Mobile cloud based-framework for sports applications

• Published in: Multidimensional systems and signal processing Vol. 30; no. 4; pp. 1991 - 2019
• Main Authors: Mahmood, Zahid, Bibi, Nargis, Usman, Muhammad, Khan, Uzair, Muhammad, Nazeer
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.10.2019; Springer Nature B.V
• Subjects: Artificial Intelligence; Batteries; Circuits and Systems; Cloud computing; Computer vision; Electrical Engineering; Energy consumption; Engineering; Machine learning; Mobile computing; Signal,Image and Speech Processing; Smartphones; Sports; Face recognition; Mobile cloud computing; Face detection
• ISSN: 0923-6082; 1573-0824
• DOI: 10.1007/s11045-019-00639-6

Smartphones are increasingly becoming popular due to the wide range of capabilities, such as Wi-Fi connectivity, video acquisition, and navigation. Some of these applications require large computational power, memory, and long battery life. Sports entertainment applications executed on smartphones is the future paradigm shift that will be enabled by the mobile cloud computing environments. Many times mobile users request multiple mobile services in workflows to fulfill their complex requirements. To investigate such issues, we develop a mobile cloud based framework that detects and retrieves player statistics on a mobile phone during live cricket. The proposed framework is divided into several services and each service is either executed locally or on the cloud. Our approach considers the dependencies among different services and aims to optimize the execution time and energy consumption for executing the services. Due to the applied offloading strategy, the proposed framework turns the smartphones smarter by significantly reducing the execution burden and energy consumption of the smartphone. Experimental results are promising and show feasibility of the proposed framework to be deployed in several related applications using techniques of computer vision and machine learning.