Controlled-mobile Sensor Networks for Dynamic Sensing and Monitoring Applications

Many potential indoor sensing and monitoring applications are characterized by hazardous and constantly-changing operating environments. For example, consider emergency response scenarios such as urban fire rescue. Traditionally, first responders have little access to situational information. In-situ information about the conditions, such as the extent and evolution of the indoor fire, can augment rescue efforts and reduce risk to emergency personnel. Static sensor networks that are pre-deployed or manually deployed have been proposed for such applications, but are less practical due to need for large infrastructure, lack of adaptivity and limited coverage. The main hypothesis of this thesis is that controlled-mobile networked sensing – the capability of nodes to move as per network needs, is a novel, feasible, and beneficial approach to monitoring dynamic and hazardous environments. Controlled-mobility in sensor networks can provide the desired autonomy and adaptability to overcome the limitations of static sensors. The research focuses on four of the major challenges in realizing controlled-mobile sensor networking systems: Understanding the trade-off between cost, weight, and sensing and actuation capabilities in designing a hardware platform for controlled-mobile sensing together with a complementary firmware architecture. Designing simulation environments for controlled-mobile sensing platforms that adequately incorporate both the cyber (network, processing, planning) and physical (motion, environment) components of such systems. Investigating the effects of controlled-mobility on network group discovery and maintenance protocols and designing approaches that meet the mobility, latency and energy constraints. Exploring novel low-overhead infrastructure-less mechanisms for collaborative coverage, deployment and navigation of resource-constrained controlled-mobile nodes in previously unseen environments. The thesis validates and evaluates the presented architecture, tools, and algorithms for controlled-mobile sensing systems through extensive simulations and a real-system test-bed implementation. The results show that controlled-mobility is feasible and can enable new class of sensing and monitoring applications