Analyzing the Applicability of Smartphone Sensors for Roadway Obstacle Identification in an Infrastructure-Free Environment Using a Soft Learning Approach
Modern-day smartphones are inbuilt with numerous sensors capable of identifying critical information from various fields. Smartphone sensors are cheap, handy, easily available and therefore useful for several purposes. Smartphone sensors can be used to identify roadway obstacles and assist vehicle drivers in handling various obstacles while driving. In this study, we analyzed the applicability of smartphone sensors to assess their usefulness in reference to roadway obstacle detection in an infrastructure-free environment using a soft learning approach. Using our approach, we found that an accelerometer, CMOS and localization sensors are the most useful and cost-effective sensors which can be used for obstacle detection and tracking in infrastructure-free environments.
KeywordsSmartphone Sensors Obstacle detection Accuracy Efficiency Driver support system
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