SenSys-ML 2024
In conjunction with CPS-IoT Week 2024
The 3rd Workshop on Machine Learning on Edge in Sensor Systems (SenSys-ML 2024)
Sensors have become more ubiquitous through the spread of the Internet of Things and increased market penetration of smartphones. The ensuing flood of data has the promise to advance state of the art in ways that could change the life of every human on the planet, including improvements in healthcare, environmental management, and city management. To enable this revolution machine learning needs to fill the gap to turn raw data into an understandable and actionable system. However, resource constraints, complex architectures, and challenging study designs and ground truth collection are some of the many hurdles that must be overcome to bring a promising idea to reality in this domain.
Sensys-ML focuses on providing extensive feedback from a diverse pool of people on Work In Progress papers involving machine learning on sensor systems (TinyML). The focus is on work that combines sensor signals from the physical world with machine learning, particularly in ways that are distributed to the device or use edge and fog computing. The development and deployment of ML at the very edge remains a technological challenge constrained by computing, memory, energy, network bandwidth and data privacy and security limitations. This is especially true for battery operated devices and always-on use cases and applications. Our end goal is to help all attendees design systems that are more scientifically advanced, robust to failure, efficient, and well validated.
Workshop Topics
Topics of interest include, but are not limited to, the following:- Advancement in Hardware for enabling TinyML capabilities at the edge
- System Architecture for supporting TinyML and UltraML
- Parallel and Distributed Machine Learning for Sensor and Network systems
- Machine Learning driven Data Analytics
- System and Algorithm co-design for practical TinyML at Sensor Systems
- Security and Privacy at the Edge
- Video Analytics at the Edge
- Validation and debugging of TinyML and UltraML
- Emerging Sensing Applications using TinyML
Important Dates
- Registration and Submission:
5th Feb 2024 AoENew deadline: 28th Feb 2024 AoE - Notification of Acceptance: 6th March 2024
- Camera-Ready: 12th March 2024 AoE
- Workshop Date: 13th May 2024
Submission Guidelines
Submitted papers must be unpublished and must not be currently under review for any other publication. There are two submission tracks:
- Full papers, which will be eligible for publication at most 6 single-spaced 8.5” x 11” pages with 9-pt font size in two-column format, including figures and tables and references. All submissions must use the LaTeX (preferred) or Word styles found here. LaTeX submissions should use the acmart.cls template (sigconf option), with the 9-pt font, make sure to use \documentclass[9pt, sigconf]{acmart} in your document. This format will be used also for the camera-ready version of accepted papers. Papers will go through double-blind peer reviewing by the PC. 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 Sensys-ML HoTCRP submission site. Accepted papers will be published in the ACM Digital Library. At least one of the authors of every accepted paper must register and present the paper at the workshop. The program committee will elect one paper for the Best Paper Award.
- Work In Progress, which is a presentation-only format. We request a 1 single spaced 8.5” x 11” page abstract submission. Please note that these submissions will not be published as this is a presentation-only format.