# Reactive Sensing and Multiplicative Frame Super-resolution

## TL;DR

This paper introduces reactive sensing, a method for evaluating objects using secondary sources when primary data is unavailable, grounded in multiplicative frames for super-resolution analysis.

## Contribution

It develops a theoretical framework linking physical volume modeling with multiplicative frames, enabling reactive sensing and super-resolution analysis.

## Key findings

- Reactive sensing effectively assesses objects with limited primary data.
- Multiplicative frames provide a quantitative basis for sensor sensitivity analysis.
- The theory supports practical super-resolution applications in various fields.

## Abstract

The problem is to evaluate the behavior of an object when primary sources of information about the object become unavailable, so that any information must be obtained from the intelligent use of available secondary sources. This evaluative process is reactive sensing. Reactive sensing is initially viewed in terms of spatial super-resolution.The theory of reactive sensing is based on two equivalent ideas, one physical and one mathematical. The physical idea models volume, e.g., engine volume in the case of analyzing engine health, and the sensitivity of sensors to such volume.The mathematical idea of multiplicative frames provides the factorization theory to compare quantitatively such volume and sensitivity. This equivalence is the foundation for reactive sensing theory and its implementation.