DRIVR Network is A.I. Driven
DRIVR A.I. Research And Development
DRIVR Network primary focus is to be A.I. driven. Our frame work, ride-share echo system and blockchain is designed to provide intelligence to smart cars while mitigating risk on the roads via Machine Learning, Camera-based machine vision systems, Sensor data fusion or Cloud Intelligence. DRIVR aims to be the forefront of higher-order critical, creative & thinkers in advanced AI technology by implementing cutting edge algorithms and deep learning
Cloud computing has many advantages that make it the perfect platform for utilizing AI technology within the automotive industry. Deploying fast processing speeds and increased data storage allows for cutting-edge edge development of automotive technology
How can our cloud-based AI platforms benefit automotive industry in the near future
- Providing alternative means for the driver to pay for their fuel
- Locating nearby shops / food outlets that are previously visited by the driver.
- Token based / cryptocurrency payment solutions embedded into the driver interface.
- Vehicle network and data security
- Automated on-road customer service
- Setting reminders to purchase needed household items as the driver approaches relevant stores.
- With the power of cloud-based platforms this list is certain to expand exponentially
Moving towards true AI framework, machine learning is a set of algorithms that attempt to model high-level data concepts by using architectures of multiple non-linear transformations. Machine learning can be used to predict infrastructure issues.
A crucial part of machine learning is various deep learning architectures such as deep neural networks (DNNs), convolutional neural networks (CNNs), and deep belief networks. These architectures are being applied to various fields such as automatic speech recognition, computer vision, natural language processing, and music/audio signal recognition where they have proven to be astoundingly responsive and accurate.
How can machine learning benefit drivers & smart cars?
- More efficient pick up times to drive to established routs
- Data filtered through high tech mapping & satellites
- Traced routs of popular pick-up points for cars to have
point to point system similar to train a circuit
- Infotainment human-machine interface
- speech recognition
- gesture recognition
- eye tracking and driver monitoring
- virtual assistance and natural language interfaces.
- Driver face analytics and emotion recognition
- Object detection/identification/avoidance
- Predictive maintenance
- Warning the driver multiple times about a particularly
dangerous driving habit you have before AI taking control of the wheel