Abbrevation
ACM SenSys
City
TorontoON
Country
Canada
Deadline Paper
Start Date
End Date
Abstract

The ACM Conference on Embedded Networked Sensor Systems (SenSys 2012)<br>solicits innovative research papers on the systems issues of networked,<br>embedded sensing and control&#046;<br>This is an exciting time in the development of the conference, as we reach<br>the 10th anniversary of the first conference held in Los Angeles&#046; ACM SenSys<br>brings together academic industry, and government professionals to a premier<br>single&#8211;track, highly selective forum on sensor network design,<br>implementation, and application&#046;<br>We seek technical papers describing original ideas, groundbreaking results<br>and/or quantified system experiences involving sensor systems&#046; SenSys takes<br>a broad systems perspective of sensor applications and systems&#046; Topics of<br>interest include, but are not limited to, the following:<br>&#8211; Experience with real&#8211;world deployments and applications<br>&#8211; Resource management and OS support for sensing systems<br>&#8211; Energy management and harvesting for long&#8211;term operation<br>&#8211; Innovative sensing applications across broad areas (e&#046;g&#046;, environmental<br>monitoring, mobile healthcare, transportation, education)<br>&#8211; Wireless communication systems and protocols for sensor networks<br>&#8211; Sensor systems leveraging smart phones, body area networks, RFIDs,<br>robots, etc&#046;<br>&#8211; Sensing technologies for pervasive computing<br>&#8211; Sensor network measurement and characterization<br>&#8211; Programming paradigms and models for distributed sensing<br>&#8211; Sensor network debugging, fault&#8211;tolerance and reliability<br>&#8211; Sensing, actuation and control in cyber&#8211;physical systems<br>&#8211; Distributed sensor data storage, retrieval, processing and management<br>&#8211; Approaches to sensor network architecture<br>&#8211; Sensor data quality, integrity, and trustworthiness<br>&#8211; In&#8211;network data reduction, inference, and signal processing<br>&#8211; Security and privacy in sensor networks<br>&#8211; Time and location estimation and management<br>