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    Design of intelligent garment with sensor fusion for rescue teams
    (GAZI UNIV, FAC ENGINEERING ARCHITECTURE, 2019) Esme, Engin.; Karlık, Bekir.
    Wearable technologies fulfill tasks such as acquiring important data, transmitting and displaying. Smart garments will be developed in order to increase the safety of personnel and make intervention more effective. In this study, an intelligent system has been designed for remote monitoring of the hazardous gases around the disaster area, the concentration of oxygen level in the environment, the ambient temperature and the mobility of the rescue team members. The search and rescue team leader can do the hazard analysis in more detail based on the accidental information using the developed system. The system consists of 2 electrochemical gas sensors, 2 metal oxide semiconductor sensors, a temperature sensor, a motion sensor, and a wireless communicating microcontroller platform. The main difference of this developed prototype from conventional methods is to determine by a machine learning algorithm in which the gas encountered at the incident site belongs to the flammable-explosive, chemical liquid vapor or stifling group. Five classes have been created in the classification process by taking into consideration the fresh air and possible mixtures of gases. As a result of comparative experimental studies of three different methods, 94.25% classification accuracy was obtained by k-NN using method. The proposed smart garment can be used to explore disaster area for planning and intervention processes, and to make the operation more efficient and relia.