  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.
