An intelligent cloud-based data processing broker for mobile e-health multimedia applications.

Mobile e-health applications provide users and healthcare practitioners with an insightful way to check users/patients’ status and monitor their daily calorie intake. Mobile e-health applications provide users and healthcare practitioners with an insightful way to check users/patients’ status and monitor their daily activities. This paper proposes a cloud-based mobile e-health calorie system that can classify food objects in the plate and further compute the overall calorie of each food object with high accuracy. The novelty in our system is that we are not only offloading heavy computational functions of the system to the cloud, but also employing an intelligent cloud-broker mechanism to strategically and efficiently utilize cloud instances to provide accurate and improved time response results. The broker system uses a dynamic cloud allocation mechanism that takes decisions on allocating and de-allocating cloud instances in real-time for ensuring the average response time stays within a predefined threshold. In this paper, we further demonstrate various scenarios to explain the workflow of the cloud components including: segmentation, deep learning, indexing food images, decision making algorithms, calorie computation, scheduling management as part of the proposed cloud broker model. The implementation results of our system showed that the proposed cloud broker results in a 45% gain in the overall time taken to process the images in the cloud. With the use of dynamic cloud allocation mechanism, we were able to reduce the average time consumption by 77.21% when 60 images were processed in parallel.