Abstract
Indoor photovoltaics (IPVs) can significantly reduce reliance on disposable batteries in Internet of Things (IoT) devices. Yet, most evaluations use idealized lighting setups and single performance metrics, neglecting the influence of real indoor environments on device performance. This Perspective advances a deployment-centered approach: (i) realistic testing under mixed or hybrid lighting (daylight + artificial); (ii) intelligent integration that aligns absorber bandgap, series-connected cells, geometric fill factor, and power management integrated circuits with workloads and duty cycles; and (iii) IoT-ready stability assessed under the same realistic indoor scenes and light/dark sequences. We propose a compact field-to-lab pipeline, translate it into voltage-matching design rules, and use photon-to-compute metrics to link harvested power to on-device sensing and learning. The goal is low-maintenance, battery-free nodes that scale reliably in buildings, logistics, and wearable applicationsultimately cutting electronic waste.