This book introduces resource-aware data fusion algorithms to gather and combine data from multiple sources, such as sensors, to achieve inferences. These techniques can be used in centralized and distributed systems to overcome sensor failure, technological limitations, and spatial and temporal coverage problems. The algorithms described in this book are evaluated with simulation and experimental results to demonstrate their ability to maintain data integrity and make data useful and informative. It describes techniques to address real problems posed by wireless sensor networks deployed in environments that might interfere with measurements, such as strong variations in pressure, temperature, radiation, and electromagnetic noise. The book uses simulation and experimental results to evaluate the presented algorithms and includes a real test-bed, along with a case study implementing data fusion algorithms.