Search

Following in the footsteps of the field Networked Infomechanical Systems (NIMS) currently deployed at the James San Jacinto Mountain Reserve in Idyllwild California, two smaller scale NIMS architectures have emerged. The Laboratory Systems (NIMS-LS) provides an experimental testbed for verification of actuated sensing of environmental phenomena. The NIMS-LS System also includes emulation of environmental phenomena (i.e. light distribution in ecosystems). The Rapidly Deployable (NIMS-RD) platform provides a flexible means of sampling environmental phenomena directly with minimal infrastructure, rapid deployability and minimal impact on the environment. NIMS-RD has been deployed at the James San Jacinto Mountain Reserve, Medea Creek in the Santa Monica Mountains, Merced River in Merced CA and White Mountains Research Station near Bishop CA.

Rapidly growing stress on the natural environment has created an urgent demand for new environmental exploration systems that operate remotely and autonomously. As sensor networks are applied to these critical environmental monitoring problems, a series of new requirements have emerged for extensive characterization of dynamic phenomena in three-dimensional environments. The unpredictable presence of obstacles to sensing and the inherent temporal evolution of events create limitations for optimal deployment of sensors in the environment. Networked Infomechanical Systems (NIMS) technology has been developed to introduce precise and sustainable actuation for distributed sensing. NIMS devices are suspended on cable infrastructure to provide a combination of broad range motion combined with accurate localization.

Rapidly growing stress on the natural environment has created an urgent demand for new environmental exploration systems that operate remotely and autonomously. As sensor networks are applied to these critical environmental monitoring problems, a series of new requirements have emerged for extensive characterization of dynamic phenomena in three-dimensional environments. The unpredictable presence of obstacles to sensing and the inherent temporal evolution of events create limitations for optimal deployment of sensors in the environment.