Please find below the call for papers for SenSys 2020. The deadline for abstract registration is Friday March 29th 23:59 AoE ------------------------------------------------------------------------------------------------------------------------------- SenSys 2020 Call for Papers
The ACM Conference on Embedded Networked Sensor Systems (SenSys 2020) is the premier computer systems conference focused on the architecture, design, implementation, and performance of networked sensing systems, sensor-oriented data modeling and analytics, and sensor-enabled applications. ACM SenSys brings together academic, industry, and government professionals to a single-track, highly selective forum that takes a broad view on the areas of computing relevant to the future of networked embedded sensor systems. Topics of interests include, but are not limited to, the following: * New platforms and hardware designs for networked sensor systems * New communication paradigms for ubiquitous connectivity * Low-power wireless media access control, network, and transport protocol designs * Systems software, including operating systems, network stacks, and programming * System services such as time and location estimation * Low-power operation, energy harvesting, and energy management * Resource-efficient machine learning for embedded and mobile platforms * Mobile and pervasive systems with elements of networked sensing * Data management and analytics, including quality, integrity, and trustworthiness * Learning algorithms and models for perception, understanding, and adaptation * Heterogeneous collaborative sensing, including human-robot sensor systems * Security and privacy in networked sensor applications and systems * Fault-tolerance, dependability, and verification * Applications and deployment experiences We invite technical papers describing original ideas, groundbreaking results, and real-world experiences involving innovative networked embedded sensor systems. Successful submissions will explain why the topic is relevant to a vision of the future of sensing systems. Submissions will be judged on originality, significance, clarity, relevance, and correctness. Important Dates * Paper Registration and Abstract: March 27 (Friday), 2020, 23:59 AoE * Paper Submission: April 6 (Monday), 2020, 23:59 AoE * Notification of Paper Acceptance: June 20 (Saturday), 2020 Note: These are hard deadlines. No extension will be granted. Submission Guidelines Submitted papers must be unpublished and must not be currently under review for any other publication. Submissions must be full papers, at most 12 single-spaced 8.5" x 11" pages with 9-pt font size in two-column format, including figures and tables. As for references, submissions may include as many pages as needed. All submissions must use the LaTeX (preferred) or Word styles found here<http://www.acm.org/publications/proceedings-template>. LaTeX submissions should use the acmart.cls template (sigconf option), with the default 9-pt font. This format will be used also for the camera-ready version of accepted papers. Authors must make a good faith effort to anonymize their submissions. Papers that do not meet the size, formatting, and anonymization requirements will not be reviewed. We require each paper to be in Adobe Portable Document Format (PDF) and submitted through the conference submission system<https://sensys20.hotcrp.com/>. Papers that describe experiments on human subjects, or that analyze nonpublic data derived from human subjects (even anonymized data), should briefly describe how the research protocol addresses ethical considerations and whether their work was vetted by an ethics review (e.g., IRB approval). We expect authors to follow the rules of their host institutions around data collection and experiments with human subjects. Accepted submissions will be available on the ACM digital library at most two weeks before the conference. SenSys 2020 Conference Submission System<https://sensys20.hotcrp.com/> Organization * General chairs: Jin Nakazawa (Keio), Polly Huang (NTU) * Program chairs: Pei Zhang (CMU), Marco Gruteser (Google / Rutgers Univ.)
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