Abstract
In recent years, with the rapid development of cloud computing, the massive storage capacity and massive computing power of cloud computing have brought new development opportunities to the security field. The traditional tourism professional multimedia teaching platform is also difficult to meet the current massive storage video. The demand for data, although there are work has been tried to deploy in the cloud environment, but a versatile platform is still an industry challenge. This paper designs and implements a cloud-based video surveillance platform based on the real-time, security, bandwidth dependence and high transmission cost of the multimedia professional teaching field. The cloud storage technology is used to solve the heterogeneity of video data. Use the cloud to solve the scalability of the platform. Then use H.264 video coding standard and RTSP video real-time transmission protocol to solve the problem of bandwidth dependence and real-time, and propose to build an embedded sensor network to carry out identity identification and centralized control separately. The network is dynamically tied to IP. The fixed video transmission method indirectly solves the instability of dynamic IP, and makes full use of FTTH resources, reducing the user cost.
Similar content being viewed by others
References
Al-Ayyoub M, Daraghmeh M, Jararweh Y et al. (2014) Multi-agent based dynamic resource provisioning and monitoring in cloud computing systems. International Ibm Cloud Academy Conference
Al-Janabi S, Al-Shourbaji I, Shojafar M et al. (2017) Mobile cloud computing:challenges and future research directions. The International Conference on the Developments on Esystems Engineering
Armbrust M, Fox A, Griffith R, Joseph AD, Katz R, Konwinski A, Lee G, Patterson D, Rabkin A, Stoica I, Zaharia M (2010) A view of cloud computing[J]. Commun ACM(4)
Assun??o MD, Calheiros RN, Bianchi S, Netto MAS, Buyya R (2014) Big Data computing and clouds: Trends and future directions[J] . Journal of parallel and distributed computing
Bono-Nuez A, Bernal-Ruíz C, Martín-del-Brío B et al (2017) Recipient size estimation for induction heating home appliances based on artificial neural networks. Neural Comput & Applic 28:3197. https://doi.org/10.1007/s00521-016-2227-6
Danenas P, Garsva G (2015) Selection of support vector machines based classifiers for credit risk domain[J]. Expert Syst Appl(6)
Do Q, Martini B, Choo K-KR (2018) Cyber-physical systems information gathering: a smart home case study. Comput Netw 138:1–12
Du Z, He L, Chen Y, Xiao Y, Gao P, Wang T (2016) Robot Cloud: Bridging the power of robotics and cloud computing[J]. Future Gen Comput Syst
Gubbi J, Buyya R, Marusic S, Palaniswami M 2013 Internet of things (IoT): A vision, architectural elements, and future directions[J]. Future Generation Computer Systems (7)
Guinard D, Trifa V, Karnouskos S (2010) Interacting with the SOA-Based Internet of Things: Discovery, Query, Selection, and On-Demand Provisioning of Web Services. IEEE Trans Serv Comput
Hao YJ, Yan C (2013) Design and implementation of Android contacts synchronization system based the Sync ML protocol. The 5th International Conference on Intelligent Networking and Collaborative Systems
Hashem IAT, Yaqoob I, Anuar NB, Mokhtar S, Gani A, Khan SU (2015) The rise of “big data” on cloud computing: Review and open research issues[J]. Inform Syst
Hosek J, Masek P, Kovac D, Ries M, Franz KRPFL (2014) IP home gateway as universal multi-purpose enabler for smart home services[J]. e & i Elektrotechnik und Informationstechnik(4–5)
Keramati A, Jafari-Marandi R, Aliannejadi M, Ahmadian I, Mozaffari M, Abbasi U (2014) Improved churn prediction in telecommunication industry using data mining techniques[J]. Appl Soft Comput J
Li J L, Li J P (2013) Data synchronization protocol in mobile computing environment using SyncML and Huffman coding. International conference on wavelet active media technology and information processing
Liouane Z, Lemlouma T, Roose P, Weis F, Messaoud H (2018) An improved extreme learning machine model for the prediction of human scenarios in smart homes. Appl Intell 48(8):2017–2030
Loukas A, Damopoulos D, Menesidou S, Skarkala M, Kambourakis G, Gritzalis S 2012 MILC: A secure and privacy-preserving mobile instant locator with chatting[J]. Inform Syst Front(3)
Patel A, Champaneria TA (2017) Fuzzy logic based algorithm for Context Awareness in IoT for Smart home environment. Region 10 Conference
Vafeiadis T, Diamantaras KI, Sarigiannidis G, Chatzisavvas KCH (2015) A comparison of machine learning techniques for customer churn prediction[J]. Simulation Modelling Practice and Theory
Vazquez JI, de Garibay JR, Renteria S, Ayerbe A (2010) Communication architectures and experiences for web-connected physical smart objects. Pervasive computing and communications workshops (PERCOM workshops)
Wang Y, Ma X, Lao Y, Wang Y (2014) A fuzzy-based customer clustering approach with hierarchical structure for logistics network optimization[J]. Expert Syst Appl(2)
Zhang M, Lehman V, Wang L (2017) Scalable name-based data synchronization for named data networking. INFOCOM 2017-IEEE conference on computer communications
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Nan, R., Zhang, H. Multimedia learning platform development and implementation based on cloud environment. Multimed Tools Appl 78, 35651–35664 (2019). https://doi.org/10.1007/s11042-019-08187-8
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-019-08187-8