Biological Sensor System Design for Gymnasium Indoor Air Protection

Abstract

Increasing attention is being directed to the vulnerability of public buildings, and national defense facilities to terrorist attack or the accidental release of biological pathogens. Many biological sensors have been developed for protecting the indoor air quality. However, there is lack of fundamental system-level research on developing sensor networks for indoor air protection. The optimal design of a sensor system is affected by sensor parameters, such as sensitivity, probability of correct detection, false positive rate, and response time. This study applies CONTAM in the sensor system design. Common building biological attack scenarios are simulated for a gymnasium. Genetic algorithm (GA) is then applied to optimize the sensor sensitivity, location, and quantity, thus achieving the best system behavior and reducing the total system cost. Assuming that each attack scenario has the same probability for occurrence, optimal system designs that account for the simulated possible attack scenarios are obtained.