Introduction to the Special Issue on Human interaction aware Data Analytics for Cyber physical Systems
Cyber physical Systems (CPS) are the systematic combination of physical processes, information, and communication technology. Typical examples of CPS are civil infrastructure monitoring, industrial control, and avionic systems. Such systems are generally deployed as a network of interacting elements with a huge amount of data. In addition, with the rapid advance of sensing, computing, and storing technologies, the amount of data increases tremendously. This imposes fundamental challenges on the design and management of CPS in multiple aspects, such as energy efficiency, security, privacy, reliability, scalability, and flexibility. Tackling these challenges necessitates innovative techniques of data analytics for handling the massive data in CPS. In the design of innovative data analysis techniques, human activities and interactions with CPS must be taken into account since humans can monitor and control physical processes when interacting with very large data sets collected via sensors. However, various important human factors, e.g. predictable and repeating behavior, have not yet been well understood and fully taken into consideration in the current generation CPS. This special issue describes significant research contributions in the domain of human interaction aware data analytics for CPS. This special issue consists of eight high quality research articles selected from 18 submissions that had covered a broad range of topics. The article "Catering to Your Concerns: Automatic Generation of Personalized Security centric Descriptions for Android Apps" develops an innovative scheme to help users avoid malware and privacy breaching apps by generating security descriptions that explain the privacyand security related aspects of an Android app in clear and understandable terms. Taking human activities and interactions with cyberphysical systems into consideration, the article "Improved LDA Dimension Reduction based Behavior Learning with Commodity WiFi for Cyber physical Systems" designs a human behaviorlearning system based on Channel State Information (CSI) utilizing a series of algorithms for data analysis and processing. To enable a sustainable edge computing paradigm while meeting the needs of home energy management and residents, the article "A Sustainable and User behavior aware Cyber physical System for Home Energy Management" introduces a cyberphysical system based energy management framework. A novel system for drone surveillance is presented in the article entitled "A Crowdsensing based Cyber physical System for Drone Surveillance Using Random Finite Set Theory" the proposed system utilizes surveillance data captured and sent from citizens' mobile devices to facilitate jointly drone detection and tracking. The article entitled "Energy efficient ECG Signal Compression for User Data Input in Cyber physical Systems by Leveraging Empirical Mode Decomposition" develops the first scheme of leveraging empirical mode decomposition (EMD) on ECG signals for sparse feature modeling and compression and further proposes a new ECG signal compression framework based on an EMD constructed feature dictionary. The article "Socially Aware Path Planning for a Flying Robot in Close Proximity of Humans" describes a motion planning framework in a cyber physical system that takes into account the human's safety perception in the presence
ACM Trans. Cyber Phys. Syst.