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Visual Simultaneous Localization and Mapping (SLAM) has been used for markerless tracking in augmented reality applications. Distributed SLAM helps multiple agents to collaboratively explore and build a global map of the environment while estimating their locations in it. One of the main challenges in Distributed SLAM is to identify local map overlaps of these agents, especially when their initial...
In order to improve the network coverage, this paper presents the research on wireless sensor network coverage based on improved particle swarm optimization algorithmfor wireless sensor nodes that are randomly deployed in a certain area. In this paper, we use the regional network coverage as the target objective function, and combine various improved particle swarm optimization algorithms to optimize...
Wireless sensor network is composed of many wireless sensor nodes with the same or different functions. A typical sensor node consists of four parts: sensor unit, information processing unit, wireless communication unit and energy supply unit. In this paper, the existing ant colony algorithm is analyzed, and an improved ant colony optimization algorithm is proposed. The paper presents design of routing...
Many benefits can derive by a massive integration of distributed energy resources (DERs) into distribution system; in this view a big issue concerns the treatment of the high number of information needed for a full exploitation of DERs, which require new functionalities and tools for their management and control. A possible solution is to introduce virtual aggregations, such as load areas and virtual...
This paper presents an automated hermetic failure monitoring system design for multiple millimeter-sized biomedical implants using an inductive link array. 1 × 1 mm2 sized passive implants, wrapped with power receiving and data transmitting inductor-capacitor (LC) tank, and coated with parylene-C and polydimethylsiloxane (PDMS) were utilized for packaging failure monitoring, which can result in phase-dip...
A hydrological sensor network is a comprehensive monitoring system which consists of varieties of hydrological stations. The spatial optimization of the deployment of these gauging stations is critical for obtaining hydrological information effectively, given that sensing resources are often limited. In this paper, we consider the hydrological station siting problem as a continuous location problem...
In job-centric monitoring, monitors gather series of measurements, e.g., the used CPU load, per job. In domains where jobs are expected to behave similar, job-centric monitoring allows detecting misbehaving jobs based on a reference series of measurements. However, current detection approaches neglect time-drifts in series, e.g., caused by different CPU speeds and therefore potentially cause false...
Probing is a technique used for network monitoring and measurement applications, including detection of silent failures and performance analysis to verify compliance with service-level agreements. Many existing approaches to probing-path selection seek to minimize the number of probes (an NP-hard problem) or to minimize probing delay, but they fail to properly assess the network overhead imposed by...
Event correlation is the task of detecting dependencies between events in event sequences, e.g., for predictive maintenance based on log-files. In this work, a new data-driven, generic framework for event correlation is presented. First, we use a fast preliminary test statistic to determine candidate event type pairs. Next, the precise distribution of the time lag between those pairs is calculated...
When faults happen at gas path components of gas turbines, some charged abnormal debris will be generated. An electrostatic sensor can be installed at the tail end of the exhaust pipe to monitor the abnormal debris online and further indicate the faults. However, the electrostatic sensor itself is faced with a problem of function failure because of a severe working condition of high temperature and...
Condition based maintenance (CBM) is a practical and effective way to guarantee the product availability. Recent years the optimization strategy of CBM is widely studied by researchers. For product with measurable degradation performance, degradation modeling plays an important role in CBM. Inverse Gaussian process has many superb properties in dealing with covariates and random effect. In this paper,...
Fault isolation is an essential step in multivariate statistical process monitoring, which discovers the cause of the detected fault. The common adopted techniques for fault isolation, such as contribution plots, reconstruction analysis, branch and bound, etc., often suffer from the problems of the smearing effect, insufficient historical fault data, and heavy computational burden. In this paper,...
Modern chemical processes are usually characterized by large-scale, complex correlation, and strong dynamics, and monitoring of such processes is imperative. This paper proposes a performance-driven fault-relevant dynamic principal component (FRDPC) subspace construction integrated with Bayesian inference method to achieve efficient monitoring for dynamic chemical processes. First, dynamic principal...
In tourism industry, a challenge is how to handle emergency situations during a journey. Although most of the tourism travel agencies focus on generating travel plans, an important part that has been ignored is to provide a creative emergency travel plan when a user meets an unforeseen situation during the journey. Thus, in order to address problems like this, the study to build a system that can...
In the urban water supply system, the location and quantity of the pressure monitoring nodes play a significant role for the monitoring effect and the response warning of the pipe burst. However, most installation of pressure monitoring nodes are based on human experience, which cannot totally present the whole water supply system condition. In view of the unreasonable layout of pressure monitoring...
Dissolved oxygen directly affects the growth status of fishes in intensive aquaculture, thus we set up a prediction model to determine the future changing trend of dissolved oxygen. The dissolved oxygen prediction model we proposed was based on the least squares support vector regression (LSSVR) model with fruit fly optimization algorithm (FOA) to find optimal parameters (γ and σ) of LSSVR. Because...
In this paper we introduce the SDNRoute system which aims to support routing decisions in Software Defined Networks. Such a system is especially important in the context of the SDN as this concept makes it possible to perform routing in a dynamic and elastic manner. We focus on the SDNRoute architecture and research challenges that must be investigated to develop the system. Additionally, we provide...
We study optimal input design and bias-compensating parameter estimation methods for continuous-time models applied on a mechanical laboratory experiment. Within this task we compare two online estimation methods that are based on Poisson moment functions with focus on quantized system outputs due to an angular encoder: The standard recursive least-squares (RLS) approach and a bias-compensating recursive...
An optical network, like any system, has to be observable before it can become subject to optimization. This is the main capability that the ORCHESTRA project introduces. ORCHESTRA's high observability relies on information provided by the coherent transceivers that can be extended, almost for free, to operate as software defined optical performance monitors (soft-OPM). Monitoring information is processed...
In Internet of Things (IoT) environments, there are multiple sensors and devices monitoring different metrics and producing massive amounts of data. Monitoring of metrics can be done at different frequencies. Systems and applications that consume monitoring data typically use constrained IT resources, e.g., constrained network facilities, storage, display, processing/computing power, and energy. Given...
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