Automobiles

Cloud computing has many benefits which make it an ideal platform for staging and deploying AI technology in the automotive field, which includes analytics, big data access and centralized connectivity. 

We work on cloud-based AI platforms to make drivers’ life easier, below are the few subsequent applications which are already present or will be introduced very soon,

• Finding gas stations and allowing the driver to pay for their fuel purchase from inside the vehicle.
• Recognizing nearby restaurants that are related to those revisited by the driver.
• Providing notes to buy required household items as the driver approaches relevant stores.

There are many intelligent devices which get connected to the internet every day to monitor health to smartphones. The technology, electrical components and software will help automobile manufacturers to collaborate with software development teams and other firms in the same sector. This will promote the successful blend of cars that depend on IoT devices.

Internet of Things has made a lasting impression on the automobile industry and will be getting bigger in the coming years. In the future, the combination of artificial intelligence and IoT devices in the future will allow manufacturers to update vehicles with additional features such as

:

• predictive maintenance
• repair scheduling
• identification of performance issues
• using smart sensors to identify medical emergencies
• automatic toll collection

Machine learning, which is a branch of artificial intelligence, completely tries to replicate the way in which humans learn and also when applied on to devices and machines, will think and act almost like human beings which are done by repetition of tasks using the past data.

We can bring  together Big data, Machine Learning and Artificial Intelligence to generate highly sensitive autonomous systems that support in the movement for those to help an ageing population mobile and ensure they can still use their cars.

Deep Learning is the process to achieve Machine Learning. It is because of Deep Learning there no possibility of any issues coming up during AI activities. DL helps split down tasks to make it easier to manage. The software in DL learns and then it starts copying the actions in the neuron layers of our brain.

DL techniques have been very useful in the automobile industry as it helps in advanced driving assistance systems and autonomous driving. Even in services where technology was not that until now, it was DL that induced in a tremendous advancement. We work to enhance the quality and characteristics of autonomous vehicles. 

Infotainment has become industry-standard a bag full of “information” and “entertainment” is the umbrella term describing the main technological interface of a car.

Artificial Intelligence develops in-vehicle infotainment systems in a better way. Because of this trend, the need for better quality hardware and software solutions has also risen because they all have to be compatible with AI.

In the infotainment, you can expect a spike in characteristics like eye tracking, speech recognition, gesture recognition, monitoring driving, and database of natural languages.

There will be not only the small cars with AI capabilities will hit the road but there will be the huge trucks with the same capabilities cruise along the streets in the future. With abilities such as pattern identification, natural language interpretation and the ability to build knowledge, cognitive analytics gives us a way to mine and make sense of this information.

Cognitive systems are assumed to work similar to a human which would interpret a real-life situation, and in order to do that, a deeper knowledge of unstructured data is required. Car manufacturers have now started incorporating this into their vehicles.

Unlike conventional vehicles, connected vehicles can do more than alert us with check-engine lights, oil lights, and low-battery indicators. AI monitors hundreds of sensors and is able to detect problems before they affect vehicle operation.

By monitoring thousands of data points per second, AI can spot minute changes that may indicate a pending component failure — often long before the failure could leave you stranded.

The insurance industry and AI have one thing in common, and it’s a biggie. Both spend a great deal of time predicting the future. It is no surprise, then, that insurance has embraced the use of AI in cars to help make risk assessments in real time.

AI does something else that even insurance customers like. It speeds up the process of filing claims when accidents do occur.

AI levels the playing field for drivers by creating risk profiles based on drivers’ individual risk factors found in big data. Rather than relying on driving history to set premiums, AI looks a myriad of less-obvious factors that can predict how safe a driver is likely to be.

From health issues to a recent divorce, AI can find details about a driver that may affect his or her ability to drive safely. Since such issues may be recent, they might not have affected the driver in the past, but potentially could in the future.

AI enables cars to do more than watch the road, it can help them keep an eye on the driver, as well.

AI software detects whether or not the driver is in the vehicle.

Using advanced AI facial recognition algorithms,  which can detect which driver is operating the vehicle. Since the husband, wife, and young adult child each have their own preferences, the system can automatically adjust the seat, mirrors, and temperature to suit the individual.