Connected Camera Architecture for Cost-Effective ADAS Processing
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Solution Overview
Problem
Conventional dash cameras face challenges in implementing Advanced Driver Assistance Systems (ADAS) features due to high computational complexity and cost, as they require powerful processors, limiting the range of features that can be upgraded over the device's lifespan without increasing costs.
Innovation Solution
A system comprising a camera module and a computation device that operate in multiple communication modes, allowing the camera module to switch modes and send video frames for processing, using a processor with GPU capabilities to analyze video frames for ADAS features, while maintaining cost-effectiveness and interoperability with various devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If a powerful processor with GPU capabilities is integrated into the dash camera to enable ADAS features, then the processing capability and feature richness are improved, but the device cost increases drastically
Solution Approach 1:
The patent extracts the powerful processing capability from the dash camera device itself and places it in a separate cloud-based server. The dash camera retains only basic video capture and encoding functions, while ADAS processing is performed remotely. This resolves the contradiction by achieving high processing capability without integrating expensive hardware into the camera device.
Solution Approach 2:
The patent introduces a communication module as an intermediary between the dash camera and the cloud server. This mediator enables the transmission of video data and processing results, allowing the system to leverage remote computational power while keeping the local device simple and cost-effective.
2Ease of manufacture
If the processor is designed for Digital Video Recorder (DVR) applications with specific components for video encoding, then the device cost is reduced, but the processor cannot be used for implementing ADAS features
Solution Approach 1:
The patent makes the system universally adaptable by separating the function of video capture (performed by the inexpensive DVR processor in the dash camera) from the function of ADAS processing (performed by the cloud server). This allows a single low-cost processor to serve multiple purposes through cloud-based enhancement, achieving versatility without increasing device complexity.
Solution Approach 2:
The patent introduces dynamic adaptability by allowing the dash camera to connect to different cloud servers and access different ADAS features as needed. The system can dynamically adjust its capabilities based on available computational resources in the cloud, rather than being constrained by fixed onboard hardware.
3Extent of automation
If additional circuitry for implementing powerful processors is added to the dash camera, then the ADAS features can be implemented, but the device cost increases and widespread use is inhibited
Solution Approach 1:
The patent creates a virtual copy of the powerful processing capabilities in the cloud server, which then services multiple dash cameras. Instead of each camera needing its own expensive processor, the computational power is replicated and shared across the network, dramatically reducing per-device costs while maintaining full ADAS functionality.
4Power
If the dash camera is modified to include powerful processors for ADAS features, then the processing capability is improved, but the driver is tied to a limited set of features that cannot be upgraded over the life-cycle of the dash camera
Solution Approach 1:
The patent creates a dynamic system where ADAS features can be updated and upgraded remotely through the cloud server without any physical modification to the dash camera hardware. New algorithms and features can be deployed to the cloud server and automatically made available to connected devices, enabling continuous improvement throughout the product lifecycle.
Data Source
AI summary
The invention provides a system and method of monitoring a vehicle during commute. The system comprising of one or more camera modules in communication with one or more computation device. A camera module is configured to collect multiple data during the commute including video frames of one or more views, and location, position, direction, orientation, velocity and the combination thereof of the vehicle. The collected data is sent to a computation device where the data is analyzed to identify events and the same will be notified to one or more user device(s). In one embodiment, the communication between the computation device and the camera module may be carried out wirelessly via Wi-Fi where the camera module is configured to act in one or more modes of communication such as an access point (AP) mode or a station (STA) mode or Wi-Fi direct or the combination thereof.