abstract
- The notion of combining redundant and complementary sensory data to achieve higher quality information has been around for long time. For example, biological systems usually rely on fusion of multimodality sensory data to perceive the surrounding environment. There has been an ever-increasing interest in multi-disciplinary research on multisensor data fusion technology driven by its versatility and diverse areas of application. This paper presents an overview of data fusion state of the art discussing advances in fusion methodologies and architectures. In addition, future directions of research in data fusion community including large-scale, hybrid, secure fusion, and importance of standard evaluation framework are highlighted and described.