An Overview of Cellular Network as A Sensor: From Mobile Phones Data to Real-time Road Traffic Monitoring

Parmeshwar Kumawat

doi:10.55524/ijircst.2020.8.4.24

Abstract

Versatile cell organizations might go about as pervasive actual portability sensors. Dependent just upon anonymized flagging information assembled from a versatile cell organization, we present a procedure for surmising vehicle trip terms on interstates and identifying gridlock continuously. Most earlier examinations utilized information from cell phones that were occupied with calls, like Call Detail Records (CDR), which limits the number of apparent gadgets to a minuscule level of the absolute populace. By utilizing the entire assortment of flagging occasions created by both inactive and dynamic gadgets, we can beat this defect. Dynamic gadgets offer better grained geographic accuracy for a little part of gadgets, while inactive gadgets give a colossal measure of spatially coarse-grained portability information. Blockage recognition execution is worked on as far as inclusion, exactness, and idealness by joining information from inactive and dynamic gadgets. People test our technique on genuine portable flagging information from a functional organization north of one month on an example parkway section close to a European city and present an extensive approval review because of ground truth got from an assorted arrangement of reference information sources, including street sensor information, cost information, taxi drifting vehicle information, and radio station messages.

Keywords

Cellular Network, Congestion Detection, Mobility, Traffic Monitoring, Travel Time Estimation.

References

M. Ramon, F. Rolland, and J. Sheen, “Sugar Sensing and Signaling,” Arab. B., 2008, doi: 10.1199/tab.0117.
O. Kaiwartya et al., “Internet of Vehicles: Motivation, Layered Architecture, Network Model, Challenges, and Future Aspects,” IEEE Access, 2016, doi: 10.1109/ACCESS.2016.2603219.
E. Soltanmohammadi, K. Ghavami, and M. Naraghi-Pour, “A Survey of Traffic Issues in Machine-To-Machine Communications over LTE,” IEEE Internet of Things Journal. 2016, doi: 10.1109/JIOT.2016.2533541.
for diabetes monitoring,” Asian J. Pharm. Clin. Res., 2014.
V. Mishra et al., “Fiber Bragg grating sensor for monitoring bone decalcification,” Orthop. Traumatol. Surg. Res., 2010, doi: 10.1016/j.otsr.2010.04.010.
S. Garg, D. V. Gupta, and R. K. Dwivedi, “Enhanced Active Monitoring Load Balancing algorithm for Virtual Machines in cloud computing,” 2017, doi: 10.1109/SYSMART.2016.7894546.
K. L. A. Yau, P. Komisarczuk, and P. D. Teal, “Reinforcement learning for context awareness and intelligence in wireless networks: Review, new features and open issues,” Journal of Network and Computer Applications. 2012, doi: 10.1016/j.jnca.2011.08.007.
S. Tripathi, P. K. Verma, and G. Goswami, “A review on SMART GRID power system network,” 2020, doi: 10.1109/SMART50582.2020.9337067.
B. Gupta, K. K. Gola, and M. Dhingra, “Wireless Sensor Networks: ‘A Review on Replica Detection Techniques,’” 2020, doi: 10.1109/SMART46866.2019.9117544.
M. Conacci-Sorrell, L. McFerrin, and R. N. Eisenman, “An overview of MYC and its interactome,” Cold Spring Harb. Perspect. Med., 2014, doi: 10.1101/cshperspect.a014357.
W. Sun, M. Choi, and S. Choi, “IEEE 802.11ah: A Long Range 802.11 WLAN at Sub 1 GHz,” J. ICT Stand., 2013, doi: 10.13052/jicts2245-800x.125.
S. M. Mian and R. Kumar, “Review on Intend Adaptive Algorithms for Time Critical Applications in Underwater Wireless Sensor Auditory and Multipath Network,” 2019, doi: 10.1109/ICACTM.2019.8776782.
M. Tahira, D. Ather, and A. K. Saxena, “Modeling and evaluation of heterogeneous networks for VANETs,” 2018, doi: 10.1109/SYSMART.2018.8746981.
V. Saxena, D. Rastogi, and R. Kumar, “Challenge in route discovery process of dynamically arranged multitier Protocol in wireless network,” 2017, doi: 10.1109/SYSMART.2016.7894514.
I. Martin et al., “A high-resolution sensor network for monitoring glacier dynamics,” IEEE Sens. J., 2014, doi: 10.1109/JSEN.2014.2348534.
Aniruddha A Pore and Shefali P Sonavane, “A Survey on Cellular Automata based WSN Models,” Int. J. Eng. Res., 2016, doi: 10.17577/ijertv5is020578.
S. Gupta and G. Khan, “MHCDA: A proposal for data collection in Wireless Sensor Network,” 2017, doi: 10.1109/SYSMART.2016.7894517.
P. Gupta, V. Prakash, and P. Suman, “Noticeable key points and issues of sensor deployment for large area Wireless Sensor Network: A survey,” 2017, doi: 10.1109/SYSMART.2016.7894511.
R. Atat, “Enabling Cyber-Physical Communication in 5G Cellular Networks: Challenges, Solutions and Applications,” 2017.
S. K. Sharma, A. Jain, K. Gupta, D. Prasad, and V. Singh, “An internal schematic view and simulation of major diagonal mesh network-on-chip,” J. Comput. Theor. Nanosci., 2019, doi: 10.1166/jctn.2019.8534.
M. Yadav, S. K. Gupta, and R. K. Saket, “Multi-hop wireless ad-hoc network routing protocols- a comparative study of DSDV, TORA, DSR and AODV,” 2015, doi: 10.1109/EESCO.2015.7253703.
N. Agrawal, A. Jain, and A. Agarwal, “Simulation of network on chip for 3D router architecture,” Int. J. Recent Technol. Eng., 2019.
K. K. Gola, B. Gupta, and G. Khan, “Underwater sensor networks: A heuristic approach for void avoidance and selection of best forwarder,” Int. J. Sci. Technol. Res., 2019.
M. Mehdi, D. Ather, M. Rababah, and M. K. Sharma, “Problems issues in the information security due to the manual mistakes,” 2016.

Cites this article as

P. Kumawat "An Overview of Cellular Network as A Sensor: From Mobile Phones Data to Real-time Road Traffic Monitoring", International Journal of Innovative Research in Engineering & Management (ijircst), Vol-8, Issue-4, Page No-372-375, 2020. Available from: https://doi.org/10.55524/ijircst.2020.8.4.24

Corresponding Author

Parmeshwar Kumawat

Assistant Professor, Department of Electrical Engineering, Vivekananda, Global University, Jaipur, India

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