The Development and Deployment of a Cloud-Based Intelligent Monitoring System
Abstract
The use of cloud computing has positive results for businesses. Several companies now utilise it because of how well it makes money and how easily it can be expanded. In addition, its heightened security and privacy make it a worthy choice for business owners and financiers (Yong, et al., 2012). The cloud has the potential to greatly reduce costs for small companies. With the help of cloud computing, sharing and cooperation across industries has become more efficient and less expensive. Having a "pay as you go" method is beneficial to users. Cloud computing not only allows for more swiftness in business dealings, but also more versatility in staffing and resource scheduling.
In comparison to buying a server outright, "pay as you go" saves money and reduces waste (Kambatala, et al., 2014). While the "total cost" of hardware continues to decrease, the prices of cloud computing and cloud storage are decreasing at a faster rate. " A cloud-based system makes it less of a hassle to keep tabs on progress and inform customers of any shifts. Therefore, it is consistent with the allocation of funds and the utilisation of resources.
There is now "any corporation has access to its own services through the internet" thanks to the development of cloud computing (Armbrust, et al., 2009). A projected 33.2% of 2016 worldwide IT budgets will go toward cloud-based services. Various integrated cloud-based technologies are used in the "real world" of corporations nowadays (Devasena, 2014).
Keywords
Cloud-Based Services, Cloud Computing, Real World OperationsHow to Cite
References
Agarwal, D., & Prasad, S. K. (2012, May). Azure bench: Benchmarking the storage services of the Azure Cloud Platform. In Parallel and Distributed Processing Symposium Workshops & PhD Forum (IPDPSW), pp. 1048-1057.
Aguilar, J. M. (2014). SignalR programming in Microsoft ASP. NET. Microsoft Press. Alamri, A., Hossain, M. S., Almogren, A., Hassan, M. M., Alnafjan, K., Zakariah, M., &
Alghamdi, A. (2015). QoS-adaptive service configuration framework for cloud- assisted video surveillance systems. Multimedia Tools and Applications, pp. 1-16.
Aleem. A. & Sprott. C.R. (2013). Let me in the cloud: analysis of the benefit and riskassessment of cloud platform. Journal of Financial Crime, pp. 6-24.
Anghelescu, P., Serbanescu, I., & Ionita, S. (2013, June). Surveillance system using IP camera and face-detection algorithm. In Electronics, Computers and Artificial Intelligence (ECAI), pp. 1-6.
Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R. H., Konwinski, A., & Zaharia,M. (2009). Above the clouds: A berkeley view of cloud computing.
Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R., Konwinski, A., & Zaharia,M. (2010). A view of cloud computing. Communications of the ACM, pp. 50-58.
BaoHong.Y & Yan. W (2015). Investigation on application of video monitoring. Chinabuilding materials science and technology 2015, Vol.1. pp.153-154.
Begum, S., & Khan, M. K. (2011, July). Potential of cloud computing architecture. In Information and Communication Technologies (ICICT), pp. 1-5.
Behl, A., & Behl, K. (2012, October). An analysis of cloud computing security issues. In Information and Communication Technologies (WICT), pp. 109-114.
Beyer. J., Elhrouz. H.& El Seed. K. (2012). Streamlining test and evaluation with cloud computing. Digital Avionics Systems Conference, pp.9E3-1-9E3-6
Boehm, B., & Hansen, W. J. (2000). SPECIAL REPORT CMU/SEI-2000-SR-008.
Bogardi-Meszoly, A., Levendovszky, T., & Charaf, H. (2006). Performance Factors in ASP. NET Web Applications with Limited Queue Models. In 2006 International Conference on Intelligent Engineering Systems, pp. 253-257.
Chang, A. Y., Parrales, M. E., Jimenez, J., Sobieszczyk, M. E., Hammer, S. M., Copenhaver, D. J., & Kulkarni, R. P. (2009). Combining Google Earth and GIS mapping technologies in a dengue surveillance system for developing countries. International Journal of health geographics, 8(1), p.1.
Chen, L., Shashidhar, N., & Liu, Q. (2012, March). Scalable secure MJPG video streaming. In Advanced Information Networking and Applications Workshops (WAINA), pp. 111-115.
Chen, T. S., Lin, M. F., Chieuh, T. C., Chang, C. H., & Tai, W. H. (2015, September). An intelligent surveillance video analysis service in cloud environment. In Security Technology (ICCST), pp. 1-6.
Chen, W. T., Chen, P. Y., Lee, W. S., & Huang, C. F. (2008, May). Design and implementation of a real time video surveillance system with wireless sensor networks. In Vehicular Technology Conference, 2008, pp. 218-222.
Frank H. (2011). Cloud Computing for syndromic surveillance. Emerging Health Threats Journal, 4(0):71-71.
Gandomi, A. & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2): 137–144.
Goyal, S. (2014). Public vs private vs hybrid vs community-cloud computing: A critical review. International Journal of Computer Network and Information Security, 6(3), p.20.
Halili, E. H. (2008). Apache JMeter: A practical beginner's guide to automated testingand performance measurement for your websites. Packt Publishing Ltd.
Hassan, M. M., Hossain, M. A., Abdullah-Al-Wadud, M., Al-Mudaihesh, T., Alyahya, S., & Alghamdi, A. (2015). A scalable and elastic cloud-assisted publish/subscribe model for IPTV video surveillance system. Cluster Computing, 18(4):1539-1548.
Hossain, M. A. (2014). Framework for a cloud-based multimedia surveillance system.International Journal of Distributed Sensor Networks.
Hossain, M. A. (2013, November). Analyzing the suitability of cloud-based multimedia surveillance systems. In High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing (HPCC_EUC), pp. 644-650.
Kim, S., Nam, Y., Kim, J., & Cho, W. D. (2009, December). ISS: intelligent surveillance system using autonomous multiple cameras. In Ubiquitous Information Technologies & Applications, 2009. ICUT'09, pp. 1-6.
Lage, R., Dolog, P., & Leginus, M. (2014, July). The role of adaptive elements in web- based surveillance system user interfaces. In International Conference on User Modeling, Adaptation, and Personalization, pp. 350-362.
Lamy-Bergot, C., Renan, E., Gadat, B. & Lavaux, D. (2009). Data supervision for adaptively transcoded Data supervision for adaptively transcoded. Proceedings of the IEEE ITST'09, pp. 415-419.
Li. Q & Zhang. T & Yu. Y (2011). Using cloud computing to process intensive floating car data for urban traffic surveillance. International Journal of Geographical Information Science, 25(8): 1303-1322.
Prati, A., Vezzani, R., Fornaciari, M., & Cucchiara, R. (2013). Intelligent video surveillance as a service. In Intelligent Multimedia Surveillance, pp. 1-16.
Qi, W. A. N. G., & Yu, Z. H. U. (2006). Design and Implementation of Digital Video Surveillance System Based on B/S Structure. Computer Engineering, 19, 089.
Qian, L., Luo, Z., Du, Y., & Guo, L. (2009, December). Cloud computing: an overview.In IEEE International Conference on Cloud Computing, pp. 626-631.
Renkis, Martin (2013). Bandwidth. Storage. Speed for cloud surveillance. Security Systems News. Vol.16(5). p.16.
Song, B., Hassan, M. M., Tian, Y., Hossain, M. S., & Alamri, A. (2015). Remote display solution for video surveillance in multimedia cloud. Multimedia Tools and Applications, pp.1-22.
Woo, S. W., Joh, H., Alhazmi, O. H., & Malaiya, Y. K. (2011). Modeling vulnerability discovery process in Apache and IIS HTTP servers. Computers & Security, 30(1):50-62.
Xiong, Y., Wan, S., She, J., Wu, M., He, Y., & Jiang, K. (2016). An energy-optimization- based method of task scheduling for a cloud video surveillance center. Journal of Network and Computer Applications, 59: 63-73.
Zhang, H., Li, M., Chen, Z., Bao, Z., Huang, Q., & Cai, D. (2010, June). Land use information release system based on Google Maps API and XML. In 2010 18th International Conference on Geoinformatics, pp. 1-4.
Zhao, Z. F., Cui, X. J., & Zhang, H. Q. (2012). Cloud storage technology in video surveillance. In Advanced Materials Research, 532: 1334-1338.
License
Copyright (c) 2024 LI MIN, DR. MIDHUNCHAKKARAVARTHY
This work is licensed under a Creative Commons Attribution 4.0 International License.
Individual articles are published Open Access under the Creative Commons Licence: CC-BY 4.0.
