This paper presents hybrid Minimum Mean Squared Error-based estimators for wireless sensornetworks with time-varying communication-bandwidth constraints, focusing on the particular application of multi-robot Cooperat...
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ISBN:
(纸本)9781467363587
This paper presents hybrid Minimum Mean Squared Error-based estimators for wireless sensornetworks with time-varying communication-bandwidth constraints, focusing on the particular application of multi-robot Cooperative Localization. When sensor nodes (e. g., robots) communicate only a quantized version of their analog measurements to the team, our proposed hybrid filters enable robots to process all available information, i.e., local analog measurements (recorded by its own sensors) as well as remote quantized measurements (collected and communicated by other sensors). Moreover, these filters are resource-aware and can utilize additional bandwidth, whenever available, to maximize estimation accuracy. Specifically, in this paper, we present two filters, the Hybrid Batch-Quantized Kalman filter (H-BQKF) and the Hybrid Iteratively-Quantized Kalman filter (H-IQKF), that can process local analog measurements along with remote measurements quantized to any number of bits. We test our proposed filters in simulations and experimentally, and demonstrate that they achieve performance comparable to the standard Kalman filter.
Micro-aerial vehicle (MAV) swarms are emerging as a new class of mobile sensornetworks with many potential applications such as urban surveillance, disaster response, radiation monitoring, etc., where the swarm is ta...
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ISBN:
(纸本)9781450319591
Micro-aerial vehicle (MAV) swarms are emerging as a new class of mobile sensornetworks with many potential applications such as urban surveillance, disaster response, radiation monitoring, etc., where the swarm is tasked with collaboratively covering a hazardous unknown environment. However, efficient collaborative coverage is challenging due to limited individual sensing, computing and communication resources of MAV sensor nodes, and lack of location infrastructure in the unknown application environment. We present SugarMap, a novel system that enables such resource-constrained MAV nodes to achieve efficient sensing coverage. The self-establishing system uses approximate motion models of mobile nodes in conjunction with radio signatures from self-deployed stationary anchor nodes to create a common coverage map. Consequently, the system coordinates node movements to reduce sensing overlap and increase the speed and efficiency of coverage. The system uses particle filters to account for uncertainty in sensors and actuation of MAV nodes, and incorporates redundancy to guarantee coverage. Through large-scale simulations and a real implementation on the sensorFly MAV sensing platform, we show that SugarMap provides better coverage than the existing coverage approaches for MAV swarms.
This paper describes a work-in-progress programming experiment where the playground is an entire city. Based on the SmartSantander FIRE infrastructure, the CityScript project is aimed at integrating and experimenting ...
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ISBN:
(纸本)9780769549521;9781467362399
This paper describes a work-in-progress programming experiment where the playground is an entire city. Based on the SmartSantander FIRE infrastructure, the CityScript project is aimed at integrating and experimenting a Web of Things scenario in which sensors and actuators in the city have a digital counterpart and can eventually used to compose mashups with social networks and other digital online sources of data.
Nowadays, the wireless sensornetworks have critical applications in the environmental monitoring, medical, security, industrial and military fields. The forest fire detection as a monitoring network is one of these a...
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ISBN:
(纸本)9781467364904;9781467364898
Nowadays, the wireless sensornetworks have critical applications in the environmental monitoring, medical, security, industrial and military fields. The forest fire detection as a monitoring network is one of these applications. sensors collect dynamic changes such as temperature, humidity, smoke, atmospheric pressure and forward those to a single node or a base station. These informations are sent to a long-distance data server which is located in a fire center. Due to the importance of these networks and their ability of real-time monitoring, they should be a reliable network communications. On the other hand, due to the limitations of sensors in processing, memory and energy resource, we need protocols that consider these limitations, especially energy. Energy consumption is important because sensors are often remote, or are located in hazardous areas. Typically, the energy resources are very small batteries that are not rechargeable and replaceable. In this paper, the performance of three routing protocols: AODV, DSR, DSDV in the forest fire detection application based on a zigbee wireless sensor network are compared. The metrics for this comparison are average end-to-end delay, packet delivery ratio and energy consumption. We evaluate their performance using NS-2. Our results show that AODV is the best between these three protocols regarding packet delivery ratio but is the worst regarding energy consumption.
In this paper, a random amplitude weighting approach is proposed to guarantee the security at physical layers for distributed wireless sensornetworks. Each sensor estimates the channels by training symbols sending fr...
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The Internet of things is a massive electronic equipment with internet interconnection of large scale virtual networks, including RFID, sensor and actuator electronic devices by the internet interconnection. In order ...
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ISBN:
(纸本)9783037855959
The Internet of things is a massive electronic equipment with internet interconnection of large scale virtual networks, including RFID, sensor and actuator electronic devices by the internet interconnection. In order to solve internet of things architecture intelligent refrigerator key technologies, The paper had discussed the internet of things architecture intelligent refrigerator definition, characteristic as well as reference architecture, focused on analysis intelligent refrigerator information space definition, information quantification method and mobile platform equipment internet of things key technology main problems and corresponding solution ways.
We describe recent developments in sensor network fault detection and identification as a part of a broad intelligent Distributed and Ubiquitous Health Management System (IDU- HMS) concept. sensor network data faults ...
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We describe recent developments in sensor network fault detection and identification as a part of a broad intelligent Distributed and Ubiquitous Health Management System (IDU- HMS) concept. sensor network data faults are formulated and mathematical models are presented. Models for detection and identification of faults are developed for distributed systems with random spatial distribution of sensor nodes. We discuss various sensor network faults, their models and software for fault detection and fault informationprocessing. We include simulations of multiple faults in a network of sensors, describe an experimental test bed, and provide experimental results that shows the effectiveness of the proposed method.
The human sensory test is often used to obtain the sensory quantities of odors, however, the fluctuation of results due to the experts condition can cause discrepancies among panelists. We have developed an artificial...
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Estimation of the principal eigenspace of a data covariance matrix is instrumental in applications such as data dimensionality reduction and denoising. In sensornetworks the acquired data are spatially scattered whic...
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ISBN:
(纸本)9781479903566
Estimation of the principal eigenspace of a data covariance matrix is instrumental in applications such as data dimensionality reduction and denoising. In sensornetworks the acquired data are spatially scattered which further calls for the development of distributed principal subspace estimation algorithms. Toward this end, the standard principal component analysis framework is reformulated as a separable constrained minimization problem which is solved by utilizing coordinate descent techniques combined with the alternating direction method of multipliers. Computationally simple local updating recursions are obtained that involve only single-hop inter-sensor communications and allow sensors to estimate the principal covariance eigenspace in a distributed fashion. Adaptive implementations are also considered that allow online informationprocessing. Numerical tests demonstrate that the novel algorithm has the potential to achieve a considerably faster convergence rate and better steady-state estimation performance compared to existing alternatives.
This paper is concerned with the multi-sensor-based estimation problem in wireless sensor network. A stochastic competitive transmission strategy is proposed to stagger the sensors' transmissions. By using the asy...
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