Technological advances in the field of ecology allow data on ecological systems to be collected at high resolution, both temporally and spatially. Devices such as Dual-frequency Identification Sonar (DIDSON) can be deployed in aquatic environments for extended periods and easily generate several terabytes of underwater surveillance data which may need to be processed multiple times. Due to the large amount of data generated and need for flexibility in processing, a distributed pipeline was constructed for DIDSON data making use of the Hadoop ecosystem. The pipeline is capable of ingesting raw DIDSON data, transforming the acoustic data to images, filtering the images, detecting and extracting motion, and generating feature data for machine learning and classification. All of the tasks in the pipeline can be run in parallel and the framework allows for custom processing. Applications of the pipeline include monitoring migration times, determining the presence of a particular species, estimating population size and other fishery management tasks.

We discuss the possibility of improving eyehand coordination in children diagnosed with this problem, using a robotic mapping from a haptic user interface to a virtual environment. Our goal is to develop an assessment and training procedure that will result in improving handwriting taking the advantage of the force feedback provided by the haptic device. Force feedback can be used to guide the subject's hand in a predetermined trajectory when he/she is unable to move in response to visual feedback. We also incorporate the inertia and viscosity effects to decrease the tremor in the hand as well as to stimulate the muscles involved in the task of holding a pencil (known as facilitation technique in the occupational therapy field). The robotic system is operated within ranges established by baseline data for accuracy of eye-hand coordination and grip strength. A set of assessment tests, commonly used by occupational therapists, were chosen to implement the various functions using force, inertia and viscosity effects. The test bed used for these tasks consisted of a six-degree-of-freedom force reflecting haptic interface device, PHANToM with the GHOST SDK Software. Preliminary data obtained from two children diagnosed with eye-hand coordination problems show that the assistance provided, improved their ability to execute and complete the tasks, suggesting that the system could be used for assessment and training purposes. In addition, these results suggest that the introduction of the haptic rendering capabilities, including the force feedback, offers special benefit and measures the impact on the occupation of handwriting. Furthermore, a real application of this system could be implemented in the future, by identifying specific job tasks that may be made accessible through a desktop in classrooms by the aforementioned haptic system.