CarKnow - "Avacar" Virtual Vehicles

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CarKnow's Cloud platform addresses difficulty accessing vehicle diagnostic information by providing hardware and software to simplify capturing, using, and reacting to sensor data. The CarKnow “CARduino” device is a GSM bridge between in-vehicle Controller Area Networks, on-device GPS and motion sensors, and a web platform leveraging MIT’s “CloudThink” object mirroring architecture. The data provided feed a secured REST API with clear privacy controls – users own their data, and any sharing is opt-in. Digital duplicate “Avacar” mirrors back applications ranging from data visualization to those improving comfort and convenience. GSM connectivity enables a low-latency, always-on connection, which applications can leverage for bidirectional communication – allowing mobile devices to remotely control vehicle functions such as locks, windows, or radio settings. Unlike existing telematics systems, which silo data, CarKnow allows cross-manufacturer applications and analytics to be developed and shared with consumers via an application store. With broader vehicle data, we can improve our understanding of common driver pain points and solve problems quickly. Information gathered additionally helps OEMs identify true use cases, and optimize in the design phase proactively. This is especially critical when trying to optimize the efficiency of a hybrid powertrain.

Vehicles provide unique data - a car might implement 200 sensors, and by nature, is a distributed sensing platform. User touchpoints are frequent, so there is quick-turn feedback to improve applications. Geographically disparate vehicles allow for large-scale sensing and data aggregation, feeding analytics that ultimately reduce traffic and fuel consumption, provide information about vehicle reliability, and validate theoretical models against real-world use scenarios.

The CARduino interfaces with an SAE-standardized On-Board Diagnostic (OBD) port. The additional use of multiple network transceivers allows access to manufacturer-specific data conventionally reserved for module-to-module communication. These sources are reverse-engineered by users on our Wiki, and are integrated with our API to allow single-command deployment across brands. The device also features innovative power-saving techniques, tamper-resistance, remote software updatability, and functions as a conventional diagnostic tool and logic analyzer. Existing logging solutions use only OBD2-regulated information.

Demonstration applications today include virtual dashboards using Google Streetview to show a real-time view of operating parameters and location, visualizations of historic fuel economy, engine speed, and idling locations, long-range cellular remote controls, prognostics (vehicle failure prediction and error analysis), and home automation integration using “If This Then That” (IFTTT) and the Belkin WeMo system. Most of these applications were developed in PHP and JavaScript and web-based to ease deployment and ensure currency.

The CarKnow hardware and software can improve the vehicle/driver dynamic, by helping optimize vehicle use during all phases -- design, operation, and maintenance. The software platform abstracts development complexities, and enables a host of new applications, as well as an application ecosystem facilitating the sale and distribution of these programs. Drivers will ultimately realize more convenient vehicle use, savings and reduced emissions during operation, and reduces frustration associated with traffic. The creation of such an ecosystem for development will encourage automotive OEMs to make more data accessible to end users and enable applications we can't yet imagine.

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  • ABOUT THE ENTRANT

  • Name:
    Josh Siegel
  • Type of entry:
    individual
  • Software used for this entry:
    EAGLE, SolidWorks, LTSpice, MATLAB, ANSYS HFSS
  • Patent status:
    pending