"While technology analysis is still new, it can provide some of the needed foundations for technology as a field of its own and answer such questions as'Can AI invent?.'" Not long ago, Dr. Stephen Thaler, a member of the scientific community, began claiming that his artificial intelligence (AI) machine, DABUS, was a bona fide inventor. The outcome so far has been that the claim has been rejected in most jurisdictions. A notable exception is South Africa, which accepted Thaler's patent application under "Formalities Examination" with DABUS as named inventor. The acceptance of the patent in South Africa and the evolution of the legal field opens the possibility of further assertions and challenges with respect to AI inventorship.

Thanks to rapid development of artificial intelligence technology in recent years, the current artificial intelligence technology is contributing to many part of society. Education, environment, medical care, military, tourism, economy, politics, etc. are having a very large impact on society as a whole. For example, in the field of education, there is an artificial intelligence tutoring system that automatically assigns tutors based on student's level. In the field of economics, there are quantitative investment methods that automatically analyze large amounts of data to find investment laws to create investment models or predict changes in financial markets. As such, artificial intelligence technology is being used in various fields. So, it is very important to know exactly what factors have an important influence on each field of artificial intelligence technology and how the relationship between each field is connected. Therefore, it is necessary to analyze artificial intelligence technology in each field. In this paper, we analyze patent documents related to artificial intelligence technology. We propose a method for keyword analysis within factors using artificial intelligence patent data sets for artificial intelligence technology analysis. This is a model that relies on feature engineering based on deep learning model named KeyBERT, and using vector space model. A case study of collecting and analyzing artificial intelligence patent data was conducted to show how the proposed model can be applied to real world problems.

With the newest smart cameras in town, customers at Roads and Transport Authority's (RTA) centres no longer need to rate their experience from'one to five' or from'happy to sad'. The new lenses can instantly capture facial expressions and determine how happy - or frustrated - customers are. Four of the RTA's centres, Al Barsha, Umm Al Ramool, Deira and Al Awir, are now equipped with these smart cameras, as part of the agency's first artificial intelligence (AI) initiative under its Smart Dubai strategy. "The initiative aims to measure customers' happiness through smart cameras that analyse the extent of their happiness," said Maher Shirah, director of smart services at the RTA's corporate technology support services sector. Accordingly, the technology gives an instant and accurate indicator of their happiness." The process assists in compiling reports about customers' experiences and enables decision-makers to take an appropriate action to improve the service, if required. Manufactured in the UAE, the AI-powered cameras are "highly accurate", the RTA said. It can take snaps at a rate of 30 frames per second at a seven-metre range within an angle of 65 degrees. It also has an autofocus feature with no flash required and can minimise the light on people's faces, allowing for a more accurate reading of their expressions. After an image is captured, the system sends detailed reports through a dashboard that generates real-time updates on customer happiness. It also sends instant SMS and e-mail notifications when the happiness rating at any centre drops from pre-defined levels. The team can then take the necessary steps to restore customers' happiness. "The smart happiness index monitors the variation in customers' happiness level from the moment they step into the centre until the moment they leave, and links it with the level of service delivered.