2015/07/06 by Rakhi Gupta, Rakhi Misuriya Gupta, Gupta, Rakhi Misuriya
Computer Science · #Computers and Society (cs.CY) #Context-Aware Activity Recognition Systems #Energy Efficient Wireless Sensor Networks #FOS: Computer and information sciences #IoT and Edge/Fog Computing #cs.CY
paper · pdf · doi:10.48550/arxiv.1507.01368
9 pages, 2 figures
arxiv created 2015/07/06 · openalex publication_date 2015/07/06 · arxiv updated 2015/07/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.