Sponsor: National Science Foundation (ENG/EECS Division)
Collaborator: Prof. Guoliang Xing (Lead-PI, Computer Science and Engineering)
This project aims to establish a principled framework for the design and operation of aquatic sensor networks consisting of resource-limited nodes. We will exploit adaptation and collaboration among nodes to holistically deal with or even leverage uncertainties in sensing, communication, and mobility. Main research thrusts include online sensor and fusion calibration for dynamic environments, model-driven radio power adaptation to achieve assured communication performance, and exploitation of node mobility and fluid motion in the joint optimization of sensing, networking, and control to realize efficient coverage and tracking. We will experimentally validate the approach in detection and tracking of harmful algal blooms at the MSU Kellogg Biological Station using networks of robotic fish.