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Predictive intelligence, in-vehicle applications will predict upcoming coverage gaps or connectivity issues, and be able to take proactive action to alleviate them.

FREMONT, CA: Few tech patterns have caught the creative mind like connected vehicles. From self-driving vehicles to automotive car application environments to Smart City traffic applications, the next few decades promise to reshape the driving experience and, potentially, transportation itself. 

Predicting Vehicle Connectivity 

In the real-world driving era, to fulfill the promise of connected car experiences, application providers need the ability to monitor radio system performance and track application quality of experience in real-time. Mainly, they need the ability to understand how a connected vehicle’s throughput and latency will fluctuate over the course of a trip. They should predict upcoming coverage and data performance gaps so they can avoid or optimize around them.

Managing and predicting connectivity is not a simple problem. It involves monitoring multiple real-time services, including the performance of the in-vehicle radio system, the app’s quality of experience, and the performance of the cellular connection. In the coming days, most of the connected vehicles will use embedded software clients in their telematics control units (TCUs) to converse back to cloud services, providing continuous details about throughput, latency, and accessibility.


To avoid consuming wireless bandwidth, the clients will evaluate network signaling and radio parameters. Then the data gathered will be uploaded to a cloud database, and it will be used to create detailed geo-data maps of cellular performance.

Mobile network operators (MNOs), just as their Automotive OEM and associated vehicle application supplier clients, will utilize these maps to make granular expectations about the accessibility and execution of every vehicle's connection, because of a GPS goal or directly the heading the vehicle is moving. With this prescient knowledge, in-vehicle applications will think about upcoming coverage gaps or availability issues before they occur, and have the option to make a proactive move to alleviate them.

An Emerging Ecosystem

Those are only a couple of instances of the conceivable outcomes for these sorts of predictive insights. At this beginning time in the game, we don't yet have the idea of how these open doors will convert into concrete services and business models. Be that as it may, it's anything but difficult to perceive how everybody associated with emerging connected car ecosystems can take benefit of them. Automotive original equipment manufacturers (OEMs) and application suppliers are incredibly keen on prescient connectivity. For OEMs, the thin customer checking on TCU's and resulting connectivity assurance solutions enable them to keep up the steady quality for connected vehicle services and safety features.

The monitoring data will reduce warranty issues by identifying vehicle problems. As they work to certify new connected apps and services, the predictive coverage dataset becomes an essential input to simulation testing models, so they can examine and optimize for issues associated with fluctuating performance. These same abilities will also be useful to third-party connected cars and Smart City app providers.

Looking Ahead

According to the reports, connected and automated vehicles will rule the transportation industry. It will drive experiences and productivity to open up new business models. Although the ecosystem of connected cars is just emerging and it will benefit the market in the coming days. MNOs and automotive OEMs should ensure that they are working with vendors who can provide an independent, unbiased reference for evaluating network and service quality.

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