Neuromorphic Sensor Fusion for Under Water Object Detection

The project aims to develop a protocol of multimodal data collection through neuromorphic sensors for underwater object detection.
The underwater object detection is very tricky phenomenon due to variability of environmental
changes like wave motion, salinity as well as visibility under water. Various sensors with different
ranges and properties can be deployed to overcome the adverse environmental conditions for object detection. However, increasing number of sensors increases the data processing power, noise and uncertainty in the process rendering the data fusion from these sensors difficult. The proven neuromorphic methods introduce a paradigm shift in handling these sensor uncertainties through sensor fusion and increasing the autonomy of the data management and decision making within the operating envelope of all the sensors used for the object detection task.