The automotive industry continues to be a hotbed of innovation, with activity driven by the need to reduce maintenance cost and improve customer experience and safety, and growing importance of technologies such as infrared thermography and acoustic monitoring. 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 Internet of Things in Automotive: Predictive maintenance systems. Buy the report here.
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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.
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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, acoustic vehicle signalling devices, autonomous parking, and brake pedal sensors are disruptive technologies that are in the early stages of application and should be tracked closely. Vehicle head up displays (HUDs), smart light dimmers, and automatic actuated vehicle doors are some of the accelerating innovation areas, where adoption has been steadily increasing. Among maturing innovation areas are road slope estimation and V2V distance monitoring, which are now well established in the industry.
Innovation S-curve for IoT in the automotive industry
Predictive maintenance systems is a key innovation area in IoT
Predictive maintenance is the data-driven approach to forecasting the failure of operational equipment and implementing preventative maintenance to prevent unplanned downtime. It uses data gathered from past service records, in-vehicle sensors, and machine learning techniques to analyse equipment conditions that could lead to a potential system/equipment failure. An IoT system then informs the customer and the automobile manufacturer that a component or system requires maintenance or replacement.
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 50+ companies, spanning technology vendors, established automotive companies, and up-and-coming start-ups engaged in the development and application of predictive maintenance systems.
Key players in predictive maintenance systems – 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 predictive maintenance systems
| Company | Total patents (2010 - 2022) | Premium intelligence on the world's largest companies |
| Strong Force Iot Portfolio 2016 | 329 | Unlock Company Profile |
| Fanuc | 75 | Unlock Company Profile |
| Mitsubishi Electric | 74 | Unlock Company Profile |
| Hitachi | 62 | Unlock Company Profile |
| Siemens | 53 | Unlock Company Profile |
| NEC | 32 | Unlock Company Profile |
| Applied Materials | 27 | Unlock Company Profile |
| Samsung Group | 26 | Unlock Company Profile |
| Boeing | 25 | Unlock Company Profile |
| Honeywell International | 23 | Unlock Company Profile |
| Veolia Environnement | 21 | Unlock Company Profile |
| Toshiba | 20 | Unlock Company Profile |
| General Electric | 18 | Unlock Company Profile |
| Palantir Technologies | 18 | Unlock Company Profile |
| Tokyo Electron | 16 | Unlock Company Profile |
| Safran | 16 | Unlock Company Profile |
| Panasonic | 15 | Unlock Company Profile |
| Omron | 15 | Unlock Company Profile |
| Doosan | 15 | Unlock Company Profile |
| Hewlett Packard Enterprise | 15 | Unlock Company Profile |
| International Business Machines | 14 | Unlock Company Profile |
| Rockwell Automation | 11 | Unlock Company Profile |
| AB SKF | 11 | Unlock Company Profile |
| Falkonry | 11 | Unlock Company Profile |
| Tata Sons Pvt | 11 | Unlock Company Profile |
| Scottish Mortgage Investment Trust | 11 | Unlock Company Profile |
| Johnson Controls International | 10 | Unlock Company Profile |
| Shinwa Controls | 10 | Unlock Company Profile |
| Intel | 10 | Unlock Company Profile |
| ASML Holding | 10 | Unlock Company Profile |
| Preferred Networks | 9 | Unlock Company Profile |
| General Motors | 9 | Unlock Company Profile |
| Capital One Financial | 8 | Unlock Company Profile |
| Emerson Electric | 8 | Unlock Company Profile |
| Yokogawa Electric | 7 | Unlock Company Profile |
| Munchener Ruckversicherungs-Gesellschaft Aktiengesellschaft (Munich Re) | 7 | Unlock Company Profile |
| Nippon Telegraph and Telephone | 7 | Unlock Company Profile |
| JTEKT | 7 | Unlock Company Profile |
| Lockheed Martin | 7 | Unlock Company Profile |
| Nissan Motor | 6 | Unlock Company Profile |
| Buhler | 6 | Unlock Company Profile |
| Furukawa | 6 | Unlock Company Profile |
| Raytheon Technologies | 6 | Unlock Company Profile |
| Toshiba Mitsubishi-Electric Industrial Systems | 6 | Unlock Company Profile |
| Sumitomo Heavy Industries | 6 | Unlock Company Profile |
| Xerox Holdings | 6 | Unlock Company Profile |
| Toyota Motor | 6 | Unlock Company Profile |
| Accenture | 6 | Unlock Company Profile |
| Oracle | 6 | Unlock Company Profile |
| Grid4C | 6 | Unlock Company Profile |
Source: GlobalData Patent Analytics
Strong Force Innovation Portfolio is a key player in the predictive maintenance systems innovation area. The company’s predictive maintenance technology predicts network faults before they occur thereby improving network uptime and operational efficiency and increasing revenues. Mitsubishi Electric, Hitachi, Siemens and Fanuc are some of the other key players.
To further understand how IoT is disrupting the automotive industry, access GlobalData’s latest thematic research report on Internet of Things (IoT) 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.
