Optimized local control strategy for voice-based interaction-tracking badges for social applications

Abstract

This paper presents a method to design optimized local control strategies for Cyber-Physical Systems that produce reliable data models for social applications. Data models have different semantics and abstraction levels. The local control strategies manage ad-hoc nano-clouds of embedded computing and communication nodes (CCNs) used for data collection, modeling, and communication. Control strategies consider tradeoffs defined by the resource constraints of embedded CCNs (e.g., computing power, communication bandwidth, and energy), assurance requirements (e.g., robustness) of the models, and privacy of users. Experiments evaluate and demonstrate the effectiveness of the control strategies for nano-clouds composed of smart voice-based interaction-tracking badges.