Data transmission accounts for significant energy consumption in wireless sensor networks where streaming data is generatedby the sensors. This impedes their use in many settings, including livestock monitoring over large pastures (which formsour target application). We present Ambrosia, a lightweight protocol that utilizes a window-based timeseries forecastingmechanism for data reduction. Ambrosia employs a configurable error threshold to ensure that the accuracy of end applicationsis unaffected by the data transfer reduction. Experimental evaluations using LoRa and BLE on a real livestock monitoringdeployment demonstrate 60% reduction in data transmission and a 2X increase in battery lifetime.