Toward Integrating Intelligence Into Everything Around Us

Abstract

The vision of ambient intelligence promises a world where computational capabilities seamlessly integrate into everyday objects and environments, creating systems that sense, learn, and adapt to human needs while remaining invisible to users. Despite significant advances in miniaturization and low-power computing, true ambient intelligence has remained elusive, hindered by a fundamental challenge: current intelligent systems require substantial energy, complex hardware, and frequent maintenance, making widespread deployment impractical. We introduce a paradigm shift in how we create intelligent systems by fundamentally reimagining sensing and computing architectures from first principles for extreme resource constraints.

This thesis centers on encoding intelligence directly into the physical domain through novel hardware-software co-design, where passive structures perform initial signal transformations without consuming power. Through novel architectures across acoustic, radio frequency, and optical domains, we demonstrate systems that achieve spatial perception, global positioning, and environmental monitoring with orders of magnitude less power than conventional approaches. These innovations enable intelligence in previously impossible contexts: insect-scale robots that navigate complex environments, sticker-sized tags that provide GPS-like tracking for years on a single battery, and wireless sensors that monitor food quality throughout global supply chains. By bridging the gap between what intelligent systems can do and what resource-constrained platforms can support, this work establishes a foundation for truly pervasive intelligence that operates sustainably at large scale.