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This paper presents a new algorithm making use of kurtosis, which is a statistical parameter, to distinguish the seismic signal generated by a person's footsteps from other signals. It is adaptive to any environment and needs no machine study or training. As persons or other targets moving on the ground generate continuous signals in the form of seismic waves, we can separate different targets based on the seismic waves they generate. The parameter of kurtosis is sensitive to impulsive signals, so it's much more sensitive to the signal generated by person footsteps than other signals generated by vehicles, winds, noise, etc. The parameter of kurtosis is usually employed in the financial analysis, but rarely used in other fields. In this paper, we make use of kurtosis to distinguish person from other targets based on its different sensitivity to different signals. Simulation and application results show that this algorithm is very effective in distinguishing person from other targets.

Topology control plays an important role in the design of wireless ad hoc and sensor networks and has demonstrated its high capability in constructing networks with desirable characteristics such as sparser connectivity, lower transmission power, and smaller node degree. However, the enforcement of a topology control algorithm in a network may degrade the energy-draining balancing capability of the network and thus reduce the network operational lifetime. For this reason, it is important to take into account energy efficiency in the design of a topology control algorithm in order to achieve prolonged network lifetime. In this paper, we propose a localized energy-efficient topology control algorithm for wireless ad hoc and sensor networks with power control capability in network nodes. To achieve prolonged network lifetime, we introduce a concept called energy criticality avoidance and propose an energy criticality avoidance strategy in topology control and energy-efficient routing. Through theoretical analysis and simulation results, we prove that the proposed topology control algorithm can maintain the global network connectivity with low complexity and can significantly prolong the lifetime of a multi-hop wireless network as compared with existing topology control algorithms with little additional protocol overhead.