Integrating sensor fusion into embedded designs
In the world of mobile platforms and wireless sensor-based embedded designs, new techniques for sensor fusion will be needed to collect data on the location and conditions of everything from smartphones to wearable consumer Internet of Things devices.
Sensor Fusion: Theory and Application
The objective of sensor fusion is to determine that the data from two or more sensors correspond to the same phenomenon. Before the Internet, the association between two or more sensors would only occur within a single well-defined system. With the Internet, we can now access the signals of several sensors on an ad hoc basis. This capability is useless, however, without some means to determine the interdependencies of the sensors.
Data Fusion improves the coverage of wireless sensor networks
Exploring the limits of wireless sensor network coverage based on data fusion models that fuse noisy measurements of multiple sensors and the scaling laws that govern the relationship between coverage, network density, and signal-to-noise ratio (SNR).
A sensor fusion method for smart phone orientation estimation
A technique for improving Android smartphone orientation estimation through the use of a DNRF (Drift & Noise Removal Filter) that fuses sensor information from the gyroscope, magnetometer and accelerometer to minimize the drift and noise in output orientation.
Sensor fusion-based event detection in WSNs
A two-level sensor fusion-based event detection technique for wireless sensor networks that uses a fusion algorithm to gather information and reach a consensus among individual detection decisions made by sensor nodes.
A sensor fusion method for smart phone orientation estimation
A technique for improving Android smartphone orientation estimation through the use of a DNRF (Drift & Noise Removal Filter) that fuses sensor information from the gyroscope, magnetometer and accelerometer to minimize the drift and noise in output orientation.
