| Over the past decade, many wireless sensor network systems have been deployed in various real-life environments with the goal of remotely collecting data from the physical world. Such low-power wireless systems, when combined with low-power medical sensors, provide the potential to alleviate many of the manual routine tasks in the healthcare domain as well. In turn, such automation techniques in the patient monitoring process can help increase the quality of patient care at many of the busy clinical environments and disaster scenes.;In this dissertation, we present MEDiSN, a wireless sensor network system for monitoring the physiological data of patients in clinical environments or victims in disaster sites. MEDiSN consists of mobile patient monitoring devices that collect physiological data and connect to a self-configuring wireless backbone network to relay their data to a gateway. As a preparation step for our deployments, we experimentally analyze the wireless channel environment at our target clinical environment and finally, evaluate the performance of MEDiSN in a real clinical environment using multiple pilot studies. Furthermore, based on the development and deployment experiences of MEDiSN, this dissertation identifies several factors that can assist wireless sensing systems to expand their horizons to new applications.;As an effort to address these factors, and moreover, expand the application coverage of the MEDiSN system, this dissertation introduces three major improvements made to MEDiSN. First, this dissertation introduces Egs, a more flexible and powerful mote platform. Egs is an ARM Cortex-M3-based mote platform that provides application developers with a powerful, yet, energy efficient sensing platform to serve in a variety of applications. Second, this dissertation discusses about the design and implementation experiences of Internet-standards compliant networking stacks for sensor networks. Specifically, we present the evaluation of the IETF RPL routing protocol's performance and also introduce experiences from testing the interoperability performance of sensor network IPv6 stacks using two independently-developed standard-compliant implementations. The final part of the dissertation presents two adaptive transmission power control techniques for mobile nodes in low-power wireless networks designed with the goal of minimizing energy consumption and maximizing bandwidth utilization. |
