Interested in how innovations in distributed sensing are being developed and applied to support science across AGU disciplines?
We are exploring the degree of need for a Technical Committee that cross-cuts AGU to help us all learn from the advances in distributed sensing that are occurring within our disciplines. Such a Committee would work to develop conference sessions and other activities that bridge and integrate knowledge from across all of AGU's Sections.
Please complete this brief survey to help us assess the degree of community interest in establishing a Distributed Sensing Technical Committee:
Brief Survey for Distributed Sensing Technical Committee (https://forms.gle/KQX7vJ9NZDRgaDR49)
There will be an information session at AGU2024 on Tuesday, Dec.10, from 8:00-9:00am. If you would like to attend, please share your contact information via the survey.
Additional Description: Sensing technologies are used in diverse applications across all disciplines of the earth sciences. Yet there are unique challenges associated with the development of sensors, deployment of sensing networks, management and dissemination of sensing data, and utilization of sensors in applications that are common across all disciplines. An AGU Technical Committee for Distributed Sensing could enable coordination of activities across AGU Sections to support sharing of knowledge, best practices, and emerging technologies for distributed sensing in all disciplines. The technical committee for Distributed Sensing would therefore be composed of interested members from all Sections of AGU and focus on developing co-sponsored thematic conference sessions or other activities that emphasize unique cross-cutting advances in distributed sensing that can be applied in a wide variety of applications.
Note that Distributed Sensing as used here refers to individual sensors, networks of sensors, and other field based measurement technologies, which could include geophysical and remote sensing, as well as broader technologies related to sensing, such as communications, edge computing, data repositories, machine learning and other related areas.
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Stephen Moysey, Professor
East Carolina University
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