Abstract-The explosive growth in social network content suggests that the largest "sensor network" yet might be human.Extending the participatory sensing model, this paper explores the prospect of utilizing social networks as sensor networks, which gives rise to an interesting reliable sensing problem. In this problem, individuals are represented by sensors (data sources) who occasionally make observations about the physical world. These observations may be true or false, and hence are viewed as binary claims. The reliable sensing problem is to determine the correctness of reported observations. From a networked sensing standpoint, what makes this sensing problem formulation different is that, in the case of human participants, not only is the reliability of sources usually unknown but also the original data provenance may be uncertain. Individuals may report observations made by others as their own. The contribution of this paper lies in developing a model that considers the impact of such information sharing on the analytical foundations of reliable sensing, and embed it into a tool called Apollo that uses Twitter as a "sensor network" for observing events in the physical world. Evaluation, using Twitter-based case-studies, shows good correspondence between observations deemed correct by Apollo and ground truth.

Breadcrumb systems (BCS) have been proposed to aid firefighters inside buildings by communicating their physiological parameters to base stations outside the buildings. In this paper, we describe the design, implementation and evaluation of an automatic and robust breadcrumb system for firefighter applications. Our solution includes a breadcrumb dispenser with an optimized link estimator that is used to decide when to deploy breadcrumbs to maintain reliable wireless connectivity. The solution includes accounting for realities of buildings and dispensing such as the height difference between where the dispenser is worn and the floor where the dispensed nodes are found. We also include adaptive power management to maintain link quality over time.Experimental results from our study show that compared to the state of the art solution [14], our breadcrumb system achieves 200% link redundancy with only 23% additional deployed nodes. Our deployed crumb-chain can achieve 90% probability of end-to-end connectivity when one node fails in the crumb-chain and over 50% probability of end-to-end connectivity when up to 3 nodes fail in the crumb-chain. In addition, by applying adaptive transmission power control at each node after the crumb-chain deployment, we solve the link quality variation problem by avoiding significant variations in packet reception ratio (PRR) and maintain PRR of over 90% at the link level.

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