This paper introduces a fuzzy sensor validation and fusion methodology and applies it to sensor data from a gas turbine power plant. The FUSVAF (Fuzzy Sensor Validation and Fusion) algorithm tackles two problems: (1) It filters out noise from measurements provided as input to a gas turbine controller to maximize power plant performance. (2) It compensates for sensor failure to allow the power p...

In this work, we propose a new data processing architecture as well as track association and fusion algorithms to improve target classification and tracking accuracy using distributed and, possibly, legacysensor platforms. We present a robust data fusion algorithm that can incorporate target classes/types at the fusion center when receiving sensor reports and/or local tracks. We aim to tackle t...

Secure and accurate data fusion is an important issue in wireless sensor networks (WSNs) and has been extensively researched in the literature. In this paper, by combining clustering techniques, reputation and trust systems, and data fusion algorithms, we propose a novel cluster-based data fusion model called Double Cluster Heads Model (DCHM) for secure and accurate data fusion in WSNs. Differe...

Towards having computers understand human users’ “context” information, this dissertation proposes a systematic context-sensing implementation methodology that can easily combine sensor outputs with subjective judgments. The feasibility of this idea is demonstrated via a meeting-participant’s focus-of-attention analysis case study with several simulated sensors using prerecorded experimental da...

Intrusion detection is an important class of wireless sensor network applications with critical performance requirements. Due to the high deployment cost, it is crucial to understand and predict the intrusion detection capability of a surveillance sensor network. However, most existing analytical studies are based on simplistic sensing models (e.g., the disc model) that do not capture the stoch...

Multi-biometrics, or the fusion of more than one biometric modality, sample, sensor, or algorithm, is quickly gaining popularity as a method of improving biometric system performance and robustness. Despite the recent growth in multibiometrics research, little investigation has been done to explore the possibility of achieving multi-modal fusion from a single sensor. This approach to multi-biom...

For a multi-hop wireless sensor network, the limited sensing and communication resources give rise to distinct challenges to the task of tracking mobile targets, which is traditionally treated primarily from the data fusion perspective. This paper investigates the impact of sensor management on data fusion in a resource-limited network. A localized multi-sensor multi-target tracking framework i...

It is important for the life time of a wireless sensor network (WSN) to reduce the amount of data transferred through the network. As a typical approach, sensor data is filtered before propagating updates, to a node at the edge of a network, where it can be fused. Information Fusion inside the network can reduce the amount of data propagated, by fusing data before and in propagation, without lo...

For node deployment of heterogeneous sensor networks, based on different probability sensing models of heterogeneous nodes and an organic small molecule model, a ‘class-molecule’ sensing model of heterogeneous nodes is proposed. Combining it with DSmT data fusion model, the change of network coverage ratio after using the new sensing model and data fusion algorithm is studied. Furthermore, acco...