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Study of federated learning in industrial IoT
Mitra Pooyandeh,Insoo Sohn 한국통신학회 2021 한국통신학회 학술대회논문집 Vol.2021 No.11
The Industrial Internet of Things (IIoT) is actually a subset of IoT. Therefore, the growing development of IoT technology in recent years and its application in the industry have improved the performance of various industries. Certainly, the extensive usage of IoT in industrial is led to producing a huge amount of data that require a server for processing. while sending this amount of data causes several issues such as data centralization and privacy-preserving. Federated learning (FL) is an exhaustive solution to overcome these problems. Given that federated learning technology implemented in IIoT keep the data on the device as result, it helps the data security and optimizes the communication cost. In this article, we present a study of FL in IIoT.
On Modeling and Simulation of AI-based IoT
Mitra Pooyandeh,Insoo Sohn(손인수) 한국통신학회 2021 한국통신학회 학술대회논문집 Vol.2021 No.6
Nowadays, the Internet of Things has become one of the essential technologies for connecting devices in the telecommunications, electricity, medical, automotive, and other industries. The Internet of Things includes an infinite set of connections and intelligent endpoints such as sensors, actuators, and so on. IoT devices, which include sensor networks with an unlimited number of sensors, face many problems, including power limitations and hardware limitations. Therefore, simulation is the best solution for changing and extending protocols in sensor networks. Furthermore, AI is becoming an important tool to solve problem related to IoT and hardware and power constraints. In this article, we review existing simulation and modeling tools and discuss including AI in the simulation.