Abstract
This work concerns the performance analysis of the sensors contained in a victim detection system. The system is a mobile platform with gas sensors utilized for real time victim localization in urban environments after a disaster has caused the entrapment of people in partially collapsed building structures. The operating principle of the platform is the sampling of air from potential survival spaces (voids) and the measurement of the sampled air’s temperature and concentration of CO2 and O2. Humans in a survival space are modelled as sources of CO2 and heat and sinks of O2. The physical openings of a survival space are modelled as sources of fresh air and sinks of the internal air. These sources and sinks dynamically affect the monitored properties of the air inside a survival space. In this paper, the effects of fresh air sources and internal air sinks are first examined in relation to local weather conditions. Then, the effect of human sources of CO2 and sinks of O2 in the space are examined. A model is formulated in order to reliably estimate the concentration of CO2 and O2 as a function of time for given reasonable entrapment scenarios. The input parameters are the local weather conditions, the openings of the survival space, and the number and type of entrapped humans. Three different tests successfully verified the presented theoretical estimations. A detection system with gas sensors of specified or measured capabilities, by utilizing this model and based on the expected concentrations, may inform the operator of the minimum required presence of humans in a survival space that can be detected after “some time”.
Highlights
The extraction of people from partially or completely destroyed buildings after a catastrophic event is executed in Urban Search and Rescue (USaR) missions
After a detection system is implemented, the analysis provided in this work can be used to provide a quick estimate of the feasibility of detecting, in the USaR operations field, a human at a specific location with given weather conditions
By applying (34) (Asum = 0.5 m2, g = 9.81 m/s2, z = 2.7 m, CR = 0.35, vre f ≈ 0.83 m/s, ∆C p = 0.44–1.51, T f = 20.5 ◦ C, and Tc = 21.5 ◦ C), we calculated that the expected fresh air flow rate at that point would be about 15.5 m3 /min ie Ff ≈ 920 Fe and, according to the theoretical expectations from Equation (36) it required Ff ≤ 956 Fe, the
Summary
The extraction of people from partially or completely destroyed buildings after a catastrophic event is executed in Urban Search and Rescue (USaR) missions. AI (Artificial Intelligence) based platforms to decide if a specific system with gas sensors is reliable enough to use and to prioritize the available search tools and not lose valuable time that may cost human lives. It would become one of the technologies that can assist, complement, or even replace trained search and rescue dog, especially in confined and narrow places. The human detection gas sensor-based scheme examined in this work operates by measuring CO2 and O2 concentration in the air in an attempt to detect changes caused by trapped humans.
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