IoT devices with data analytics capabilities Using machine learning algorithms for intelligent decision making: a review of patents and the cited academic literature

Abstract

Innovation in IoT data analytics is essential for social and economic advancement as well as for opening up new business prospects. IoT data analytics applications have garnered a lot of attention lately for information mining, knowledge extraction, and prediction/inference making. Another field of study that has been effectively used to address a variety of networking issues, including resource allocation, routing, traffic engineering, and security, is machine learning. The use of machine learning (ML)-based techniques to enhance different Internet of Things applications has increased recently. Despite a wealth of research on machine learning and IoT data analytics, there is a dearth of studies that only address the development of ML-based methods for IoT data analysis. The present study examines the patenting practices of various international jurisdictions in the domain of IoT data analytics, in addition to the academically cited literature. Between 2000 and 2023, we gathered 24,931 patent applications, and 13,432 scholarly works were cited by the patents. Our research details the trends in the development of IoT data analytics technologies and the relationship between patenting activity and the referenced scientific literature. Additionally, it examines and displays the social networks found in scientific publications and patents. As a result, it discloses the patenting practices of international jurisdictions concerning IoT data analytics technologies, the degree to which different agents such as Lens Id and Applicants interact within social networks, and the connection between patents and science. According to this study, information retrieval, database structures, and file system structures make up the majority of the IPC categories for filed IoT data analytics patent applications. Chinese businesses and individuals make up the bulk of the patent Lens Id and Applicants. Computer science and medicine are scientific fields that are more strongly connected within the network of co-fields. The relationship between scientific works and inventions is not very strong.