The success of future Internet-of-Things (IoT) based application deployments depends on the ability of wireless sensor platforms to sustain uninterrupted operation based on environmental energy harvesting. In this paper, we deploy a multitransducer platform for photovoltaic and piezoelectric energy harvesting and collect raw data about the harvested power in commonly-encountered outdoor and indoor scenarios. We couple the generated power profiles with probability mixture models and make our data and processing code freely available to the research community for wireless sensors and IoT-oriented applications. Our aim is to provide data-driven probability models that characterize the energy production process, which will substantially facilitate the coupling of energy harvesting statistics with energy consumption models for processing and transceiver designs within upcoming IoT deployments
