Representation of best Practices in IoT Sistems by Using the SEMAT Essence Kernel

Abstract

The Internet of Things (IoT) facilitates coordinated interaction among machines, devices, and users. Best practices in IoT encompass processes designed to enhance the efficiency of IoT systems implementation. While state-of-the-art reviews reveal diverse methods for modeling such practices, existing models in the literature remain fragmented: they often address isolated development phases and lack replicability due to insufficiently structured methodologies. This study addresses this gap by modeling IoT best practices found in scientific literature on IoT systems using the SEMAT Essence Kernel language (Software Engineering Method and Theory). From an analysis of 97 scientific papers, four best practices were selected and processed through a terminological extractor, generating a dictionary of 123,566 terms to standardize their nomenclature. Each practice’s components were systematically mapped to SEMAT Essence Kernel elements.  The resulting models represent best practices in power consumption, data security, cloud computing resource utilization, and Big Data integration for IoT systems. The proposed approach demonstrates the SEMAT Essence Kernel’s efficacy in formalizing IoT best-practice knowledge. Validation by a panel of IoT experts yielded promising results, confirming the models’ robustness~and~applicability.