SI:Cont-IoT 2019 : Context-aware Computing for the Internet of Things: Trends and Challenges
Call For Papers
Internet of Things; Engineering Cyber Physical Human Systems invites manuscript submission in the area of Context-aware Computing for the Internet of Things
We’re currently shifting from the Information Age to the Intelligence Age. The Intelligence Age will be characterized by autonomous communication between intelligent devices that are sensitive to a person’s presence and respond by performing a specific task that enhances that person’s lifestyle.
In this perspective, the Internet of Things envisages a plethora of heterogeneous objects interacting with people, with other objects and the physical environment.
Thingsare able to sense a user’s presence, movement and behavior, analyze that data in order to learn about that user, and then make an intelligent decision to perform a task based on the data.
Collection, modelling, reasoning, and distribution of context in relation to IoT sensor data plays critical role in this challenge and context-aware computing has proven to be successful in understanding sensor data.
Context-aware Computing for the Internet of Things paradigm is a very challenging research area and there is generally a deficiency to understand the suitable approaches to support this field.
The success of IoT systems and applications depends on the efficient integration of its devices, sensors and data management techniques.
This special issue will bring together researchers from diverse fields and specializations, such as communications engineering, computer science, electrical and electronics engineering, educators, mathematicians and specialists in areas related to Context-aware Computing for the Internet of Things.
Topics of interest include, but not limited to the following:
● Context-aware models for IoT;
● Context-aware algorithms for IoT;
● Context-aware networks for IoT;
● Context-aware computing for Ambient intellitenge;
● IoT on eHealth/mHealth and Ambient Assisted Living
● Environmental intelligent sensing and mobile computing;
● Ambient context modeling and reasoning;
● Smart environments and related applications;
● Contextual Data Classification and management on IoT environments;
● Context-aware applications for the Internet of Things
● Social Big Data and Data Mining techniques;
● Context-aware reasoning for Real-time intelligence;
● Algorithms for Big Data analytics and data mining on IoT environments;
● Ambient intelligence techniques applied to Cultural Heritage domain;
● IoT architecture, tools and applications for Data analysis;
Francesco Piccialli (lead), University of Naples “Federico II”, Italy
Department of Electrical Engineering and Information Technology
Gwanggil Jeon, Incheon National University, South Korea
Department of Embedded Systems Engineering