
In this paper, we investigate the problem of detecting and monitoring changes (abnormality) in molecular communication (MC), using the quickest change detection (QCD) schemes. The objective is to watch an environment using a sensor network and make decisions on the time and location of changes based on the received signals from sensors in the fusion center (FC). Such assumptions call for considering spatial and temporal correlations among sensors' transmitting signals. We use the framework of Partially Observable Markov Decision Processes (POMDPs) based on non-homogeneous Markov models. The metric in detection (stopping-time) scenario is to minimize the delay of announcing an abnormality...
Image Flow and INS Sensor Fusion for the Accurate Localization of Planner Micro Robots
, M.Sc. Thesis Sharif University of Technology ; Vossoughi, Gholamreza (Supervisor)
Abstract
This research focuses on the robust mobile robot localization exploiting motion information acquired from an optical mouse operating based on optical flow technology. Most techniques of visual motion measurement are based on the well research discipline called “optical flow”. Theoretically, optical flow as a method of localization can be highly accurate, but it is sensitive to the noise and surface texture/optical characteristics and distance variations between the CCD detector and surface. As one could not achieve acceptable results in practical situations, to handle these problems, we propose to attach an acceleration – gyro (INS) sensor on the CCD detector (optical mouse) to improve the...
Asynchronous track-to-track fusion by direct estimation of time of sample in sensor networks
, Article IEEE Sensors Journal ; Vol. 14, issue. 1 , Jan , 2014 , p. 210-217 ; 1530437X ; Hemmatyar, A. M. A ; Sharif University of Technology
Abstract
Asynchronous data fusion is inevitable in track-to-track fusion for tracking high-speed targets. For low-speed targets, e.g., the movement of clouds, synchronization is insignificant and, depending on the application, may be disregarded. Real-time asynchronous fusion is a demanding task in sensor networks when the sensors are not synchronous in sampling-rate or in sampling-phase. In the method proposed in this paper, an estimator in the fusion center estimates the actual time of the sample with respect to the time-reference of the fusion center upon receiving the data from a sensor. Then, the computer of the fusion center uses predictions to transfer all the received data to the data...
Trunk motion system (TMS) using printed body worn sensor (BWS) via data fusion approach
, Article Sensors (Switzerland) ; Volume 17, Issue 1 , 2017 ; 14248220 (ISSN) ; Zobeiri, O ; Moshiri, B ; Narimani, R ; Mehravar, M ; Rashedi, E ; Parnianpour, M ; Sharif University of Technology
MDPI AG
2017
Abstract
Human movement analysis is an important part of biomechanics and rehabilitation, for which many measurement systems are introduced. Among these, wearable devices have substantial biomedical applications, primarily since they can be implemented both in indoor and outdoor applications. In this study, a Trunk Motion System (TMS) using printed Body‐Worn Sensors (BWS) is designed and developed. TMS can measure three‐dimensional (3D) trunk motions, is lightweight, and is a portable and non‐invasive system. After the recognition of sensor locations, twelve BWSs were printed on stretchable clothing with the purpose of measuring the 3D trunk movements. To integrate BWSs data, a neural network data...
Human arm motion tracking by inertial/magnetic sensors using unscented Kalman filter and relative motion constraint
, Article Journal of Intelligent and Robotic Systems: Theory and Applications ; Volume 90, Issue 1-2 , May , 2018 , Pages 161-170 ; 09210296 (ISSN) ; Salarieh, H ; Alasty, A ; Abediny, M ; Sharif University of Technology
Springer Netherlands
2018
Abstract
Human motion tracking has many applications in biomedical and industrial services. Low-cost inertial/magnetic sensors are widely used in human motion capture systems to obtain the orientation of the human body segments. In this paper, we have presented a quaternion-based unscented Kalman filter algorithm to fuse inertial/magnetic sensors measurements for tracking human arm movements. In order to have a better estimation of the orientation of the forearm and the upper arm, a constraint equation was developed based on the relative velocity of the elbow joint with respect to the inertial sensors attached to the forearm and the upper arm. Also to compensate for fast body motions, we adapted the...
Sound source localization in wide-range outdoor environment using distributed sensor network
, Article IEEE Sensors Journal ; Volume 20, Issue 4 , 2020 , Pages 2234-2246 ; Shouraki, S. B ; Iranmehr, E ; Linares Barranco, B ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2020
Abstract
Sound source localization has always been one of the most challenging subjects in different fields of engineering, one of the most important of which being tracking of flying objects. This article focuses on sound source localization using fuzzy fusion and a beamforming method. It proposes a new fuzzy-based algorithm for localizing a sound source using distributed sensor nodes. Eight low-cost sensor nodes have been constructed in this study each of which consists of a microphone array to capture sound waves. Each node is able to record audio signals synchronously on an SD card to evaluate different algorithms offline. However, the sensor nodes are designed to be able to estimate the location...
Implementation of translational motion dynamics for INS data fusion in DVL outage in underwater navigation
, Article IEEE Sensors Journal ; Volume 21, Issue 5 , 2021 , Pages 6652-6659 ; 1530437X (ISSN) ; Hashemi, M ; Salarieh, H ; Alasty, A ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2021
Abstract
Underwater navigation is generally accomplished through the data fusion of INS (Inertial Navigation System) and auxiliary sensors such as DVL (Doppler Velocity Logger) sensor. However, because of the possibility of DVL outage, alternative low-cost solutions are attractive. Among these, one is using vehicle kinetic model information extracted by the Newton-Euler equation to improve INS performance, which is called model-aided navigation. In this paper, only the vehicle translational motion dynamics are used to replace DVL in underwater navigation in DVL outage. The vehicle 3D translational dynamics has been obtained by using general Newton-Euler equations. Integrating these dynamics leads to...
Change Point Detection in Molecular Carrier Based Nano Networks
,
M.Sc. Thesis
Sharif University of Technology
;
Nasiri Kenari, Masoumeh
(Supervisor)
;
Aminzadeh Gohari, Amin
(Co-Advisor)
Abstract
Molecular communication (MC) is an emerging communication paradigm, whereas molecules are used as information carriers to establish communication among elements in nano-meter to meter scales. In this thesis, we investigate the problem of detecting and monitoring changes (abnormality) based on molecular communication, using quickest change point detection scheme. We assume the distributions and parameters of the system are known. To this end, we consider a network of multiple sensors, each sensing its surrounding and employing On-Off-keying modulation for data transmission toward a fusion center (FC). An abnormality initiates randomly in time and location, and further propagates in the...
A Data Mining Approach for Prognostics and Health Monitoring Using Age Based Clustering: A Case Study on a Gas Turbine Compressor
, Ph.D. Dissertation Sharif University of Technology ; Durali, Mohammad (Supervisor) ; Saadat, Mahmoud (Supervisor)
Abstract
In recent years health monitoring and prognostics of complex systems have been considered more than ever.. In the present researh, data - based approach has been selected among various prognostics and health monitoring approaches. One of the most challenging issues in data-based methods is how to map system sensor information to its health status. In this research, different methods of mapping are discussed. The results show that sensor fusion by principal component analysis (PCA) offers acceptable performance. This pattern produces a single-dimensional signal for health monitoring with high reliability.The second challenge is to predict the status and design of the prognostics module. For...
Augmenting Inertial Motion Capture with SLAM Using EKF and SRUKF Data Fusion Algorithms
, M.Sc. Thesis Sharif University of Technology ; Salarieh, Hassan (Supervisor)
Abstract
Inertial motion capture systems widely use low-cost IMUs to obtain the orientation of human body segments, but these sensors alone are unable to estimate link positions. Therefore, this research used a SLAM method in conjunction with inertial data fusion to estimate link positions. SLAM is a method that tracks a target in a reconstructed map of the environment using a camera. This paper proposes quaternion-based extended and square-root unscented Kalman filters (EKF & SRUKF) algorithms for pose estimation. The Kalman filters use measurements based on SLAM position data, multi-link biomechanical constraints, and vertical referencing to correct errors. In addition to the sensor biases, the...
Concurrent orbit and attitude estimation using minimum sigma point unscented Kalman filter
, Article Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering ; Vol. 228, issue. 6 , 2014 , p. 801-819 ; Pourtakdoust, S. H ; Sharif University of Technology
Abstract
Concurrent orbit and attitude determination (COAD) plays a key role in reducing the cost of navigation and control subsystem for small satellites. This article is devoted to the problem of the COAD of satellites. A measurement package consisting of three axis magnetometer (TAM) and a sun sensor is shown to be sufficient to estimate the attitude and orbit information. To this end, an autonomous gyro-less COAD algorithm is proposed and implemented through the centralized data fusion of the TAM and the sun sensor. The set of nonlinear-coupled roto-translation dynamics of the satellite is used with a modified unscented Kalman filter (MUKF) to estimate the full satellite states. The MUKF is...
A novel approach for improvement of network lifetime and quality of service in wireless sensor networks
, Article Proceedings - 5th International Multi-Conference on Computing in the Global Information Technology, ICCGI 2010, 20 September 2010 through 25 September 2010 ; 2010 , Pages 274-278 ; 9780769541815 (ISBN) ; Pour Ali Akbar, E ; Ghalavand, M ; Movaghar, A ; Sharif University of Technology
Abstract
Wireless sensor networking remains one of the most exciting and challenging research domains of our time. Sensor nodes are arranged in the clusters and relay nodes could have been used as cluster head with more power, but this method has a Low Speed for networks with many sensors. In another method Storage and forwarding nodes are used to transfer the data from sensors to the base station. In this method, the data might have been failed due to the damage of the storage node. In this article, a hybrid method has been used to improve the network quality, which in that network, in addition to the forwarding and storage nodes, there is also cluster head. The purpose of this article is to solve...
An effective data aggregation mechanism for wireless sensor networks
, Article 2010 6th International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2010, 23 September 2010 through 25 September 2010 ; September , 2010 ; 9781424437092 (ISBN) ; Sharif University of Technology
2010
Abstract
Wireless sensor networks are tiny devices with limited computation and energy capacities. For such devices, data transmission is a very energy-consuming operation. It thus becomes essential to increase the lifetime of a WSN by minimizing the number of bits sent by each device. One well known approach is to aggregate sensor data. Data aggregation is used to eliminate redundancy and minimize the number of transmissions in order to save energy. Most energy efficient aggregation protocols have focused on cluster-based structure approaches. In this paper, we investigate the efficiency of data aggregation by focusing on two aspects of the problem: first how to improve cluster-based routing...