Big Data Meet Green Challenges: Big Data Toward Green Applications

• Published in: IEEE systems journal Vol. 10; no. 3; pp. 888 - 900
• Main Authors: Wu, Jinsong, Guo, Song, Li, Jie, Zeng, Deze
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-09-2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Air pollution; Big data; Correlation analysis; data analytics; Data management; Data mining; energy efficiency; environmental issues; environmental sustainability; green; Green aspects; Green products; green revolution; Innovation; Literature reviews; Meteorology; Monitoring; Productivity; recyclability; renewable resource; resource efficiency; sustainability; sustainability applications; sustainable environments; Trends; Water pollution
• ISSN: 1932-8184; 1937-9234
• DOI: 10.1109/JSYST.2016.2550530

Big data are widely recognized as being one of the most powerful drivers to promote productivity, improve efficiency, and support innovation. It is highly expected to explore the power of big data and turn big data into big values. To answer the interesting question whether there are inherent correlations between the two tendencies of big data and green challenges, a recent study has investigated the issues on greening the whole life cycle of big data systems. This paper would like to discover the relations between the trend of big data era and that of the new generation green revolution through a comprehensive and panoramic literature survey in big data technologies toward various green objectives and a discussion on relevant challenges and future directions.