Smartphones serve as a technical interface to the outside world. These devices have embedded, on-board sensors (such as accelerometers, WiFi, and GPSes) that can provide valuable information for investigating users' needs and behavioral patterns. Similarly, computers that are embedded in vehicles are capable of collecting valuable sensor data that can be accessed by smartphones through the use of On-Board Diagnostics (OBD) sensors. This paper describes a prototype of a mobile computing platform that provides access to vehicles' sensors by using smartphones and tablets, without compromising these devices' security. Data such as speed, engine RPM, fuel consumption, GPS locations, etc. are collected from moving vehicles by using a WiFi On-Board Diagnostics (OBD) sensor, and then backhauled to a remote server for both real-time and offline analysis. We describe the design and implementation details of our platform, for which we developed a library for in-vehicle sensor access and created a non-relational database for scalable backend data storage. We propose that our data collection and visualization tools are useful for analyzing driving behaviors; we also discuss future applications, security, and privacy concerns specific to vehicular networks.