Cloud Based Architecture for Enabling Intuitive Decision Making

Abstract

To address the current need of innovative technologies that blend rapid data processing capabilities of computers with intuitive decision making skills of humans, we have developed a prototype of Cloud Enabled Brain Computer Interface (CEB) decision making technologies. The implemented architecture integrates cloud enabled big data analytics capabilities, networked BCI (Brain Computer Interface) devices, and Decision Making Engine. The novel CEB technology comprises of 1. Cloud-enabled BCI (Brain-Computer Interface) headsets, which is developed and networked in a cloud to enable rapid decision making and 2. Genetic algorithm based decision making engine, to intelligently assist the users in decision making; Advantage of our architecture is that when CEB loads the data, it will automatically recommend the best applicable Machine Learning (ML) algorithms after being evaluated to solve a given problem. Hence, with such automated machine learning techniques, CEB users workload is significantly reduced. Our experiments on DARPA dataset indicate that CEB technologies performed 10 times faster and about 4 times less false negative rate than current computational methods in seeking and understanding information. Our results demonstrate that these CEB technologies would enable humans to accurately and quickly detect meaningful information from a mass amount of data. The novel CEB technologies ensure that the reduced manpower does not result in reduced performance.