The Role of Artificial Intelligence in Enhancing Performance and Power Control of Embedded Systems (Published)
Artificial intelligence is revolutionizing embedded systems by addressing fundamental challenges in performance optimization and power management that have traditionally constrained these resource-limited devices. This technological convergence represents a paradigm shift from static, preprogrammed approaches to dynamic, learning-capable systems that can autonomously adapt to changing conditions and workloads. The integration of sophisticated machine learning algorithms directly onto embedded hardware enables dramatic improvements in processing capabilities, energy efficiency, and operational autonomy across diverse application domains. From automotive systems processing massive sensor data volumes with sub-150ms latency to wearable medical devices achieving multi-day battery life while continuously monitoring vital signs, embedded AI demonstrates transformative potential. Through specialized hardware architectures, algorithm optimization techniques, and intelligent power management strategies, embedded systems now achieve unprecedented capabilities despite their inherent constraints. The economic impact is substantial, with the market reaching $45.3 billion by 2025, driven by applications spanning industrial automation, autonomous vehicles, and consumer electronics. This technological evolution enables embedded systems to process data locally with reduced latency, enhanced privacy, improved reliability, and significant energy savings, fundamentally changing how intelligent devices interact with and respond to their environments.
Keywords: Artificial Intelligence, Performance Enhancement, edge computing, embedded systems, power optimization