The retail industry continues to be a hotbed of patent innovation. Activity is driven by increasing e-commerce, data analytics, supply chain management and risk mitigation techniques, and the growing importance of technologies such as artificial intelligence (AI), virtual reality, augmented reality, 3D imaging, and machine learning. In the last three years alone, there have been over 156,000 patents filed and granted in the retail industry, according to GlobalData’s report on Artificial intelligence in retail: automated object recognition. 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 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.
50+ innovations will shape the retail industry
According to GlobalData’s Technology Foresights, which plots the S-curve for the retail industry using innovation intensity models built on over 115,000 patents, there are 50+ innovation areas that will shape the future of the industry.
Within the emerging innovation stage, cosmetics recommenders, 3D garment modeling, and in-store theft monitoring are disruptive technologies that are in the early stages of application and should be tracked closely. In-store product recognition, personalized recommendation AI, and smart checkout are some of the accelerating innovation areas, where adoption has been steadily increasing. Among maturing innovation areas is automated object recognition, which is now well established in the industry.
Innovation S-curve for artificial intelligence in the retail industry
Automated object recognition is a key innovation area in artificial intelligence
Automated object recognition technology refers to the use of sensors or cameras to detect and identify objects. This technology makes use of stored references to identify different objects in real time without human intervention. The technology is aimed at achieving what a human eye sees and comprehends for recognition.
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 retail companies, and up-and-coming start-ups engaged in the development and application of automated object recognition.
Key players in automated object recognition – a disruptive innovation in the retail 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 automated object recognition
| Company | Total patents (2010 - 2022) | Premium intelligence on the world's largest companies |
| Toshiba | 201 | Unlock Company Profile |
| Nant | 136 | Unlock Company Profile |
| Cox Enterprises | 125 | Unlock Company Profile |
| Walmart | 103 | Unlock Company Profile |
| NEC | 42 | Unlock Company Profile |
| Evryx Acquisition | 12 | Unlock Company Profile |
| Trax Technology Solutions | 11 | Unlock Company Profile |
| Mashgin | 9 | Unlock Company Profile |
| NCR | 9 | Unlock Company Profile |
| Casio Computer | 8 | Unlock Company Profile |
| Wistron | 6 | Unlock Company Profile |
| Kyocera | 6 | Unlock Company Profile |
| JPMorgan Chase | 5 | Unlock Company Profile |
| Hydra | 5 | Unlock Company Profile |
| Ricoh | 4 | Unlock Company Profile |
| Digimarc | 4 | Unlock Company Profile |
| Ishida | 4 | Unlock Company Profile |
| OPTIMUM | 3 | Unlock Company Profile |
| Panasonic | 3 | Unlock Company Profile |
| ArcSoft | 2 | Unlock Company Profile |
| Evryx Technologies | 1 | Unlock Company Profile |
| Berkshire Hathaway | 1 | Unlock Company Profile |
| Tiliter | 1 | Unlock Company Profile |
Source: GlobalData Patent Analytics
The leading players in the automated object recognition space in terms of patents filed are Toshiba, Trax Technology Solutions, Nant, Cox Enterprises, and Walmart.
Toshiba’s produce recognition AI, ELERATM is designed to optimize the self-checkout experience of customers at retail outlets, as it enables scanning of all items in the cart, including those without bar codes, for quick and effective checkout The updated AI platform claims to require only a small volume of reference/training data unlike typical recognition software, which rely on large volumes of data. Toshiba’s object detection AI can even work with a single image to accurately recognize objects, significantly reducing misidentification and improving loss prevention for retailers.
OPTIMUM, Cox Enterprises, and Walmart are the top three companies in this space in terms of application diversity.
By geographic reach, Nant leads the pack, followed by Cox Enterprises and Walmart.
Automated object detection systems have a wide range of applications in the retail industry including abnormality detection, inventory, security & risk management, optimization of product placement, as well as to create interactive experiences for shoppers.To further understand the key themes and technologies disrupting the retail industry, access GlobalData’s latest thematic research report on Artificial Intelligence (AI) in Retail and Apparel.
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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.
