{"id":5480,"date":"2012-07-18T22:28:21","date_gmt":"2012-07-18T22:28:21","guid":{"rendered":"https:\/\/mtlsites.mit.edu\/annual_reports\/2012\/?p=5480"},"modified":"2012-07-18T22:28:21","modified_gmt":"2012-07-18T22:28:21","slug":"adaptive-low-power-sensor-interfaces-for-wireless-sensor-nodes","status":"publish","type":"post","link":"https:\/\/mtlsites.mit.edu\/annual_reports\/2012\/adaptive-low-power-sensor-interfaces-for-wireless-sensor-nodes\/","title":{"rendered":"Adaptive Low-power Sensor Interfaces for Wireless Sensor Nodes"},"content":{"rendered":"
Wireless sensor nodes (WSNs) have a great potential to save energy and improve safety when applied to building energy monitoring, structural monitoring, and environmental monitoring. These systems typically comprise a low-power microprocessor, a wireless transceiver, analog signal conditioning circuits, and an analog-to-digital converter (ADC). However, in order to be sustained by harvested ambient energy, these systems must operate within a tight power budget. Today, circuit blocks like amplifiers and ADCs have individually been highly optimized, but achieving greater power savings requires approaching the system as a whole.<\/p>\n
This work focuses on power reduction of the sensor interface circuitry through resolution and sampling frequency scaling [1<\/a>] <\/sup> and compressed sensing algorithms [2<\/a>] <\/sup>. Combining the control provided by the algorithms with the scalability designed into the interface circuits creates a fully self-contained adaptive sensor interface that scales its sampling frequency and resolution, among other parameters, based on the local information content of the incoming signal.<\/p>\n