IoT-networks group-based model that uses AI for workgroup allocation

This paper presents a centralized management architecture model for designing workgroup-based Internet of Things (IoT) and Everything (IoE) networks. The establishes the organization an object according to its functions capacities in layers. From model, it is derived design algorithms that give network operation. These include multi-protocol communication interconnectivity algorithm, routing resource sharing grouping all controlled by Artificial Intelligence (AI). algorithm consists creating collaborative workgroups based on Machine Learning (ML) techniques use objects’ features allocating these within workgroup attends type service layer capabilities. was tested with simulation shows Machine-to-Machine (M2M) interaction between devices involved providing user Smart Home. uses AI hosted IoT-Gateway collect data define connected object's services. extraction done using Discovery Functions Services Protocol (DFSP) transported through IoT-Protocol. With this information, assigns new when enters network. result tests can be used know which ML technique has better accuracy.