![Open Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextgreen.png)
![Restricted Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextred.png)
![Open Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextgreen.png)
![Open Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltext_open_medium.gif)
![Restricted Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextred.png)
![Restricted Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltext_restricted_medium.gif)
Analysis and Study of Machine to Machine (Real Time Data Management)
Subscribe/Renew Journal
Machine to machine communication is a procedure in which two devices communicate data in order to achieve the desired output without the need for human intervention. Corporate processes may be enhanced, business assets can be managed more efficiently, and new revenue can be easily generated using this application. In everyday life, ATM customers confront issues such as the lack of guards, ATM thefts, lack of security, and ATMs without cameras, among others. Machine to machine communication is crucial, since it makes life easier by connecting mobile operating systems such as Android, iOS, and Windows to tracking devices, as well as employing fingerprint sensors with mobile devices. As a result, a real time GPS tracker knows how to send data to a mobile device. Individual users utilize this service to broadcast their current position to relatives and friends in real time. This service is used by businesses to manage their staff or to give a track and trace service to their customers as a bonus feature. The panic alarms generated during the process are handled with extreme caution and responsibility. Real time finger imprint is a leading producer of fingerprint core technology that tracks the finger and stores the data on the device. The machine-to-machine concept is gaining popularity. This utility will be released in the future, along with upgrades, and will set new security goals.
Keywords
Fingerprint sensors, Machine to machine communication, Mobile OS, Panic alert, Tracking and its usage.
Subscription
Login to verify subscription
User
Font Size
Information
- E. A. Lee, “Cyber physical systems: Design challenges,” in 11th IEEE Symposium on Object Oriented Real-Time Distributed Computing, 2008.
- T. Taleb, and A. Kunz, “Machine type communications in 3GPP networks: Potential, challenges, and solutions,” IEEE Communications Magazine, vol. 50, no. 3, pp. 178-184, 2012.
- K. Zheng, F. Hu, W. Wang, W. Xiang, and M. Dohler, “Radio resource allocation in LTE-advanced cellular networks with M2M communications,” IEEE Communications Magazine, vol. 50, no. 7, pp. 184-192, 2012.
- V. Sharma, U. Mukherji, V. Joseph, and S. Gupta, “Optimal energy management policies for energy harvest senor nodes,” IEEE Transaction on Wireless Communications, vol. 9, no. 4, pp. 1326-1336, 2010.
- K. C. Chen, “Machine-to-machine communications for healthcare,” Journal of Computing Science and Engineering, vol. 6, no. 2, 2012.
- C. Y. Ho, and C.-Y. Huang, “Energy-saving massive access control and resource allocation schemes for M2M communications in OFDMA cellular networks,” IEEE Communications Letters, vol. 1, no. 3, pp. 209-211, 2012.
- B. K. Gandhi, and M. K. Rao, “A prototype for IoT based car parking management system for smart cities,” Indian Journal of Science and Technology, vol. 9, no. 17, 2016.
- J. Kumar, S. Kumar, A. Kumar, and B. Behera, “Real-time monitoring security system integrated with Raspberry Pi and e-mail communication link,” in 2019 9th International Conference on Cloud Computing Data Science Engineering (Confluence), 2019, pp. 79-84.
- W. C. Ao, S. M. Cheng, and K. C. Chen, “Connectivity of multiple cooperative cognitive radio ad hoc networks,” IEEE Journal on Selected Areas in Communications, vol. 30, no. 2, pp. 263-270, 2012.
- S. M. Cheng, P. Y. Chen, and K. C. Chen, “Ecology of cognitive radio ad hoc networks,” IEEE Communications Letters, vol. 15, no. 7, pp. 764-766, 2011.
- P. Blasco, D. Gunduz, and M. Dohler, “A learning theoretic approach to energy harvesting communication system optimization,” in IEEE GLOBECOM, Workshop (IWM2MC), 2012.
- R. Y. Udaykumar, and S. Kumar, “IEEE 802.16-2004 (WiMAX) protocol for grid control center and aggregator communication in V2G for smart grid application,” IEEE International Conference on Computational Intelligence and Computing Research, 2013.
- J. B. Ekanayake, N. Jenkins, K. Liyanage, J. Wu, and A. Yokoyama, Smart Grid: Technology and Applications. John Wiley & Sons, Ltd., 2012.
- D. S. K. Nayak, P. Shreerudra, and J. Tripathy, “IoT ecosystems enable smart communication solutions: A case study,” 2022.
![](https://i-scholar.in/public/site/images/abstractview.png)
Abstract Views: 222
![](https://i-scholar.in/public/site/images/pdfview.png)
PDF Views: 0