The technology industry continues to be a hotbed of innovation, with activity driven by the increasing demand for smart and autonomous devices across various industries, the need for real-time data analysis and decision-making at the edge, and the rising availability of powerful yet energy-efficient hardware, as well as growing importance of technologies such as edge computing, deep learning models optimised for resource-constrained environments, and sensor fusion techniques that combine data from multiple sensors to enhance perception and context awareness. Additionally, technologies like natural language processing and speech recognition enable seamless human-machine interactions in embedded systems. In the last three years alone, there have been over 3.6 million patents filed and granted in the technology industry, according to GlobalData’s report on Innovation in Artificial Intelligence: Intelligent embedded systems. 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.

300+ innovations will shape the technology industry

According to GlobalData’s Technology Foresights, which plots the S-curve for the technology industry using innovation intensity models built on over 2.5 million patents, there are 300+ innovation areas that will shape the future of the industry.

Within the emerging innovation stage, finite element simulation, ML-enabled blockchain networks and generative adversarial network (GAN) are disruptive technologies that are in the early stages of application and should be tracked closely. Demand forecasting applications, intelligent embedded systems, and deep reinforcement learning are some of the accelerating innovation areas, where adoption has been steadily increasing. Among maturing innovation areas are wearable physiological monitors and smart lighting, which are now well established in the industry.

Innovation S-curve for artificial intelligence in the technology industry

Intelligent embedded systems is a key innovation area in artificial intelligence

Intelligent embedded systems are computer systems seamlessly integrated into physical devices or products, possessing the capability to autonomously make decisions and carry out commands based on programming and external input. These systems find application in a diverse range of fields, including industrial automation, robotics, medical devices, and consumer electronics.

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 200+ companies, spanning technology vendors, established technology companies, and up-and-coming start-ups engaged in the development and application of intelligent embedded systems.

Key players in intelligent embedded systems – a disruptive innovation in the technology 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 intelligent embedded systems

Company Total patents (2010 - 2022) Premium intelligence on the world's largest companies
Tencent 278 Unlock Company Profile
Samsung Group 214 Unlock Company Profile
Stradvision 213 Unlock Company Profile
International Business Machines (IBM) 175 Unlock Company Profile
NEC 172 Unlock Company Profile
Alphabet 148 Unlock Company Profile
Baidu 135 Unlock Company Profile
Furukawa 128 Unlock Company Profile
Ping An Insurance 103 Unlock Company Profile
ADOBE 101 Unlock Company Profile
SoftBank Group 99 Unlock Company Profile
Fujifilm 98 Unlock Company Profile
Intel 97 Unlock Company Profile
Huawei Investment & Holding 93 Unlock Company Profile
Sony Group 91 Unlock Company Profile
Canon 84 Unlock Company Profile
Beijing SenseTime Technology Development 83 Unlock Company Profile
Microsoft 83 Unlock Company Profile
Hitachi 77 Unlock Company Profile
Toshiba 77 Unlock Company Profile
Capital One Financial 77 Unlock Company Profile
Beijing Electronics 76 Unlock Company Profile
Koninklijke Philips 73 Unlock Company Profile
Nippon Telegraph and Telephone 64 Unlock Company Profile
Meta Platforms 60 Unlock Company Profile
Qualcomm 60 Unlock Company Profile
Robert Bosch Stiftung 57 Unlock Company Profile
Snap-on 56 Unlock Company Profile
Nokia 53 Unlock Company Profile
State Grid 48 Unlock Company Profile
Shenzhen Sensetime Technology 48 Unlock Company Profile
Raytheon Technologies 47 Unlock Company Profile
Panasonic 46 Unlock Company Profile 46 Unlock Company Profile
Illumina 45 Unlock Company Profile
AbbVie 45 Unlock Company Profile
Siemens 43 Unlock Company Profile
Accenture 41 Unlock Company Profile
F. Hoffmann-La Roche 39 Unlock Company Profile
Xerox 37 Unlock Company Profile
General Electric 36 Unlock Company Profile
Toyota Motor 33 Unlock Company Profile
Tata Sons 33 Unlock Company Profile
Geenee 33 Unlock Company Profile
Mitsubishi Electric 32 Unlock Company Profile
General Motors 31 Unlock Company Profile
Procter & Gamble 28 Unlock Company Profile 26 Unlock Company Profile
China Electronics Technology Group 26 Unlock Company Profile
GuangDong OPPO Mobile Telecommunications 26 Unlock Company Profile

Source: GlobalData Patent Analytics

Tencent is a leading patent filer in intelligent embedded systems. The company’s patents are aimed at invention describing face model matrix training method, apparatus, and storage medium. The method includes obtaining a face image library comprising multiple groups of face images, with each group including at least one face image of at least one person, and separately parsing each group of face images and calculating a first matrix and a second matrix according to parsing results.

The first matrix is an intra-group covariance matrix of facial features of each group of face images, and the second matrix is an inter-group covariance matrix of facial features of the groups of face images.

The method also includes training face model matrices according to the first matrix and the second matrix.

Other prominent patent filers in the space include Samsung Group and Stradvision.

By geographic reach, Snap-on leads the pack, followed by Sartorius and WheelRight. In terms of application diversity, AbbVie holds the top position, followed by Grabango and Bear Flag Robotics.

Intelligent embedded systems have revolutionised the capabilities of embedded devices by integrating advanced artificial intelligence (AI) algorithms. The innovation involves the integration of AI technologies, such as machine learning and computer vision, into embedded systems, enabling them to make intelligent decisions and perform complex tasks.

To further understand how artificial intelligence is disrupting the technology industry, access GlobalData’s latest thematic research report on Artificial Intelligence (AI) – Thematic Intelligence.

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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.