REFERENCES

1. Zantalis F, Koulouras G, Karabetsos S, Kandris D. A review of machine learning and IoT in smart transportation. Future Internet 2019;11:94.

2. Singh D, Tripathi G, Jara AJ. A survey of Internet-of-Things: future vision, architecture, challenges and services. 2014 IEEE World Forum on Internet of Things (WF-IoT); 2014 Mar 6-8; Seoul, Korea (South). IEEE; 2014. p. 287-92.

3. Luan TH, Gao L, Li Z, Xiang Y, Sun L. Fog Computing: Focusing on Mobile Users at the Edge. Available from: https://arxiv.org/abs/1502.01815 [Last accessed on 28 Feb 2022].

4. Soltanmohammadi E, Ghavami K, Naraghi-pour M. A survey of traffic issues in machine-to-machine communications over LTE. IEEE Internet Things J 2016;3:865-84.

5. Soret B, Pedersen KI, Jørgensen NTK, Fernández-lópez V. Interference coordination for dense wireless networks. IEEE Commun Mag 2015;53:102-9.

6. Andrews JG. Seven ways that HetNets are a cellular paradigm shift. IEEE Commun Mag 2013;51:136-44.

7. Wu Q, Wu J, Shen J, Yong B, Zhou Q. An edge based multi-agent auto communication method for traffic light control. Sensors (Basel) 2020;20:4291.

8. Mohammed M, Khan MB, Bashier EBM. Machine learning: algorithms and applications. 1st ed. Boca Raton: CRC Press; 2016.

9. Kubat M. An introduction to machine learning. 3rd ed. Cham: Springer; 2017.

10. Omrani H. Predicting travel mode of individuals by machine learning. Transportation Research Procedia 2015;10:840-9.

11. Sang KS, Zhou B, Yang P, Yang Z. .

12. Yang J, Han Y, Wang Y, Jiang B, Lv Z, Song H. Optimization of real-time traffic network assignment based on IoT data using DBN and clustering model in smart city. Future Generation Computer Systems 2020;108:976-86.

13. Hou Y, Edara P, Sun C. Traffic flow forecasting for urban work zones. IEEE Trans Intell Transport Syst 2015;16:1761-70.

14. S.; Neetha, T. Machine learning based traffic congestion prediction in a IoT based Smart City. Int Res J Eng Technol 2017;4:3442-5.

15. Chang I, Tai H, Yeh F, Hsieh D, Chang S. A VANET-based A* route planning algorithm for travelling time- and energy-efficient GPS navigation app. Int J Distrib Sens Netw 2013;9:794521.

16. Hefnawy A, Bouras A, Cherifi C. .

17. Amato G, Carrara F, Falchi F, Gennaro C, Meghini C, Vairo C. Deep learning for decentralized parking lot occupancy detection. Expert Syst Appl 2017;72:327-34.

18. Wu Q, Huang C, Wang SY, Chiu WC, Chen T. .

19. Gupta A, Kulkarni S, Jathar V, Sharma V, Jain N. Smart car parking management system using IoT. American Journal of Science, Engineering and Technology 2017;2:112-9.

20. Aydin I, Karakose M, Karakose E. A navigation and reservation based smart parking platform using genetic optimization for smart cities. 2017 5th International Istanbul Smart Grid and Cities Congress and Fair (ICSG); 2017 Apr 19-21; Istanbul, Turkey. IEEE; 2017. p. 120-4.

21. Arjona J, Linares, MP, Casanovas J. .

22. Jia G, Han G, Li A, Du J. SSL: smart street lamp based on fog computing for smarter cities. IEEE Trans Ind Inf 2018;14:4995-5004.

23. Kokilavani M, Malathi A. Smart street lighting system using IoT. Int J Adv Res Appl Sci Technol 2017;3:8-11.

24. Tripathy AK, Mishra AK, Das TK. .

25. Liu W, Kim S, Marczuk K, Ang MH. .

26. Ozbayoglu M, Kucukayan G, Dogdu E. .

27. Kwon D, Park S, Baek S, Malaiya RK, Yoon G, Ryu J. .

28. Ryder B, Wortmann Felix. .

29. Celesti A, Galletta A, Carnevale L, Fazio M, Lay-ekuakille A, Villari M. An IoT cloud system for traffic monitoring and vehicular accidents prevention based on mobile sensor data processing. IEEE Sensors J 2018;18:4795-802.

30. Kulkarni A, Mhalgi N, Gurnani S, Giri N. Pothole detection system using machine learning on Android. Int J Emerg Technol Adv Eng 2014;4:360-4.

31. Gopalakrishnan K. Deep learning in data-driven pavement image analysis and automated distress detection: a review. Data 2018;3:28.

32. Collotta M, Pau G, Talty T, Tonguz OK. Bluetooth 5: a concrete step forward toward the IoT. IEEE Commun Mag 2018;56:125-31.

33. Giliberto M, Arena F, Pau G. A fuzzy-based solution for optimized management of energy consumption in e-bikes. J Wirel Mob Netw Ubiquitous Comput Dependable Appl 2019;10:45-64.

34. Bacciu D, Carta A, Gnesi S, Semini L. An experience in using machine learning for short-term predictions in smart transportation systems. Journal of Logical and Algebraic Methods in Programming 2017;87:52-66.

35. Chowdhury DN, Agarwal N, Laha AB, Mukherjee A. .

36. Geetha S, Cicilia D. .

37. Sarrab M, Pulparambil S, Awadalla M. Development of an IoT based real-time traffic monitoring system for city governance. Global Transitions 2020;2:230-45.

Journal of Smart Environments and Green Computing
ISSN 2767-6595 (Online)
Follow Us

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/