Simple Sensors Become Gateways for Vehicle Telematics
New innovations in technology have paved a way for vehicles to be smarter and more intelligent in their data management systems. Traditionally engineered to be more mechanical by design, many modern vehicles today have transformed into digital computers on wheels with the introduction of embedded electronics and microprocessors. These embedded computing processors provide a central nervous system for the processing and monitoring of specific sensor inputs throughout a modern vehicle. For example, automotive OEMs include hundreds of these embedded microprocessors in order to manage a wide-network of sensor inputs/outputs for specific functions and the safety of the vehicle. The introduction of these embedded microprocessors in vehicles have ultimately transformed the entire history of vehicles in an incredible and intelligent way. This has been proven with all the technological features behind modern day vehicles.
Modern day vehicles leverage these electronic controllers and can tap into valuable data insights that provide major benefits in terms of automation for vehicles. Many of those features that come almost second nature to consumers like power steering, traction control, air condition, transmission, and air bags are all controlled by an embedded microcontrollers and sensors. Especially as advancements in machine learning and new AI technologies help shape the future for autonomous driving vehicles, new edge computing platforms will be pivotal in the next wave of real-time processing, data analytics, and especially vehicle telematics. For example Tesla’s current line of production vehicles provide semi-autonomous driving by leveraging a network of sensors for its advanced driver-assistance systems (ADAS). At its core, most connected and intelligent ADAS features are made possible from edge computing solutions that provide robust, real-time processing capabilities directly from senor data. Ruggedized edge computers will bring even more processing power and real-time intelligence for many automotive applications, eventually paving a new era of autonomous commercial vehicles. . Vehicle fleet telematics and the data that is generated is accelerating benefits of data collection, especially in edge computing applications for the automotive markets. Many of these applications are collecting a significant amount of data that will assist with building machine learning algorithms for an autonomous future.
Embedded Microcontrollers in Vehicles are sensors for IoT
Embedded ECUs are basically computers that manage the basic input and output of data streams from sensors in the vehicle. Modern day vehicles rely on this complex network of computers to interpret specific functions of the vehicle. Although many automotive functions seem unnoticeable and automatic to the end-user, this is made possible from an embedded microprocessor. These microprocessors or ECUs were first mass produced in 1970 and implemented as a solution to meet regulations on fuel and emission standards. Eventually by the 1980s, automotive OEMs incorporated additional ECUs to control dedicated functions of a car engine like the fuel injection system, an important element to the fuel efficiency ratio for a car. Fast forward to 2020 and vehicles today have hundreds of embedded ECUs processing and monitoring data for the most critical vehicle functions. For example, some popular functions managed by ECUs are anti-braking, traction control, active suspension control, cruise control, power windows and assisted parking to name a few. In addition to the advent of ECUs, another pivotal advancement for modern vehicle technology is its ability to communicate through a protocol between all of its embedded processing controllers, also known as the “CANBus.”
(example of an vehicle ECU)
Image source: auto.howstuffworks.com
CANBus Protocol: The Communication Gateway for Vehicles
With hundreds of sensors now populated in modern day vehicles, one may ask how the data is transmitted from each ECU. This is made possible through the Controller Area Network Bus or CANbus protocol. The CANBus protocol is a message-based protocol that is used in vehicles to connect and transfer information about specific statuses of the vehicle. For example, modern vehicles use embedded ECUs and sensors for predictive maintenance diagnostics in real-time. Learn more about the specifics of the CANBus protocol and the technology drivers behind it in a blog post here. An example of an ECU and CANBus at work is when the “maintenance required” light is displayed in the dashboard for many vehicles. Ultimately, the introduction of ECUs and CANBus protocol were pivotal advancements for modern vehicle in terms of the communication and transmission of data. But as vehicles continue to become more reliant on digital data in our technology-driven world, a new demand for better insights and analytics is shaping opportunities for better telematics solutions.
What are Vehicle Telematics?
In general, the term “telematics” is a convergence of both telecommunication and information processing at its core. Add the word “vehicle” in front and it becomes a hot topic among many IoT and edge computing discussions for the major benefits telematics technologies can provide. These technologies can be any device that collects and communicates data on the status of the vehicle. Vehicle telematics data that is collected is extremely valuable as it provides the foundation for many benefits. Some vehicle telematics that are beneficial can be anything from GPS location tracking, optimizing fuel consumption, and even monitoring component health for vehicles. Successful vehicle telematics solutions are often hardware devices and software working together to analyze data for a certain application. An example would be commercial fleet vehicles that use telematics data to gain an overview of its entire fleet of vehicles to improve efficiency and profitability. Commercial fleet vehicles is an area where it shows most promise and benefits from analyzing its vehicle telematics data.
Commercial Vehicle Market Snapshot in 2020
According to Technavio, a leading market research firm forecasts that from 2019-2023 the global commercial vehicle telematics market will grow to $17.2 Billion, with a CAGR of 21% through its compounded forecast years (infographic below). Commercial vehicles are classified differently and are registered to a company that uses them for business operations like transporting goods and logistics; some examples of fleet vehicles are trucks, buses, heavy equipment (mining and construction), and taxis. In terms of market segmentation, the forecast also indicates that embedded telematics technologies will be the largest market share and growth driver for the period. Embedded telematics technologies can range from IoT sensors, GPS tracking devices, and intelligent telematics computers with powerful processing capabilities. The forecast report also shares how automotive OEM suppliers are recognizing the need for telematics offerings and investing into telematics solutions for better business opportunities for the market.
Image source: technavio.com
One example where telematics technologies are proving to be useful is in commercial vehicle fleet managers and the data it collects from its inventory of vehicles. New telematics technology and a demand for fleet managers to be more efficient in its operations have pushed huge improvements in how commercial fleets are tracked for better maintenance and costs over time. Ultimately, new telematics technology integrated across commercial vehicles will help make better informed decisions, increase efficiency across operations/logistics planning, and provide long-term growth in fleet management solutions.
How Does the Technology Behind Vehicle Telematics Work?
The technology behind vehicle telematics continues to grow in terms of better insights and business opportunities for many commercial vehicles. Significant data is generated from sensors and communicated through wireless technologies for a real-time insights or actions. This is made possible from wireless (Wi-Fi, 4G/LTE, 5G) networks, optimized edge computing solutions, and intelligent IoT sensors all working together harmoniously. One area of the vehicle telematics market that continues to progress in its digital transformation is in commercial fleet vehicles. Many of these fleet vehicles leverage existing technologies already embedded in the vehicle (ECUs and CANbus) but also use new IoT sensors dedicated for real-time processing. New edge computing solutions and telematics computers help analyze data generated from IoT sensors for incredible insights. The future of vehicle telematics technology continues to grow with faster wireless networks and new edge computing platforms.
The benefit behind edge computing is quite simple, by shifting the need for compute power closer in proximity to where data is generated, it provides faster processing and real-time decision making capabilities. Rugged edge computers and industrial embedded computers for fleet vehicles are great examples of high-performance telematics solutions for data processing, storage, and telemetry accuracy. Many of these purpose-built computing solutions are designed for reliability in remote or harsh environments. Some of the best vehicle telematics computers leverage passive cooling designs, can operate in extreme temperatures, have a resistance to shock and vibration, and can support wide-voltage power protection for vehicle batteries. Learn more about the Top 5 embedded computing designs for Iot and edge deployments in a past blog post here. As a result, many commercial vehicle fleets like trucks, buses, first responders, and mining equipment can leverage rugged edge computers as telematics solutions for robust information processing and analytics.
5 Data Flow Steps for Vehicle Telematics Data
- ECUs and other IoT sensors in the vehicle pass information through the CANBus channel to a telematics device or edge computer
- A key element to the telematics computer is its wireless connectivity to cellular or satellites networks (GPS, GRPS, 4G/LTE, and 5G) and can pass data bi-directionally
- Data and location telemetry can be used for local processing (Edge computing) or immediately transmitted from the vehicle directly to a server
- Telecommunication providers (AT&T, Version, T-Mobile) control the flow of information and interpret the data
- The final step is a real-time dashboard of vehicle telematics data for commercial fleet managers from a control hub or mobile app