In smart environments, a multi-robot system is difficult to achieve a high confidence level of information for reliable decision making. The pieces of sensed information obtained from a multi-robot system have different degrees of uncertainty. Generated contexts about the situation of the environment can be conflicting even if they are acquired by simultaneous operations. In particular, unpredi...

The role of data fusion in sensor platforms is becoming increasingly important in various domains of science, technology and business. Fusion pertains to the merging or integration of information towards an enhanced level of awareness. This thesis provides a canonical overview of several major fusion architectures developed from the remote sensing and defense community. Additionally, it provide...

Nonlinear state estimation and fusion tracking are always hot research topics for information processing. Compared to linear fusion tracking, nonlinear fusion tracking takes many new problems and challenges. Especially, the performances of fusion tracking, based on different nonlinear filters, are obviously different. The conventional nonlinear filters include extended Kalman filter (EKF), unsc...

This study attempts to apply a back-propagation network (BPN) for multi-sensors data fusion in a wireless sensor networks (WSNs) system with a node-sink mobile network structure. This investigate is to finish the factory monitoring at environment monitoring services (EMS). These practice wireless sensor network circuits include temperature, humidity, ultraviolet, and illumination four variable ...

Distributed scenarios pose a big challenge to tracking and fusion systems. They require the prevention of repeatedly incorporating same information, which originates from ring closures in communication path would affect optimality. Additionally, multi-sensor multi-object Generalized Labeled Multi-Bernoulli filter update is NP-hard principle. The method proposed this paper tackles these problems...

The problem of multi-modal pattern recognition is considered under the assumption that the kernel-based approach is applicable within each particular modality. The Cartesian product of the linear spaces into which the respective kernels embed the output scales of single sensor is employed as an appropriate joint scale corresponding to the idea of combining modalities, actually, at the sensor le...

Fusion of multi-sensor imaging data enables a synergetic interpretation of complementary information obtained by sensors of different spectral ranges. Multi-sensor data of diverse spectral, spatial and temporal resolutions require advanced numerical techniques for analysis and interpretation. This paper reviews ten advanced pixel based image fusion techniques – Component substitution (COS), Loc...

According to the complexity of turbine on power plant, a kind of fault diagnosis method based on information fusion is proposed in this paper. Multi-sensor data is adopted and D-S evidence theory is applied, thus the uncertainty of information can be effectively overcome. Considering the data credibility of various information sources, the data fusion method is applied to the simulation experim...

Multi-sensor target tracking has traditionally been performed using a single processor to monitor several sensors (centralized fusion), but this method is demanding of both computational power and communication band-width. Distributed sensor fusion is a method of addressing these limitations. However, the distributed sensor fusion problem is more complex due to the correlation of separate track...

Technological advancements in the silicon industry, as predicted by Moore’s law, have enabled integration of billions of transistors on a single chip. To exploit this high transistor density for high performance, embedded systems are undergoing a transition from single-core to multi-core. Although a majority of embedded wireless sensor networks (EWSNs) consist of single-core embedded sensor nod...