in decreasing the cost and complexity of soft-
ware maintenance The builtin application upgrade mechanisms and communication channels on a smartphone make it possible to push updates to thousands or millions of clients and rollback if installation fails. We have found that this capability is quite helpful in maintaining/evolving the software in accident detection and notification systems It may not be possible to detect all accidents with
smartphones Due to the filters utilized to prevent false positives, it maybe possible to experience a low speed “fender-bender” without the application detecting it. More work is needed to enhance the filtering mechanisms to account for these types of collisions. In particular, WreckWatch’s filtering algorithm could be enhanced to determine whether the user is in a vehicle or not utilizing history information. For example, users often travel similar routes to work and WreckWatch could learn where stops or reductions in speed are common by analysis of trends (e.g. if a person usually travels through an area at 40 mph but occasionally slows to a stop indicating a potential traffic jam. Likewise, WreckWatch could use known intersections to identify potential stops and anticipate them or download traffic information to predict the location of traffic jams resulting from long-duration reductions in speed Acoustic data is not sufficient for detecting traffic
accidents Our empirical results show that some smartphone microphones and signal processing infrastructure suffers from signal clipping above dBs. This clipping makes it hard to differentiate sounds, such as shouting, from airbag deployment.
It is possible that this limitation can be overcome,
but it will require additional work.
WreckWatch is an open-source Android application that is freely available from code.google.com/p/
vtnetapps
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