BRANDED CONTENT: The Role of Deep Data and Intelligent Edge Filtering in the Future of Connected Vehicles

Traditional methods of automotive data analysis involve transferring all in-vehicle data to the cloud for processing. This is accomplished with either an over-the-air (OTA) software solution, which is often limited to infotainment and navigation data, or at the dealership with a direct data download.

When working with a limited number of data points or parameters, let’s say ten for this example, this method isn’t terrible. But what happens when that number increases tenfold? One hundredfold? The truth is it will soon be much more.

By 2025 it is estimated that connected vehicles will be producing data at a volume of 10 exabytes (10 million terabytes) per month. That is over 1,000 times its present volume. This is great for OEMs, who can utilize this data to create downstream revenue, improve component efficiency and functionality, and reduce recall and warranty costs. However, one major problem stands in the way: the ability to access and process this data to scale.

Fortunately, the Deep Connected Platform (DCP), an embedded IoT-based firmware and cloud solution from Sibros, is unlocking the door to not only deep data but real data. This type of vertically-integrated software and data management solution enables OEMs with multiple communication methods (CAN, LIN, Ethernet, Flex) to tap into in-vehicle systems and provides millisecond-level data collection and intelligent edge filtering from predevelopment to product rollout and beyond. Let’s dive deeper into the backbone of connected vehicle software and data access.

Interpreting deep data with intelligent edge filtering
Most of today’s automotive data insights are harvested from a laboratory simulation. In other words, component improvements and decisions are made on a “best guess” basis, rather than on accurate, real-world data. Unfortunately, there is no way of knowing how close these virtual tests come to reality or whether the decisions made will prove effective for vehicle functionality and performance.

Sibros DCP opens the door to real-world data, not just from one or two vehicles, but from the entire fleet. Its superior data compression methods and intelligent edge filtering expedite the vehicle-to-cloud data transfer process. In other words, DCP brings sorting, processing, and data compression closer to the data source and enables data segregation for smoother analysis. Customizable parameters enable OEMs to isolate information related to a specific system, such as the Advanced Driver Assistance Systems (ADAS) or EV battery management systems (BMS). Rather than digging through a slush pile of irrelevant details and data points, manufacturers can utilize selective data logging and customizable frequencies to examine exactly what they want, when they want it to quickly achieve actionable results.

Vehicle Prognostics
When the oil light comes on, it indicates a need for preventative maintenance: change the oil now to increase the longevity of your vehicle later. The problem is, oil change frequency, whether determined by the car or a mechanic, has always been determined with two data points: time and distance.

The trouble with this type of reasoning is that additional factors contribute to engine oil needs. Driver habits, terrain, external temperatures, and even undetected system faults all contribute to engine oil cycling. Sibros Deep Logger is responsible for collecting data from every electronic control unit (ECU) in the vehicle. With this information, manufacturers can account for system dependencies and driver habits not only to provide more accurate preventative maintenance recommendations for oil changes but other systems as well. Preventative maintenance is only the tip of the iceberg. Another, and perhaps more important benefit of deep data and intelligent edge filtering is the ability to identify and remedy software and hardware faults that jeopardize vehicle and owner safety.

Enhancing data with OTA updates
According to the Society of Indian Automobile Manufacturers (SIAM) there were over 7 lakh vehicle recalls in 2021, a number that will only continue to rise alongside vehicle complexity. Unfortunately, many recalls go unnoticed for months or even years. Then there is the issue of completion rates, which fall between 56-76% and over time result in millions of unsafe vehicles on the road. These problems are easily remedied with deep data access, analysis, and over-the-air updates.

Let’s say the brake assist in the vehicle’s ADAS is experiencing a .05 second delay after detecting a potential collision. Without access to real-time data, it might take several traffic accidents or near misses before this issue comes to light. An easier solution is to identify and address the issue before it escalates. With Sibros DCP, OEMs can set up alerts that notify them when a particular ECU is functioning outside of acceptable parameters. This is especially crucial with safety-critical components where faults can quickly escalate into life-threatening problems.

The next step is to determine the scope. Is the fault limited to a specific make, model, or drivetrain? Is it an isolated incident? Or maybe it is a fleet-wide design defect. Gone are the days when OEMs needed to recall every suspected unit to figure this out. They can accomplish it remotely with millisecond-level data mined by Sibros Deep Logger directly from vehicle ECUs.

Sibros further streamlines the recall rollout process by enabling vehicle-wide over-the-air (OTA) software updates with its Deep Updater. Instead of waiting for customers to respond to a recall summons, OEMs can increase completion rates with a targeted update package, sent via 5G or Wi-Fi directly to the affected vehicles. Once the package arrives, it waits for the owner's consent before initiating the installation. Safety-critical updates can be sent with a time constraint: if owner consent is not received within a specified period, the update will initialize the next time the vehicle is in a safe state. Not only does this keep unsafe vehicles off the road but it enhances the driver’s experience, by taking a dealer visit out of the equation.

Customer facing features

Deep data and intelligent edge filtering also play a key role in the creation of innovative and desirable customer-facing features. It allows OEMs to look at what systems and features drivers use and how they use them.

The next step is to take those insights and transform them into revenue streams, such as offering the ability to remotely upgrade in-vehicle features. Some examples of this are engine calibrations on demand for different terrain types, automotive wiper adjustments to heavy rainfall, automatic window defrost and heat settings for ice and fog removal, and personalized cockpit settings to increase driver comfort. Aside from direct upgrades, other customer-facing features include access to personalized third-party applications and more accurate Usage Based Insurance rates.

Stay on the edge with Sibros
Deep data and intelligent edge filtering are key players in the evolution of the connected vehicle and are easily obtainable with a hardware-agnostic platform, like Sibros DCP. The Deep Connected Platform is usable both as an out-of-the-box solution or as an add-on to enhance a manufacturer’s existing automotive software. Sibros is compliant with global safety, cybersecurity, and data management standards to enable smooth integration and solution rollout.

DCP offers compatibility with every vehicle architecture, from ICEs to EVs and two-wheelers to passenger cars to provide OEMs with scalable fleet-wide updates and data management. Sibros enables a safer driving experience via safe, secure, and robust OTA software updates for the entire vehicle lifecycle and helps OEMs reduce cloud transfer and storage costs with superior data compression at the edge. Don’t get stuck in the past with limited data access and sorting capabilities. Drive into the future with Sibros Deep Connected Platform, a safe, efficient, and reliable way for managing data and powering your connected vehicle ecosystem.