Leveraging live machine learning and deep sleep to support a self-adaptive efficient configuration of battery powered sensors

Sensor networks empower Internet of Things (IoT) applications by connecting them to physical world measurements. However, the necessary use of limited bandwidth networks and battery-powered devices makes their optimal configuration challenging. An over-usage of periodic sensors (i.e. too frequent measurements) may easily lead to network congestion or battery drain effects, and conversely, a lower usage is likely to cause poor measurement …