Intelligent Data in the context of the internet-of-things

TL;DR

This paper presents a flexible framework for managing diverse IoT sensor data, enabling real-time analytics and intelligent applications to optimize resource use and create innovative IoT solutions.

Contribution

It introduces a novel framework that addresses data diversity and supports real-time analytics for IoT, facilitating smarter decision-making and application development.

Findings

Framework effectively manages diverse sensor data

Supports real-time analytics and event response

Enables new IoT applications and business models

Abstract

Advent of the Internet-of-Things will allow us to optimize equipment and resource usage, enabling increased efficiencies in automation and enabling new and more cost efficient business model. As tremendous growth opportunities emerge, so do the challenges such as diverse devices spanning across multiple networks, the need to manage the exponential growth of sensor generated data and to make sense of the huge influx of data in meaningful ways. The multitude of diversity can best be addressed by fundamentally opening up systems, architecture and applications. To go the next step and truly exploit the value of the sensor data would further require real-time analytics to gain intelligence and respond to events as they happen. Historical analysis can be used to look for trends, analyze collections of sensor data for correlation and formulate hints and suggestions based on usage and patterns. In this paper, we present a framework that overcomes diversity through its ability to flexibly represent sensor data on the internet. Business goals-driven information processing, information derived intelligence and information control as elements of the framework can further enable creation of new and innovative applications that enhance and exploit the value of Internet-of-Things.