- Title
- A survey on big multimedia data processing and management in smart cities
- Creator
- Usman, Muhammad; Jan, Mian; He, Xiangjian; Chen, Jinjun
- Date
- 2019
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/185527
- Identifier
- vital:16721
- Identifier
-
https://doi.org/10.1145/3323334
- Identifier
- ISBN:0360-0300
- Abstract
- Integration of embedded multimedia devices with powerful computing platforms, e.g., machine learning platforms, helps to build smart cities and transforms the concept of Internet of Things into Internet of Multimedia Things (IoMT). To provide different services to the residents of smart cities, the IoMT technology generates big multimedia data. The management of big multimedia data is a challenging task for IoMT technology. Without proper management, it is hard to maintain consistency, reusability, and reconcilability of generated big multimedia data in smart cities. Various machine learning techniques can be used for automatic classification of raw multimedia data and to allow machines to learn features and perform specific tasks. In this survey, we focus on various machine learning platforms that can be used to process and manage big multimedia data generated by different applications in smart cities. We also highlight various limitations and research challenges that need to be considered when processing big multimedia data in real-time.
- Publisher
- Baltimore: ACM
- Relation
- ACM computing surveys Vol. 52, no. 3 (2019), p. 1-29
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright IEEE
- Subject
- Artificial intelligence; Data processing; Internet of Things; IoMT; Machine learning; Management; Multimedia; Platforms; Smart cities; 46 Information and computing sciences
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