The automotive industry continues to be a hotbed of patent innovation. The automotive industry is leveraging artificial intelligence (AI) for fault monitoring due to the increasing complexity of vehicles, increasing demand for safety, cost of downtime, increasing data availability, and the decreasing cost of computing, which can help identify faults early and reduce costs. The automotive industry is utilizing advanced AI technologies for fault monitoring, including deep learning, edge computing, digital twins, and federated learning, to identify data patterns and diagnose faults. In the last three years alone, there have been over 1.7 million patents filed and granted in the automotive industry, according to GlobalData’s report on Artificial intelligence in automotive: fault monitoring AI. 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 stabilizing 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.
300+ 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 one million patents, there are 300+ innovation areas that will shape the future of the industry.
Within the emerging innovation stage, autonomous on-demand logistics, end-to-end learning models, and adaptive driver alerting are disruptive technologies that are in the early stages of application and should be tracked closely. Vehicular vision, adaptive cruise control, and predictive acceleration control are some of the accelerating innovation areas, where adoption has been steadily increasing.
Innovation S-curve for artificial intelligence in the automotive industry
Fault monitoring AI is a key innovation area in artificial intelligence
Fault monitoring AI refers to the use of artificial intelligence technologies to monitor and detect faults or anomalies in various systems, such as communication networks, computing devices, and datasets. It involves the analysis of data and the use of machine learning techniques to identify deviations from normal behavior, enabling proactive measures to be taken to prevent system failures or improve system performance.
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 30+ companies, spanning technology vendors, established automotive companies, and up-and-coming start-ups engaged in the development and application of fault monitoring AI.
Key players in fault monitoring AI – a disruptive innovation in the automotive industry
‘Application diversity’ measures the number of applications identified for each patent. It broadly splits companies into either ‘niche’ or ‘diversified’ innovators.
‘Geographic reach’ refers to the number of countries each patent is registered in. It reflects the breadth of geographic application intended, ranging from ‘global’ to ‘local’.
Patent volumes related to fault monitoring AI
Source: GlobalData Patent Analytics
IBM, the leading patent filer in fault monitoring AI, has filed a patent for an AI system that uses sensor data to monitor automotive components' health. The technology could revolutionize vehicle safety and reliability, reducing downtime and extending vehicle life. Microsoft and Dell Technologies are some of the other leading patent filers in fault monitoring using AI.
In terms of application diversity, Juniper Networks leads the pack. People.ai and VMware stood in the second and third positions respectively. By means of geographic reach, People.ai held the top position followed by Aurora Labs and monday.com.
To further understand the key themes and technologies disrupting the automotive industry, access GlobalData’s latest thematic research report on Artificial Intelligence (AI) in Automotive.