An adaptive routing protocol for health monitoring with a sensor network and mobile robot

In this paper, we developed an adaptive route selection algorithm for a Mobile Ad-hoc Network (MANET). This algorithm has been realized and implemented for health monitoring applications with sensor nodes and a mobile robot. The health care devices include a body-pose estimation module, and a SpO₂ and ECG sensor module. These sensor modules wore on individuals and the mobile robot itself form a mobile sensor network. Conventional Ad-hoc On-demand Distance Vector (AODV) looks for a route which has the smallest hop count, but the route with the smallest hop count might not be the best route. In this paper we propose a novel routing protocol that features to combine signal strength and battery level into account, and uses fuzzy inference to search for a route with stable RF signals. Simulation results show that the packet delivery ratio increases from 81% to 90%. In practical experiment on a Zigbee MANET, the packet delivery ratio improves from 66% to 94%. The proposed MANET has also been experimented in practical health care application by integrating a pose estimation module, a SpO₂ sensor and a mobile robot.