For the development of automobiles in the future, high-level autonomy technology is essential. Our cars can now see, hear, and even anticipate the future, thanks to the development of IoT. Vehicles are becoming massive moving internet-connected machines that do more than just transport us; they also provide entertainment, let us buy, make calls, pay bills, and even save lives in emergencies.
The usage of sensors in autonomous vehicles is made possible by big data. An autonomous vehicle won’t be useful on the road if it doesn’t have access to a consistent and dependable flow of huge data about self-driving cars; it won’t know what to do with the data it collects. Without data, a connected car is analogous to a child who doesn’t know better and puts their fingers in electrical sockets, grabs a knife, or tries to catch a spark.
Big Data serving Big!
Nearly every business has seen a change, thanks to big data. From more overtones, like media and advertising, where it’s used to forecast trends and analyze audiences, to more covert ones, like healthcare or energy management, where a lot of data is utilized to explore the largest difficulties we currently face. When it comes to big data, its analytics, and IoT, the automotive industry is not an exception. They are employed in numerous stages of the production and promotion of automobiles. However, investing in the creation, testing, or use of autonomous vehicles is undoubtedly the most innovative thing automobile firms can do with their massive data.
One of MarketsandMarkets’ first comprehensive analyses on automotive AI businesses predicted that by 2025, the market value of this sector would be USD 10 billion. Even larger figures have been shown by more recent statistics. For instance, analysts at Global Markets Insights (2019) forecast that by 2026, there will be a rise from USD 1 billion in 2019 to USD 12 billion. It appears to be a safe investment because the majority of significant IT corporations and significant manufacturers are confident in the unavoidable success of such cars.
What change does big data make?
To position the car on the road and keep it in the right lane, we use sight to notice the traffic signal switches and spatial awareness. To judge how close other vehicles are, we use sound, and to remember a traffic sign, we use memory. In addition to being able to process, train, and learn from errors, engineers want AI to comprehend each of these processes when creating an autonomous car.
As huge data is necessary for autonomous vehicles to function, so are sensors that collect this data. Driving involves the utilization of a variety of senses and sophisticated cognitive processes, sometimes without our awareness. An autonomous car uses different types of sensors to see and feel the world around it like a camera, radar, and lidar etc.
In a matter of milliseconds, an autonomous vehicle processes and analyses data from a variety of internal sensors. This enables the car to safely go from point A to point B while also transmitting information about the road’s state to the cloud and, consequently, to other vehicles. Then, other vehicles are given access to massive data from self-driving automobiles.
Big data Into Action!
Do you think smart cars simply use the data they collect for themselves? Think again. This data’s actual potential is substantially higher:
- An automaker may detect a problem with your automobile from a distance and notify you right away through your car.
- The management of a fleet of hundreds or thousands of linked vehicles can be made more effective and efficient with the use of vehicle data.
- From the gas stations that drivers select to the music they listen to, big data is a rich source of behavioral insights. Customer service, sales, and marketing all benefit from having this knowledge.
- Big data from linked automobiles will improve the accuracy of city planning and engineering; examples include more effective road planning, early warning systems on risky places, and safer pedestrian crossings.
- Big data from linked automobiles can be used to create insurance plans for drivers that are specific to their behavior
Conclusion
Without big data, the automotive sector cannot advance further. The usage of data by cars will be analogous to the use of gas or energy in the connected and autonomous vehicle future. Companies need to have experience in the automotive sector as well as knowledge of AI, machine learning, natural language processing, IoT, and platform development in order to offer big data solutions for the sector.