Sensing Without Colocation: Operator-Based Virtual Instrumentation for Domains Beyond Physical Reach
Jay Phil Yoo, Kazuma Kobayashi, Souvik Chakraborty, Syed Bahauddin Alam

TL;DR
This paper introduces operator-theoretic virtual sensing, a novel principle enabling remote measurement of inaccessible fields by learned operators, demonstrated through a system mapping neutron monitors to global radiation dose fields with high efficiency.
Contribution
The paper presents a new sensing paradigm that uses learned operators to measure inaccessible target fields, overcoming traditional colocated sensing limitations.
Findings
Mapped 12 neutron monitors to global dose fields at 10,000m altitude
Achieved sub-millisecond inference times
Operated efficiently on embedded AI hardware with low power consumption
Abstract
Classical sensing rests on one foundational assumption: the quantity of interest must be colocated with the measurement device. This is not an engineering convenience. It is the organizing principle of every instrumentation standard developed over the past century, and it fails completely at aviation altitude, where no physical sensor can survive long enough to monitor the cosmic radiation field that irradiates millions of aircrew annually. We establish that this barrier is resolved by a new sensing principle: when the sensor manifold and the target field manifold are physically disjoint, a learned operator bridging them \emph{is} the instrument. We term this \textbf{operator-theoretic virtual sensing} and instantiate it in \textbf{STONe}, which maps \textbf{twelve} ground-based neutron monitors (sparse, indirect, surface-bound) to the complete global dose field at 10{,}000\,m across…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMeteorological Phenomena and Simulations · Atmospheric aerosols and clouds · Air Quality Monitoring and Forecasting
