Technology Mapping of ARM And RISC-V Embedded Architectures for Internet of Things Applications: A Systematic Literature Review

Abstract

The Internet of Things (IoT) has emerged as a transformative paradigm reshaping industries through the interconnection of billions of smart devices across diverse domains. As IoT ecosystems continue to expand, the embedded processor architecture serving as the computational core of each connected device has become a critical determinant of system performance, energy efficiency, reliability, security, and overall cost-effectiveness. This systematic review examined the role of ARM-based and RISC-V embedded architectures in IoT applications, with the goal of developing an evidence-based technology mapping framework for architecture selection. Following PRISMA 2020 guidelines, a structured search was conducted across five databases (IEEE Xplore, ACM Digital Library, SpringerLink, ScienceDirect, Google Scholar) for peer-reviewed studies published between 2024 and 2026. After screening 184 initial records, 28 studies met the inclusion criteria. Findings revealed that while ARM architectures demonstrate established performance benchmarks (1.25-2.14 DMIPS/MHz) with mature ecosystem support (70% developer priority), RISC-V implementations offer significant customization potential with 12-17% cycle reduction for specialized workloads through custom extensions. The ESP32 platform provides integrated wireless capabilities with TCP throughput of 12-15 Mbps. A substantial operational gap exists between technical performance data and actionable architecture selection guidance. Based on the synthesis, this study proposes an evidence-based technology mapping framework that integrates computational performance, energy efficiency, ecosystem maturity, security mechanisms, and application-specific requirements. Key best practices include application-driven evaluation, multi-criteria decision analysis, ecosystem readiness assessment, and balanced consideration of technical and strategic factors.