Skill UI

A comprehensive set of programmatic interfaces for RuView's Wi-Fi sensing capabilities, including the CLI binary, REST API, and WebAssembly builds. This toolkit allows developers to integrate sophisticated disaster survivor detection and signal analysis into various environments, such as scripting, web browsers, and edge devices (ESP32-WASM3). Ideal for systems requiring cross-platform, scalable sensing data streams.

A comprehensive guide for bringing RuView CSI sensing nodes (ESP32-S3/C6) online. This skill covers the full lifecycle: building the embedded firmware, flashing the device, provisioning WiFi credentials, and confirming the Continuous Sensing Image (CSI) data stream. Essential for physical hardware deployment and debugging of complex sensing systems.

This guide provides a comprehensive framework for positioning mobile and embedded systems manuscripts for ACM MobiSys. It details venue fit, contribution framing, necessary real-device evidence, and how to differentiate the work from related conferences (e.g., MobiCom, UbiComp). Use this when your research value depends on surviving real-world device constraints, sensing, or edge computing environments.

A comprehensive guide for designing and auditing rigorous experiments for sensing systems and information processing claims. It emphasizes the necessity of measuring performance on real hardware (not simulation), accurately instrumenting ground truth, quantifying energy consumption, latency, and physical footprint, and establishing fair, skeptical baselines. This ensures scientific rigor and reproducibility in research submissions.

Provides strict guidelines for structuring technical research papers, especially in sensing systems. It dictates how to partition core claims, methods, and decision-critical evidence between the main body (the reviewed pages, limited to ≤12 pages) and supplementary artifacts, appendices, or demos. The core rule is that the paper must be judged solely from the reviewed pages, ensuring all necessary evidence is visible to the reviewer.

A comprehensive project management guide detailing the entire lifecycle of a high-stakes sensing systems research submission. It provides a detailed backward planning timeline, covering critical milestones from initial venue and track selection, hardware freezing, field deployment logistics, double-blind review, and final submission to major conferences like SenSys. It emphasizes managing the critical path of field work and data artifacts.

This guide provides structured rules for authors writing sensor-systems or information-processing papers. It emphasizes leading with the physical sensing problem, requiring real-hardware measurements for energy, latency, and ground truth, and adhering to strict academic formatting constraints. Use this when revising submissions to ensure technical depth and practical deployability.

A comprehensive guide for designing and auditing rigorous empirical evaluations for sensing systems, particularly Human Activity Recognition (HAR). It emphasizes best practices such as leave-one-subject-out cross-validation, using real human subjects under diverse conditions, reporting event-level metrics (e.g., Macro-F1) over raw accuracy, establishing fair baselines, and mitigating data leakage (e.g., subject or session leakage). This ensures that reported results are robust, generalizable, and defensible against academic skepticism.

A comprehensive guide detailing the required structure and technical rigor for writing papers in sensing and embedded systems (SenSys). It mandates replacing vague adjectives with concrete, measured metrics (e.g., energy in joules, latency in milliseconds) and structuring the argument around a clear 'pain $\to$ gap $\to$ mechanism $\to$ measured behavior' arc on the first page. Essential for academic researchers and engineers.