{"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

\"Figure<\/a>

Figure 1: Block diagram of adaptive sensor interface.<\/p><\/div>\n

  1. M. Yip and A. P. Chandrakasan, “A resolution-reconfigurable 5-to-10b 0.4V-to-1V power scalable SAR ADC,” IEEE International Solid-State Circuits Conference, <\/em>Feb 2011, pp. 190-191. [↩<\/a>] <\/li>
  2. F. Chen, A. P. Chandrakasan, and V. M. Stojanovic, “Design and analysis of a hardware-efficient compressed sensing architecture for data compression in wireless sensors, ” IEEE Journal of Solid-State Circuits<\/em>, vol. 47, no. 3, pp. 744-756, Mar. 2012. [↩<\/a>] <\/li><\/ol>","protected":false},"excerpt":{"rendered":"

    Wireless sensor nodes (WSNs) have a great potential to save energy and improve safety when applied to building energy monitoring,…<\/p>\n","protected":false},"author":1,"featured_media":5481,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[26],"tags":[17,11520],"_links":{"self":[{"href":"https:\/\/mtlsites.mit.edu\/annual_reports\/2012\/wp-json\/wp\/v2\/posts\/5480"}],"collection":[{"href":"https:\/\/mtlsites.mit.edu\/annual_reports\/2012\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mtlsites.mit.edu\/annual_reports\/2012\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mtlsites.mit.edu\/annual_reports\/2012\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/mtlsites.mit.edu\/annual_reports\/2012\/wp-json\/wp\/v2\/comments?post=5480"}],"version-history":[{"count":4,"href":"https:\/\/mtlsites.mit.edu\/annual_reports\/2012\/wp-json\/wp\/v2\/posts\/5480\/revisions"}],"predecessor-version":[{"id":6434,"href":"https:\/\/mtlsites.mit.edu\/annual_reports\/2012\/wp-json\/wp\/v2\/posts\/5480\/revisions\/6434"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/mtlsites.mit.edu\/annual_reports\/2012\/wp-json\/wp\/v2\/media\/5481"}],"wp:attachment":[{"href":"https:\/\/mtlsites.mit.edu\/annual_reports\/2012\/wp-json\/wp\/v2\/media?parent=5480"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mtlsites.mit.edu\/annual_reports\/2012\/wp-json\/wp\/v2\/categories?post=5480"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mtlsites.mit.edu\/annual_reports\/2012\/wp-json\/wp\/v2\/tags?post=5480"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}