IoT-based Hybrid Wireless Network for Tourist Boat Tracking towards Smart Cities
Keywords:environment monitoring, hybrid wireless networks, LoRa, tourist boat, Zigbee
Moving and transporting by canoe and boat on rivers and canals is a cultural feature of the Mekong Delta and plays an important role in the economy and society. However, the management and use of equipment to support the monitoring of waterway transport vehicles in this area has yet to receive adequate investment and attention. Given the complicated evolution of the COVID-19 epidemic, it is critical to strengthen oversight of inland waterway management, as well as freight and passenger transportation. This paper presents the design and implementation of an IoT-based support system for managing and monitoring passenger ships and tourism activities in smart cities. This study proposes a hybrid wireless communication network solution that takes advantage of the strengths of LoRa and Zigbee wireless communication technologies, as well as telecommunication networks, to ensure that the system has a wide operating range of several kilometers, low power consumption, and can be deployed in areas where telecommunications are not available. Aside from tracking the journey and managing information about vehicles, drivers, and passengers, the system also aids in the collection of environmental parameters along river routes according to the travel route. An experimental evaluation of the system's operation was carried out for the tourist boat route between two famous tourist sites, Ninh Kieu Key and Cai Rang floating market in Can Tho city, Vietnam.
Gonzalez N, Van Den Bossche A, Val T. Hybrid wireless protocols for the Internet of Things. The 5th International Conference on Performance Evaluation and Modeling in Wired and Wireless Networks (PEMWN); 22-25 November 2016; Paris, France. IEEE Xplore; 2017. p. 1-4 DOI: https://doi.org/10.1109/PEMWN.2016.7842895
Zhou W, Tong Z, Dong ZY, Wang Y. Lora-hybrid: A LoRaWAN based multihop solution for regional microgrid. IEEE 4th International Conference on Computer and Communication Systems (ICCCS); 23-25 February 2019; Singapore. IEEE Xplore; 2019. p. 650-654 DOI: https://doi.org/10.1109/CCOMS.2019.8821683
Sant’Ana JMDS, Hoeller A, Souza RD, Montejo-Sanchez S, Alves H, Noronha-Neto M De. Hybrid Coded Replication in LoRa Networks. IEEE Trans Ind Informatics. 2020;16(8):5577–85.
Cilfone A, Davoli L, Belli L, Ferrari G. Wireless mesh networking: An IoT-oriented perspective survey on relevant technologies. Futur Internet. 2019;11(4). DOI: https://doi.org/10.3390/fi11040099
Chang RS, Chen WY, Wen YF. Hybrid wireless network protocols. IEEE Trans Veh Technol. 2003;52(4):1099–109. Sant’Ana JMDS, Hoeller A, Souza RD, Montejo-Sanchez S, Alves H, Noronha-Neto M De. Hybrid Coded Replication in LoRa Networks. IEEE Trans Ind Informatics. 2020;16(8):5577–85. DOI: https://doi.org/10.1109/TII.2020.2966120
Verma A, Shukla V. Analyzing the Influence of IoT in Tourism Industry. SSRN Electron J. 2019;2083–93.
Guo X, Wang Y, Mao J, Deng Y, Chan FTS, Ruan J. Towards an IoT enabled Tourism and Visualization Review on the Relevant Literature in Recent 10 Years. Mob Networks Appl. 2022;27(3):886–99. DOI: https://doi.org/10.1007/s11036-021-01813-6
Verma A, Shukla V. Analyzing the Influence of IoT in Tourism Industry. SSRN Electron J. 2019;2083–93. DOI: https://doi.org/10.2139/ssrn.3358168
Tripathy AK, Tripathy PK, Ray NK, Mohanty SP. iTour: The Future of Smart Tourism. IEEE Consum Electron Mag. 2018;7(3):32–7. DOI: https://doi.org/10.1109/MCE.2018.2797758
Rusdi JF, Salam S, Abu NA, Sahib S, Naseer M, Abdullah AA. Drone Tracking Modelling Ontology for Tourist Behavior. J Phys Conf Ser. 2019;1201(1).
Sudiartha IKG, Indrayana INE, Suasnawa IW, Asri SA, Sunu PW. Data Structure Comparison between MySql Relational Database and Firebase Database NoSql on Mobile Based Tourist Tracking Application. J Phys Conf Ser. 2020;1569(3). DOI: https://doi.org/10.1088/1742-6596/1569/3/032092
Nguyen Duc Nhuan, Nguyen Hoang Phuong. Industry and trade magazine, Vietnam. 2022. Issues for river economic development in the Mekong Delta. https://tapchicongthuong.vn/bai-viet/nhung-van-de-dat-ra-cho-phat-trien-kinh-te-duong-song-o-dong-bang-song-cuu-long-89211.htm
The electronic information page of Tra Vinh Police, Vietnam. 2018. Developing inland waterway transport in the Mekong Delta region, contributing to regional economic growth and ensuring social order. http://congan.travinh.gov.vn/ch26/265-Phat-trien-giao-thong-duong-thuy-noi-dia-khu-vuc-Dong-bang-song-Cuu-Long-gop-phan-tang-truong-kinh-te-vung-va-bao-dam-trat-tu-xa-hoi.html
Trong Duy, Nhan Dan Newspaper. 2019. Visitors to the Mekong Delta are estimated at 47 million in 2019. https://nhandan.vn/nam-2019-du-khach-den-dong-bang-song-cuu-long-uoc-dat-47-trieu-luot-post380077.html
Pooja G, Sundar R, Harshini R, Arjuna S, Ram Kumar C. Recent Trends and Challenges in Smart Cities. EAI Endorsed Trans Smart Cities [Internet]. 2022 Sep. 27 [cited 2023 Feb. 10];6(3):e4. Available from: https://publications.eai.eu/index.php/sc/article/view/2273 DOI: https://doi.org/10.4108/eetsc.v6i3.2273
de Camargo ET, Spanhol FA, Castro e Souza ÁR. Deployment of a LoRaWAN network and evaluation of tracking devices in the context of smart cities. J Internet Serv Appl [Internet]. 2021;12(1):8. Available from: https://doi.org/10.1186/s13174-021-00138-7 DOI: https://doi.org/10.1186/s13174-021-00138-7
Ramli N, Zabidi MM, Ahmad A, Musliman IA. An open source LoRa based vehicle tracking system. Indones J Electr Eng Informatics. 2019 Jun 1;7(2):221–8. DOI: https://doi.org/10.11591/ijeei.v7i2.1174
Sheu BH, Yang TC, Yang TM, Huang CI, Chen WP. Real-time Alarm, Dynamic GPS Tracking, and Monitoring System for Man Overboard. Sensors Mater. 2020;32(1):197–221. DOI: https://doi.org/10.18494/SAM.2020.2582
Liya ML, Aswathy M. LoRa technology for Internet of Things(IoT):A brief Survey. In: Proceedings of the 4th International Conference on IoT in Social, Mobile, Analytics and Cloud, ISMAC 2020. Institute of Electrical and Electronics Engineers Inc.; 2020. p. 128–33.
Belka R, Deniziak RS, Łukawski G, Pięta P. BLE-based indoor tracking system with overlapping-resistant IoT solution for tourism applications. Sensors (Switzerland). 2021;21(2):1–21. DOI: https://doi.org/10.3390/s21020329
Marques CP, Guedes AS, Bento R. Tracking changes in tourism demand with point-of-sale data: The case of Portugal. Tour Hosp Res. 2023;23(1):101–7. DOI: https://doi.org/10.1177/14673584221075175
Chauhan H, Kumar D, Gupta D, Gupta S, Verma V. Blockchain and IoT based vehicle tracking system for industry 4.0 applications. IOP Conf Ser Mater Sci Eng. 2021;1022(1):0–9. DOI: https://doi.org/10.1088/1757-899X/1022/1/012051
Robinson AR, Esty M, Tilburg CE. A Compact GPS Surface Drifter with LoRa Telemetry and Self-Contained Tracking System.
Sanchez-Iborra R, G. Liaño I, Simoes C, et al. Tracking and monitoring system based on LoRa technology for lightweight boats. Electronics, 2018, 8(1): 15. Ramli N, Mun’im Zabidi M, Ahmad A, et al. An open source LoRa based vehicle tracking system. Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 2019, 7(2): 221-228 DOI: https://doi.org/10.52549/ijeei.v7i2.1174
Rusdi JF, Salam S, Abu NA, Sahib S, Naseer M, Abdullah AA. Drone Tracking Modelling Ontology for Tourist Behavior. J Phys Conf Ser. 2019;1201(1). DOI: https://doi.org/10.1088/1742-6596/1201/1/012032
Sreeram Charan N, Maheshwar Reddy K, Rakesh Reddy E, Malarvizhi N. Design and Development of a Rendering System for Vehicle Riding. EAI Endorsed Trans Smart Cities [Internet]. 2022 Mar. 29 [cited 2023 Feb. 10];6(17):e4. Available from: https://publications.eai.eu/index.php/sc/article/view/161 DOI: https://doi.org/10.4108/eetsc.v6i17.161
Woo-García RM, Herrera-Nevraumont V, Osorio-de-la-Rosa E, SVázquez-Valdés SE, López-Huerta F. Location monitoring system for sailboats by GPS using GSM/GPRS technology. IEEE Embed Syst Lett. 2022;1. DOI: https://doi.org/10.1109/LES.2022.3188935
Ghosh R, Kumar S. Mobile health applications during epidemic management in India: a review. EAI Endorsed Trans Smart Cities [Internet]. 2020 Oct. 5 [cited 2023 Feb. 10];5(13):e1. Available from: https://publications.eai.eu/index.php/sc/article/view/1114
Oliveti M, van der Spek S. Evaluating urban neighbourhoods in terms of mobility performances, using open data and GPS tracks to assess actual people travel behaviour. EAI Endorsed Trans Smart Cities [Internet]. 2017 Dec. 20 [cited 2023 Feb. 10];2(6):e1. Available from: https://publications.eai.eu/index.php/sc/article/view/1156 DOI: https://doi.org/10.4108/eai.20-12-2017.153495
Park E, Kim WH, Kim SB. Tracking tourism and hospitality employees’ real-time perceptions and emotions in an online community during the COVID-19 pandemic. Curr Issues Tour [Internet]. 2022;25(23):3761–5. Available from: https://doi.org/10.1080/13683500.2020.1823336
Belka R, Deniziak SR, Płaza M, Hejduk M, Pięta P, Płaza M, et al. Integrated visitor support system for tourism industry based on IoT technologies. In: ProcSPIE [Internet]. 2018. p. 108081J. Available from: https://doi.org/10.1117/12.2326403 DOI: https://doi.org/10.1117/12.2326403
Gonçalves F, Martins AL, Ferreira JC, Marques E, Andrade M, Mota L. Tourism Guidance Tracking and Safety Platform BT - Intelligent Transport Systems. From Research and Development to the Market Uptake. In: Martins AL, Ferreira JC, Kocian A, editors. Cham: Springer International Publishing; 2020. p. 162–71. DOI: https://doi.org/10.1007/978-3-030-38822-5_11
Crivellari A, Beinat E. Identifying foreign tourists’ nationality from mobility traces via LSTM neural network and location embeddings. Appl Sci. 2019;9(14). DOI: https://doi.org/10.3390/app9142861
Bloom JZ. Tourist market segmentation with linear and non-linear techniques. Tour Manag [Internet]. 2004;25(6):723–33. Available from: https://www.sciencedirect.com/science/article/pii/S0261517703001948 DOI: https://doi.org/10.1016/j.tourman.2003.07.004
O’Connor A, Zerger A, Itami B. Geo-temporal tracking and analysis of tourist movement. Math Comput Simul [Internet]. 2005;69(1):135–50. Available from: https://www.sciencedirect.com/science/article/pii/S0378475405000613 DOI: https://doi.org/10.1016/j.matcom.2005.02.036
Bloom JZ. MARKET SEGMENTATION: A Neural Network Application. Ann Tour Res [Internet]. 2005;32(1):93–111. Available from: https://www.sciencedirect.com/science/article/pii/S0160738304001033 DOI: https://doi.org/10.1016/j.annals.2004.05.001
Huang X, Jagota V, Espinoza-Muñoz E, Flores-Albornoz J. Tourist hot spots prediction model based on optimized neural network algorithm. Int J Syst Assur Eng Manag [Internet]. 2022;13(1):63–71. Available from: https://doi.org/10.1007/s13198-021-01226-4 DOI: https://doi.org/10.1007/s13198-021-01226-4
Hardy A, Aryal J. Using innovations to understand tourist mobility in national parks. J Sustain Tour [Internet]. 2020 Feb 1;28(2):263–83. Available from: https://doi.org/10.1080/09669582.2019.1670186 DOI: https://doi.org/10.1080/09669582.2019.1670186
Fan J, Xu W, Wu Y, Gong Y. Human Tracking Using Convolutional Neural Networks. IEEE Trans Neural Networks. 2010;21(10):1610–23. DOI: https://doi.org/10.1109/TNN.2010.2066286
Xu Y, Zhou X, Chen S, Li F. Deep learning for multiple object tracking: A survey. IET Comput Vis. 2019;13(4):411–9. DOI: https://doi.org/10.1049/iet-cvi.2018.5598
Brunetti A, Buongiorno D, Trotta GF, Bevilacqua V. Computer vision and deep learning techniques for pedestrian detection and tracking: A survey. Neurocomputing [Internet]. 2018;300:17–33. Available from: https://www.sciencedirect.com/science/article/pii/S092523121830290X DOI: https://doi.org/10.1016/j.neucom.2018.01.092
Marvasti-Zadeh SM, Cheng L, Ghanei-Yakhdan H, Kasaei S. Deep Learning for Visual Tracking: A Comprehensive Survey. IEEE Trans Intell Transp Syst. 2022;23(5):3943–68. DOI: https://doi.org/10.1109/TITS.2020.3046478
Jiao L, Wang D, Bai Y, Chen P, Liu F. Deep Learning in Visual Tracking: A Review. IEEE Trans Neural Networks Learn Syst. 2021;1–20. DOI: https://doi.org/10.1109/TNNLS.2021.3136907
Al-zubaydi ZA, Al-qaraawi SM. Tourists Localization System in Iraqi marshlands Zone. 2018;7(3):303–6.
Sodhro AH, Pirbhulal S, Luo Z, de Albuquerque VHC. Towards an optimal resource management for IoT based Green and sustainable smart cities. J Clean Prod [Internet]. 2019;220:1167–79. Available from: https://doi.org/10.1016/j.jclepro.2019.01.188 DOI: https://doi.org/10.1016/j.jclepro.2019.01.188
Park E, Kim WH, Kim SB. Tracking tourism and hospitality employees’ real-time perceptions and emotions in an online community during the COVID-19 pandemic. Curr Issues Tour [Internet]. 2022;25(23):3761–5. Available from: https://doi.org/10.1080/13683500.2020.1823336 DOI: https://doi.org/10.1080/13683500.2020.1823336
Semtech Corporation. 2020. SX1276/77/78/79 - 137 MHz to 1020 MHz Low Power Long Range Transceiver. Rev. 7, 2020. https://semtech.my.salesforce.com/sfc/p/#E0000000JelG/a/2R0000001Rbr/6EfVZUorrpoKFfvaF_Fkpgp5kzjiNyiAbqcpqh9qSjE
Digi International Inc. Digi XBee 3 Zigbee RF Module. https://www.digi.com/products/embedded-systems/digi-xbee/rf-modules/2-4-ghz-rf-modules/xbee3-zigbee-3
Infineon Technologies. 2019. PSoC 5LP: CY8C58LP Family Datasheet. https://www.infineon.com/dgdl/Infineon-PSoC_5LP_CY8C58LP_Family_Datasheet_Programmable_System-on-Chip_(PSoC_)-DataSheet-v15_00-EN.pdf?fileId=8ac78c8c7d0d8da4017d0ec547013ab9
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