The automotive industry continues to be a hotbed of innovation, with activity driven by the demand for better customer experience, rising interest driver safety in vehicles, autonomous driving, safety features, testing and simulation, and growing importance of technologies such as advanced signal/image processing algorithms and predictive AI-based analytics. In the last three years alone, there have been over 1.2 million patents filed and granted in the automotive industry, according to GlobalData’s report on Artificial intelligence in Automotive: Driver drowsiness detection. Buy the report here.
However, not all innovations are equal and nor do they follow a constant upward trend. Instead, their evolution takes the form of an S-shaped curve that reflects their typical lifecycle from early emergence to accelerating adoption, before finally stabilising and reaching maturity.
Identifying where a particular innovation is on this journey, especially those that are in the emerging and accelerating stages, is essential for understanding their current level of adoption and the likely future trajectory and impact they will have.
290+ innovations will shape the automotive industry
According to GlobalData’s Technology Foresights, which plots the S-curve for the automotive industry using innovation intensity models built on over 619,000 patents, there are 290+ innovation areas that will shape the future of the industry.
Within the emerging innovation stage, manufacturability analysis, autonomous parking, and lidar for vehicle anti-collision are disruptive technologies that are in the early stages of application and should be tracked closely. Speed profile estimation, smart light dimmers, and driver drowsiness detection are some of the accelerating innovation areas, where adoption has been steadily increasing. Among maturing innovation areas are road slope estimation and adaptive cruise control, which are now well established in the industry.
Innovation S-curve for artificial intelligence in the automotive industry
Driver drowsiness detection is a key innovation area in artificial intelligence
Driver drowsiness detection systems use cameras, eye tracking sensors and other hardware to track visual cues, where drowsiness can be identified through eye-blinking frequency, facial expressions, yawning frequency, eye-gaze movement and head movement.
GlobalData’s analysis also uncovers the companies at the forefront of each innovation area and assesses the potential reach and impact of their patenting activity across different applications and geographies. According to GlobalData, there are 20+ companies, spanning technology vendors, established automotive companies, and up-and-coming start-ups engaged in the development and application of driver drowsiness detection.
Key players in driver drowsiness detection – a disruptive innovation in the automotive industry
‘Application diversity’ measures the number of different applications identified for each relevant patent and broadly splits companies into either ‘niche’ or ‘diversified’ innovators.
‘Geographic reach’ refers to the number of different countries each relevant patent is registered in and reflects the breadth of geographic application intended, ranging from ‘global’ to ‘local’.
Patent volumes related to driver drowsiness detection
Source: GlobalData Patent Analytics
Toyota is a key player in the driver drowsiness detection innovation area. The company’s Toyota Safety Sense alerts drivers about the dangers of DWS – Driving While Sleepy. It is designed to support a driver’s awareness and increase safety while driving. Panasonic, Hyundai, LG and Honda are the other key players in the innovation area.
To further understand how artificial intelligence is disrupting the automotive industry, access GlobalData’s latest thematic research report on Artificial Intelligence (AI) in Automotive.
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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.
GlobalData’s Patent Analytics tracks patent filings and grants from official offices around the world. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
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