A data modeling conceptual framework for ubiquitous computing based on context awareness

Abstract

This paper introduces a framework for data modeling to support ubiquitous computing based on context-awareness. Data always grow in term of volume, variety, velocity, and value. The problem arises when it grows exponentially. Consequently, data is anywhere and requirements change in early data definitions then data design become not as the plan. Therefore, suitable approach with new paradigm and methods of data modeling needs to be enhanced to solve the problems in the real world. Data model must consider the active object that related to each other. Any objects may interact with each other in a ubiquitous way and recorded in digital technology. Sensors, actuator devices, and radio frequency identification technology may support communication between objects through ubiquitous computing. The data model in Ubiquitous Computing needs to restructure to become active and dynamic. Ubiquitous computing is a model that enable all objects around the people to communicate and invisible. In order to support this paradigm, a new perspective of how data are designed and stored on each object is needed. Furthermore, using ubiquitous computing, the pervasive network can request and response information, which means the devices may communicate and has the initiative to solve a problem without human intervention. Human wants more intelligence objects. Therefore, more sensors and memory are required. Data structures need to enhance or embedded into any devices that interact with the human.