Wireless Mesh Network Performance for Urban Search and Rescue Missions

10.5121/ijcnc.2010.2203

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          Cristina Ribeiro1 Alexander Ferworn2 and Jimmy Tran2 1Department of Computer and Information Science, University of Guelph, Guelph, Canada cribeiro@uoguelph.ca 2Department of Computer Science, Ryerson University, Toronto, Canada aferworn@ryerson.ca, q2tran@ryerson.ca
ABSTRACT In this paper we demonstrate that the Canine Pose Estimation (CPE) system can provide a reliable estimate for some poses and when coupled with effective wireless transmission over a mesh network. Pose estimates are time sensitive, thus it is important that pose data arrives at its destination quickly. Propagation delay and packet delivery ratio measuring algorithms were developed and used to appraise Wireless Mesh Network (WMN) performance as a means of carriage for this time-critical data. The experiments were conducted in the rooms of a building where the radio characteristics closely resembled those of a partially collapsed building—a typical US&R environment. This paper presents the results of the experiments, which demonstrate that it is possible to receive the canine pose estimation data in real- time although accuracy of the results depend on the network size and the deployment environment.

KEYWORDS Wireless Mesh Network, WiFi, Transmission Delay, Propagation Delay, Packet Delivery Ratio, Wireless Networks for Computational Public Safety, Canine Pose Estimation, Canine Augmentation Technology & Urban Search and Rescue

1. INTRODUCTION The fastest and most reliable means of finding people trapped after a building collapse is through the use of trained Urban Search and Rescue (USAR) dogs. Sometimes called disaster dogs, these canines are the state-of-the-art when conducting search operations within an urban disaster like those that occurred in Mexico [1], Kobe [2], Turkey [3] or New York [4].
   Search operations necessarily occur before rescue can take place. Since there is a finite time that someone can survive entombed within the wreckage of a building, it is critical that search operations occur as quickly and efficiently as possible so that the ensuing operation is rescue and not recovery. Search operations have several challenges that increase the time it takes to find survivors (often called “patients”) within the wreckage.
   A particular matter requiring improvement is in the situational awareness [5-7] canine handlers have while conducting searches under certain conditions. Situations can arise where a handler is not aware of their dog’s whereabouts or behaviour. This lack of situational awareness is generally due to the distance and obstacles between the handler and the canine. In the extreme, a handler may be asked to send his or her dog into the rubble of a building without the ability to actually follow behind, because human access may be precluded or limited. If the handler’s situational awareness of the canine could be enhanced, search times could be reduced, improving the performance of the team, resulting in more lives saved.
   A complementary area of research is the augmentation of USAR dogs [8-11] with technology that allows emergency first responders to experience what is happening around the dog while it
             
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39 is searching. While this area of research is very important, the handler still does not know what the dog is actually doing while out of sight; this augmenting of senses focuses on what is around the dog and not the dog itself. This technology does however provide some additional situational awareness capabilities, but only from the perspective of the canine.
The orientation of the dog is very important for the handler as the dog’s posture communicates a significant amount of information. Orientation or posture, referred to as ’pose’, is important, because USAR canines are trained to display different poses to indicate various situational conditions they have experienced. In a sense, they use pose as a language. An example of this is a canine, which is cross-trained to search for cadavers. This specially trained dog assumes the sitting pose when it has found a cadaver. Another pose, lying down, indicates that the canine has stopped searching because of disinterest, exhaustion, or injury. Past research has been conducted on animals in terms of behavioural assessments [12]; however, not in the area of situational awareness which is needed for USAR operations. Handlers are limited in their capabilities to conduct searches in cases where their dogs cannot be seen. At the moment there are no solutions that provide the canine handler with situational awareness regarding canine pose. This paper begins with an overview of Computational Public Safety. In section 2 is a su

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