IoT Sensor Challenges for Geothermal Energy Installations Monitoring: A Survey
Status PubMed-not-MEDLINE Jazyk angličtina Země Švýcarsko Médium electronic
Typ dokumentu časopisecké články, přehledy
Grantová podpora
SP2023/009
Student Grant System, VSB-TU Ostrava
No. 856670
European Union's Horizon 2020 research and innovation programme
PubMed
37420742
PubMed Central
PMC10300865
DOI
10.3390/s23125577
PII: s23125577
Knihovny.cz E-zdroje
- Klíčová slova
- IoT, edge computing, energy harvesting, geothermal energy, geothermal sensors,
- MeSH
- cloud computing MeSH
- geotermální energie * MeSH
- informační technologie MeSH
- internet věcí * MeSH
- technologie MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
Geothermal energy installations are becoming increasingly common in new city developments and renovations. With a broad range of technological applications and improvements in this field, the demand for suitable monitoring technologies and control processes for geothermal energy installations is also growing. This article identifies opportunities for the future development and deployment of IoT sensors applied to geothermal energy installations. The first part of the survey describes the technologies and applications of various sensor types. Sensors that monitor temperature, flow rate and other mechanical parameters are presented with a technological background and their potential applications. The second part of the article surveys Internet-of-Things (IoT), communication technology and cloud solutions applicable to geothermal energy monitoring, with a focus on IoT node designs, data transmission technologies and cloud services. Energy harvesting technologies and edge computing methods are also reviewed. The survey concludes with a discussion of research challenges and an outline of new areas of application for monitoring geothermal installations and innovating technologies to produce IoT sensor solutions.
Department of Electronics Engineering Kaunas University of Technology 44249 Kaunas Lithuania
School of Technology and Innovations University of Vaasa 65200 Vaasa Finland
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Mubarok M.H., Zarrouk S.J., Cater J.E. Two-phase flow measurement of geothermal fluid using orifice plate: Field testing and CFD validation. Renew. Energy. 2019;134:927–946. doi: 10.1016/j.renene.2018.11.081. DOI
Helbig S., Zarrouk S.J. Measuring two-phase flow in geothermal pipelines using sharp edge orifice plates. Geothermics. 2012;44:52–64. doi: 10.1016/j.geothermics.2012.07.003. DOI
Okazaki T., Seto R., Watanabe T., Ueda A., Kuramitz H. U-Shaped Polymer Cladding and Hetero-Core Fiber Optic Sensors for Monitoring Scale Formation in Geothermal Brine. Anal. Lett. 2020;53:2160–2169. doi: 10.1080/00032719.2020.1732400. DOI
Yadav D.K., Jayanthu S., Das S.K., Chinara S., Mishra P. Critical review on slope monitoring systems with a vision of unifying WSN and IoT. IET Wirel. Sens. Syst. 2019;9:167–180. doi: 10.1049/iet-wss.2018.5197. DOI
Bense V., Read T., Bour O., Le Borgne T., Coleman T., Krause S., Chalari A., Mondanos M., Ciocca F., Selker J. Distributed Temperature S ensing as a downhole tool in hydrogeology. Water Resour. Res. 2016;52:9259–9273. doi: 10.1002/2016WR018869. DOI
Challener W., Palit S., Jones R., Airey L., Craddock R., Knobloch A. MOEMS pressure sensors for geothermal well monitoring; Proceedings of the MOEMS and Miniaturized Systems XII; San Francisco, CA, USA. 2–7 February 2013.
Ali H., Choi J.H. A review of underground pipeline leakage and sinkhole monitoring methods based on wireless sensor networking. Sustainability. 2019;11:4007. doi: 10.3390/su11154007. DOI
Kim J.W., Lee C., Park S. Real-time health monitoring of pipeline structures using piezoelectric guided wave propagation. Adv. Sci. Lett. 2011;4:696–701. doi: 10.1166/asl.2011.1674. DOI
Muduli L., Mishra D.P., Jana P.K. Application of wireless sensor network for environmental monitoring in underground coal mines: A systematic review. J. Netw. Comput. Appl. 2018;106:48–67. doi: 10.1016/j.jnca.2017.12.022. DOI
Grimsley R., Marineau M., Iannucci B. Experiences in LP-IoT: EnviSense Deployment of Remotely Reprogrammable Environmental Sensors; Proceedings of the 1st ACM Workshop on No Power and Low Power Internet-of-Things; New Orleans, LA, USA. 31 January–4 February 2022; pp. 1–7.
Adhya S., Saha D., Das A., Jana J., Saha H. An IoT based smart solar photovoltaic remote monitoring and control unit; Proceedings of the 2nd International Conference on Control, Instrumentation, Energy and Communication, CIEC 2016; Kolkata, India. 28–30 January 2016; Piscataway, NJ, USA: IEEE; 2016. pp. 432–436.
Hossain M.I., Markendahl J.I. Comparison of LPWAN Technologies: Cost Structure and Scalability. Wirel. Pers. Commun. 2021;121:887–903. doi: 10.1007/s11277-021-08664-0. DOI
Aranzabal N., Martos J., Steger H., Blum P., Soret J. Temperature measurements along a vertical borehole heat exchanger: A method comparison. Renew. Energy. 2019;143:1247–1258. doi: 10.1016/j.renene.2019.05.092. DOI
Sanjuan B., Béchu E., Braibant G., Lebert F. High Temperature-High Pressure Rated Sensors and Tools Useful for Geothermal Purposes. Bibliographical Review. 2009, Final Report, BRGM/RP-57342-FR, pp. 44. [(accessed on 2 May 2023)]. Available online: http://infoterre.brgm.fr/rapports/RP-57342-FR.pdf.
Ukil A., Braendle H., Krippner P. Distributed temperature sensing: Review of technology and applications. IEEE Sens. J. 2011;12:885–892. doi: 10.1109/JSEN.2011.2162060. DOI
McDaniel A., Fratta D., Tinjum J.M., Hart D.J. Long-term district-scale geothermal exchange borefield monitoring with fiber optic distributed temperature sensing. Geothermics. 2018;72:193–204. doi: 10.1016/j.geothermics.2017.11.008. DOI
Reinsch T., Henninges J., Ásmundsson R. Thermal, mechanical and chemical influences on the performance of optical fibres for distributed temperature sensing in a hot geothermal well. Environ. Earth Sci. 2013;70:3465–3480. doi: 10.1007/s12665-013-2248-8. DOI
Martos J., Montero Á., Torres J., Soret J., Martínez G., García-Olcina R. Novel wireless sensor system for dynamic characterization of borehole heat exchangers. Sensors. 2011;11:7082–7094. doi: 10.3390/s110707082. PubMed DOI PMC
Erkan K., Akkoyunlu B., Balkan E., Tayanç M. A portable borehole temperature logging system using the four-wire resistance method. J. Geophys. Eng. 2017;14:1413–1419. doi: 10.1088/1742-2140/aa7ffe. DOI
Becerra G., Picazo M., Aguilar J., Xamán J., Osorio E., Hernandez J., Ledesma-Alonso R. Experimental study of a geothermal earth-to-air heat exchanger in Chetumal, Quintana Roo, Mexico. Energy Effic. 2022;15:20. doi: 10.1007/s12053-022-10022-3. DOI
Aranzabal N., Radioti G., Martos J., Soret J., Nguyen F., Charlier R. Enhanced thermal response test using fiber optics for a double U-pipe borehole heat exchanger analysed by numerical modeling; Proceedings of the 29th International Conference on Efficiency, Cost, Optimisation, Simulation and Environmental Impact of Energy Systems; Portoroz, Slovenia. 19–23 June 2016.
Gehlin S.E., Hellstrom G. Comparison of four models for thermal response test evaluation. ASHRAE Trans. 2003;109:131.
Ouyang L.B., Belanger D.L. Flow profiling by distributed temperature sensor (DTS) system-expectation and reality. SPE Prod. Oper. 2006;21:269–281. doi: 10.2118/90541-PA. DOI
Patterson J.R., Cardiff M., Coleman T., Wang H., Feigl K.L., Akerley J., Spielman P. Geothermal reservoir characterization using distributed temperature sensing at Brady Geothermal Field, Nevada. Lead. Edge. 2017;36:1024a1–1024a7. doi: 10.1190/tle36121024a1.1. DOI
Wu H., Feder K.S., Stolov A.A., Shenk S.D., Monberg E.M., Simoff D.A. High-temperature enhanced Rayleigh scattering optical fiber sensor for borehole applications; Proceedings of the Optical Components and Materials XVII; San Francisco, CA, USA. 1–6 February 2020; pp. 167–172.
Wu H., Stolov A.A., Feder K.S. Optical fiber as distributed acoustic sensing element with improved Rayleigh backscattering sensitivity and robustness under elevated temperature; Proceedings of the Optical Fibers and Sensors for Medical Diagnostics, Treatment and Environmental Applications XXI; Online, CA, USA. 6–12 March 2021; pp. 51–57.
Ilko J., Rusko M., Halper C., Majernik M., Majernik S. Flow Measurement on Hot Water Lines at Geothermal Power Plant Using Ultrasonic Method; Proceedings of the 31st DAAAM International Symposium; Mostar, Bosnia and Herzegovina. 21–24 October 2020;
Chhantyal K., Viumdal H., Mylvaganam S., Elseth G. Ultrasonic level sensors for flowmetering of non-Newtonian fluids in open Venturi channels: Using data fusion based on Artificial Neural Network and Support Vector Machines; Proceedings of the 2016 IEEE Sensors Applications Symposium (SAS); Catania, Italy. 20–22 April 2016; Piscataway, NJ, USA: IEEE; 2016. pp. 1–6.
de Zuquim M.P.S., Zarrouk S.J. Nursery greenhouses heated with geothermal energy–A case study from Rotorua New Zealand. Geothermics. 2021;95:102123. doi: 10.1016/j.geothermics.2021.102123. DOI
Agamata-Lu C. Chemical Tracer Dilution Test Using Isopropanol, Benzoate and Bromide at the Broadlands-Ohaaki Geothermal Field. Trans.-Geotherm. Resour. Counc. 2000;24:549–554.
Mella M., Olsen S., Rose P., Bour D., Petty S., Harris J. A Downhole Fluorimeter for Measuring Flow Processes in Geothermal and EGS Wellbores. Geotherm. Resour. Counc. Trans. 2010;34:1161–1166.
Sugiharto M.P., Marastio F.E., Fanani A.F., Pasaribu F., Silaban M., Maulana D.T., Saptadji N.M. The Implementation of Flow Performance Test to Monitor Well Performance in Geothermal Field. Iop Conf. Ser. Earth Environ. Sci. 2021;732:012020. doi: 10.1088/1755-1315/732/1/012020. DOI
Ruliandi D. Geothermal power plant system performance prediction using artificial neural networks; Proceedings of the 2015 IEEE Conference on Technologies for Sustainability; Ogden, UT, USA. 30 July–1 August 2015; pp. 216–223.
Mubarok M.H., Cater J.E., Zarrouk S.J. Comparative CFD modelling of pressure differential flow meters for measuring two-phase geothermal fluid flow. Geothermics. 2020;86:101801. doi: 10.1016/j.geothermics.2020.101801. DOI
Mubarok M.H., Zarrouk S.J., Cater J.E., Mundakir A., Bramantyo E.A., Lim Y.W. Real-time enthalpy measurement of two-phase geothermal fluid flow using load cell sensors: Field testing results. Geothermics. 2021;89:101930. doi: 10.1016/j.geothermics.2020.101930. DOI
Shen J. Measurement of Fluid Properties of Two-Phase Fluids Using an Ultrasonic Meter. 5,115,670. U.S. Patent. 1992 May 26;
Sanderson M., Yeung H. Guidelines for the use of ultrasonic non-invasive metering techniques. Flow Meas. Instrum. 2002;13:125–142. doi: 10.1016/S0955-5986(02)00043-2. DOI
Uhlmann M., Bertsch S. Measurement and Simulation of Startup and Shut Down of Heat Pumps; In Proceeding of the International Refrigeration and Air Conditioning Conference; West Lafayette, IN, USA. 12–15 July 2010.
Bixley P., Dench N., Wilson D. Development of well testing methods at Wairakei 1950–1980; Proceedings of the 20th Geothermal Workshop; Auckland, New Zealand. 1998.
Siitonen H.J. Output tests of shallow Rotorua wells; Proceedings of the 8th New Zealand Geothermal Workshop; Auckland, New Zealand. 5–7 November 1986; pp. 63–67.
Sanchez-Velasco R.A., Canchola-Felix I. Geothermal Steam Measurement with Orifice Plates, According with the ISO 5167—The Cerro Prieto Case. 2018.
López J., Martínez A., Pérez A., Medina A. Geological Results, Drilling and Mass Flow of the Well AZ-89, the Geothermal Field of Los Azufres, Mich. Resultados Geológicos, de Perforación y Produción del Pozo AZ-89, del Campo Geotérmico de los Azufres, Mich. 2018. [(accessed on 2 May 2023)]. Available online: https://www.researchgate.net/publication/296708344_Geological_results_drilling_and_mass_flow_of_the_well_AZ-89_the_geothermal_field_of_Los_Azufres_Mich.
Lovelock B. The 19th New Zealand Geothermal Workshop. University of Auckland; Auckland, New Zealand: 1997. Steam flow measurement in two-phase pipelines using volatile organic liquid tracers; pp. 75–80.
Armenta M. Validation of Hiriart Equation to Compute Steam Production by the Lip Pressure Method. Geothermal Resources Council; Davis, CA, USA: 1997. Technical Report.
Spencer E. Progress on international standardization of orifice plates for flow measurement. Int. J. Heat Fluid Flow. 1982;3:59–66. doi: 10.1016/0142-727X(82)90001-7. DOI
O’Banion T. Coriolis: The direct approach to mass flow measurement. Chem. Eng. Prog. 2013;109:41–46.
Sisler J.R., Zarrouk S.J., Urgel A., Lim Y.W., Adams R., Martin S. Measurement of two phase flows in geothermal pipelines using load-cells: Field trial results; Proceedings of the 37th New Zealand Geothermal Workshop; Taupo, New Zealand. 18–20 November 2015; p. 20.
Leven C., Barrash W. Fiber optic pressure measurements open up new experimental possibilities in hydrogeology. Groundwater. 2021;60:125–136. doi: 10.1111/gwat.13128. PubMed DOI
Dresen G., Stanchits S., Rybacki E. Borehole breakout evolution through acoustic emission location analysis. Int. J. Rock Mech. Min. Sci. 2010;47:426–435. doi: 10.1016/j.ijrmms.2009.12.010. DOI
Simonetti A. A measurement technique for the vibrating wire sensors; Proceedings of the NORCHIP 2012; Copenhagen, Denmark. 12–13 November 2012; Piscataway, NJ, USA: IEEE; 2012. pp. 1–6.
Stevens L. Pressure, temperature and flow logging in geothermal wells; Proceedings of the World Geothermal Congress; Kyushu-Tohoku, Japan. 28 May–10 June 2000; pp. 2435–2437.
Doetsch J., Gischig V.S., Villiger L., Krietsch H., Nejati M., Amann F., Jalali M., Madonna C., Maurer H., Wiemer S., et al. Subsurface fluid pressure and rock deformation monitoring using seismic velocity observations. Geophys. Res. Lett. 2018;45:10–389. doi: 10.1029/2018GL079009. DOI
Becker M., Coleman T., Ciervo C., Cole M., Mondanos M. Fluid pressure sensing with fiber-optic distributed acoustic sensing. Lead. Edge. 2017;36:1018–1023. doi: 10.1190/tle36121018.1. DOI
Liu H., Gao Z., Shao L., Li J. Design of monitoring system based on vibrating wire sensor; Proceedings of the 2019 Chinese Control And Decision Conference (CCDC); Nanchang, China. 3–5 June 2019; Piscataway, NJ, USA: IEEE; 2019. pp. 2457–2461.
Putra A.D., Toda H., Hafidz A., Matsuba K., Kimikado Y., Takahashi Y., Tsuzuki S., Kinoshita N., Yasuhara H. Development of slope deformation monitoring system based on tilt sensors with low-power wide area network technology and its application. J. Civ. Struct. Health Monit. 2021;11:1037–1053. doi: 10.1007/s13349-021-00494-9. DOI
Clarivate. Web of Science. [(accessed on 14 July 2022)]. Available online: https://www.webofscience.com.
Papaioannou P., Tzanis N., Tranoris C., Denazis S., Birbas A. A Prototype 5G/IoT Implementation for Transforming a Legacy Facility to a Smart Factory; Proceedings of the Artificial Intelligence Applications and Innovations. AIAI 2021 IFIP WG 12.5 International Workshops: 5G-PINE 2021, AI-BIO 2021, DAAI 2021, DARE 2021, EEAI 2021, and MHDW 2021; Hersonissos, Crete, Greece. 25–27 June 2021.
Lee J., Lee J., Jeong J. Design and Implementation of Injection Data Preprocessing Monitoring System Based on Node-RED; Proceedings of the International Symposium on Medical Information and Communication Technology, ISMICT, 2021; Xiamen, China. 14–16 April 2021; pp. 19–23.
Ali A. Framework for Air Pollution Monitoring in Smart Cities by Using IoT and Smart Sensors. ARPN J. Eng. Appl. Sci. 2022;17:670–674. doi: 10.31449/inf.v46i5.4003. DOI
Jabbar W.A., Annathurai S., Rahim T.A.A., Mohd Fauzi M.F. Smart energy meter based on a long-range wide-area network for a stand-alone photovoltaic system. Expert Syst. Appl. 2022;197:116703. doi: 10.1016/j.eswa.2022.116703. DOI
Lin J.Y., Tsai H.L., Lu G.H. Development of Wireless AC Power-Monitoring Module; Proceedings of the 8th International Conference on Applied System Innovation, ICASI 2022; Nantou, Taiwan. 22–23 April 2022; pp. 1–4.
Civerchia F., Bocchino S., Salvadori C., Rossi E., Maggiani L., Petracca M. Industrial Internet of Things monitoring solution for advanced predictive maintenance applications. J. Ind. Inf. Integr. 2017;7:4–12. doi: 10.1016/j.jii.2017.02.003. DOI
Shim H.K., Sun S., Kim H.S., Lee D.G., Lee Y.J., Jang J.S., Cho K.H., Baik J.M., Kang C.Y., Leng Y., et al. On a nonlinear broadband piezoelectric energy harvester with a coupled beam array. Appl. Energy. 2022;328:120129. doi: 10.1016/j.apenergy.2022.120129. DOI
Elahi H., Munir K., Eugeni M., Atek S., Gaudenzi P. Energy harvesting towards self-powered IoT devices. Energies. 2020;13:5528. doi: 10.3390/en13215528. DOI
Ryan E., Kosanovic D., McDaniel B. Application of thermal energy storage with electrified heating and cooling in a cold climate. Appl. Energy. 2022;328:120147. doi: 10.1016/j.apenergy.2022.120147. DOI
Yazawa K., Feng Y., Lu N. Conformal heat energy harvester on Steam4 pipelines for powering IoT sensors. Energy Convers. Manag. 2021;244:114487. doi: 10.1016/j.enconman.2021.114487. DOI
Das P., Ghosh S., Chatterjee S., De S. A Low Cost Outdoor Air Pollution Monitoring Device With Power Controlled Built-In PM Sensor. IEEE Sens. J. 2022;22:13682–13695. doi: 10.1109/JSEN.2022.3175821. DOI
Wang P., Gao M., Sun Y., Zhang H., Liao Y., Xie S. A vibration-powered self-contained node by profiling mechanism and its application in cleaner agricultural production. J. Clean. Prod. 2022;366:132897. doi: 10.1016/j.jclepro.2022.132897. DOI
Tran L.G., Cha H.K., Park W.T. RF power harvesting: A review on designing methodologies and applications. Micro Nano Syst. Lett. 2017;5:14. doi: 10.1186/s40486-017-0051-0. DOI
Twaha S., Zhu J., Yan Y., Li B. A comprehensive review of thermoelectric technology: Materials, applications, modelling and performance improvement. Renew. Sustain. Energy Rev. 2016;65:698–726. doi: 10.1016/j.rser.2016.07.034. DOI
Roy S., Kabir M.H., Salauddin M., Halim M.A. An Electromagnetic Wind Energy Harvester Based on Rotational Magnet Pole-Pairs for Autonomous IoT Applications. Energies. 2022;15:5725. doi: 10.3390/en15155725. DOI
Sandhu M.M., Khalifa S., Jurdak R., Portmann M. Task Scheduling for Energy-Harvesting-Based IoT: A Survey and Critical Analysis. IEEE Internet Things J. 2021;8:13825–13848. doi: 10.1109/JIOT.2021.3086186. DOI
Paterova T., Prauzek M., Konecny J., Ozana S., Zmij P., Stankus M., Weise D., Pierer A. Environment-monitoring IoT devices powered by a TEG which converts thermal flux between air and near-surface soil into electrical energy. Sensors. 2021;21:8098. doi: 10.3390/s21238098. PubMed DOI PMC
Shukla S., Jha P.K., Ray K.C. An energy-efficient single-cycle RV32I microprocessor for edge computing applications. Integration. 2023;88:233–240. doi: 10.1016/j.vlsi.2022.09.005. DOI
Pereira F., Correia R., Pinho P., Lopes S.I., Carvalho N.B. Challenges in resource-constrained iot devices: Energy and communication as critical success factors for future iot deployment. Sensors. 2020;20:6420. doi: 10.3390/s20226420. PubMed DOI PMC
NXP Semiconductors Official Site | NXP Semiconductors. [(accessed on 15 February 2023)]. Available online: https://www.nxp.com/
Smart|Connected|Secure|Microchip Technology. [(accessed on 18 February 2023)]. Available online: https://www.microchip.com/
Lin L., Tang Z., Tan N., Xiao X. Power management in low-power MCUs for energy IoT applications. J. Sens. 2020;2020:8819236. doi: 10.1155/2020/8819236. DOI
Khalifeh A., Mazunga F., Nechibvute A., Nyambo B.M. Microcontroller Unit-Based Wireless Sensor Network Nodes: A Review. Sensors. 2022;22:8937. doi: 10.3390/s22228937. PubMed DOI PMC
Lanza M., Sebastian A., Lu W.D., Le Gallo M., Chang M.F., Akinwande D., Puglisi F.M., Alshareef H.N., Liu M., Roldan J.B. Memristive technologies for data storage, computation, encryption, and radio-frequency communication. Science. 2022;376:eabj9979. doi: 10.1126/science.abj9979. PubMed DOI
Ayoub W., Samhat A.E., Nouvel F., Mroue M., Prévotet J.C. Internet of Mobile Things: Overview of LoRaWAN, DASH7, and NB-IoT in LPWANs Standards and Supported Mobility. IEEE Commun. Surv. Tutor. 2019;21:1561–1581. doi: 10.1109/COMST.2018.2877382. DOI
Raza U., Kulkarni P., Sooriyabandara M. Low Power Wide Area Networks: An Overview. IEEE Commun. Surv. Tutor. 2017;19:855–873. doi: 10.1109/COMST.2017.2652320. DOI
Alghamdi A.M., Khairullah E.F., Al Mojamed M.M. LoRaWAN Performance Analysis for a Water Monitoring and Leakage Detection System in a Housing Complex. Sensors. 2022;22:7188. doi: 10.3390/s22197188. PubMed DOI PMC
Haxhibeqiri J., De Poorter E., Moerman I., Hoebeke J. A survey of LoRaWAN for IoT: From technology to application. Sensors. 2018;18:3995. doi: 10.3390/s18113995. PubMed DOI PMC
Mekki K., Bajic E., Chaxel F., Meyer F. A comparative study of LPWAN technologies for large-scale IoT deployment. ICT Express. 2019;5:1–7. doi: 10.1016/j.icte.2017.12.005. DOI
Sousa D., Hernandez D., Oliveira F., Luís M., Sargento S. A platform of unmanned surface vehicle swarms for real time monitoring in aquaculture environments. Sensors. 2019;19:4695. doi: 10.3390/s19214695. PubMed DOI PMC
Lykov Y., Paniotova A., Shatalova V., Lykova A. Energy Efficiency Comparison LPWANs: LoRaWan vs Sigfox; Proceedings of the 2020 IEEE International Conference on Problems of Infocommunications. Science and Technology (PIC S&T); Kharkiv, Ukraine. 6–9 October 2020; Piscataway, NJ, USA: IEEE; 2020. pp. 485–490.
Gomez C., Veras J.C., Vidal R., Casals L., Paradells J. A sigfox energy consumption model. Sensors. 2019;19:681. doi: 10.3390/s19030681. PubMed DOI PMC
Aernouts M., Berkvens R., Van Vlaenderen K., Weyn M. Sigfox and LoRaWAN datasets for fingerprint localization in large urban and rural areas. Data. 2018;3:13. doi: 10.3390/data3020013. DOI
Popli S., Jha R.K., Jain S. A Survey on Energy Efficient Narrowband Internet of Things (NBIoT): Architecture, Application and Challenges. IEEE Access. 2019;7:16739–16776. doi: 10.1109/ACCESS.2018.2881533. DOI
Sun R., Chang W., Talarico S., Niu H., Yang H. Design and performance of unlicensed NB-IoT; Proceedings of the International Symposium on Wireless Communication Systems; Oulu, Finland. 27–30 August 2019; pp. 469–473.
Alobaidy H.A.H., Singh M.J., Nordin R., Abdullah N.F., Gze Wei C., Siang Soon M.L. Real-World Evaluation of Power Consumption and Performance of NB-IoT in Malaysia. IEEE Internet Things J. 2022;9:11614–11632. doi: 10.1109/JIOT.2021.3131160. DOI
Jewel M.K.H., Zakariyya R.S., Lin F. On channel estimation in LTE–based downlink narrowband internet of things systems. Electronics. 2021;10:1246. doi: 10.3390/electronics10111246. DOI
Olejniczak A., Błaszkiewicz O., Cwalina K.K., Rajchowski P., Sadowski J. Software-defined NB-IoT uplink framework—The design, implementation and use cases. Sensors. 2021;21:8234. doi: 10.3390/s21248234. PubMed DOI PMC
Lalle Y., Fourati L.C., Fourati M., Barraca J.P. A Comparative Study of LoRaWAN, SigFox, and NB-IoT for Smart Water Grid; Proceedings of the 2019 Global Information Infrastructure and Networking Symposium, GIIS 2019; Paris, France. 18–20 December 2019.
Almuhaya M.A.M., Jabbar W.A., Sulaiman N., Abdulmalek S. A Survey on LoRaWAN Technology: Recent Trends, Opportunities, Simulation Tools and Future Directions. Electronics. 2022;11:164. doi: 10.3390/electronics11010164. DOI
Durand T., Visagie L., Booysen M.T. Evaluation of next-generation low-power communication technology to replace GSM in IoT-applications. IET Commun. 2019;13:2533–2540. doi: 10.1049/iet-com.2019.0168. DOI
Manvi S.S., Shyam G.K. Resource management for Infrastructure as a Service (IaaS) in cloud computing: A survey. J. Netw. Comput. Appl. 2014;41:424–440. doi: 10.1016/j.jnca.2013.10.004. DOI
Papacharalambous B. Cloud services vs. On–premise solutions cost comparison calculator; Proceedings of the Business Information Systems Workshops: BIS 2014 International Workshops; Larnaca, Cyprus. 22–23 May 2014; Cham, Switzerland: Springer; 2014. pp. 318–325.
Parast F.K., Sindhav C., Nikam S., Yekta H.I., Kent K.B., Hakak S. Cloud computing security: A survey of service–based models. Comput. Secur. 2022;114:102580. doi: 10.1016/j.cose.2021.102580. DOI
Pierleoni P., Concetti R., Belli A., Palma L. Amazon, Google and Microsoft Solutions for IoT: Architectures and a Performance Comparison. IEEE Access. 2019;8:5455–5470. doi: 10.1109/ACCESS.2019.2961511. DOI
Muhammed A.S., Ucuz D. Comparison of the IoT Platform Vendors, Microsoft Azure, AmazonWeb Services, and Google Cloud, from Users’ Perspectives; Proceedings of the 8th International Symposium on Digital Forensics and Security; Beirut, Lebanon. 1–2 June 2020.
Grados B., Bedon H. Software Components of an IoT Monitoring Platform in Google Cloud Platform: A Descriptive Research and an Architectural Proposal. In: Botto-Tobar M., Zambrano Vizuete M., Torres-Carrión P., Montes León S., Pizarro Vásquez G., Durakovic B., editors. Applied Technologies. ICAT 2019. Communications in Computer and Information Science. Volume 1193. Springer; Berlin, Germany: 2020. pp. 153–167.
Kaya M.C., Nikoo M.S., Schwartz M.L., Oguztuzun H. Internet of measurement things architecture: Proof of concept with scope of accreditation. Sensors. 2020;20:503. doi: 10.3390/s20020503. PubMed DOI PMC
Kim C.W., Qi J., Kawabe D. Current Perspectives and New Directions in Mechanics, Modelling and Design of Structural Systems. CRC Press; London, UK: 2022. Development of vibration-based early scour warning system for railway bridge piers; pp. 1735–1740.
Dai H., Shi P., Liu H., Chen R., Chen Z. Electrical fire monitoring IoT framework for ancient architectural complex leveraging edge computing. Int. J. Commun. Syst. 2022;35:e5329. doi: 10.1002/dac.5329. DOI
Bassetti E., Panizzi E. Earthquake Detection at the Edge: IoT Crowdsensing Network. Information. 2022;13:195. doi: 10.3390/info13040195. DOI
Rivet F., Foucaud L., Ferre G. Edge Computing Technique for a 87% Energy Saving for IoT Device Dedicated to Environmental Monitoring; Proceedings of the 2021 IEEE 12th Latin American Symposium on Circuits and Systems, LASCAS 2021; Arequipa, Peru. 22–25 February 2021.
Debski R., Drezewski R. Real-time surrogate-assisted preprocessing of streaming sensor data. Comput. Netw. 2022;219:109422. doi: 10.1016/j.comnet.2022.109422. DOI
Murshed M.S., Murphy C., Hou D., Khan N., Ananthanarayanan G., Hussain F. Machine Learning at the Network Edge: A Survey. ACM Comput. Surv. 2022;54:1–37. doi: 10.1145/3469029. DOI
Nourildean S.W., Hassib M.D., Mohammed Y.A. Internet of things based wireless sensor network: A review. J. Electr. Eng. Comput. Sci. 2022;27:246–261. doi: 10.11591/ijeecs.v27.i1.pp246-261. DOI
Tran-Dang H., Krommenacker N., Charpentier P., Kim D.S. The Internet of Things for logistics: Perspectives, application review, and challenges. IETE Tech. Rev. 2022;39:93–121. doi: 10.1080/02564602.2020.1827308. DOI
Li W., Awais M., Ru W., Shi W., Ajmal M., Uddin S., Liu C. Review of sensor network-based irrigation systems using IoT and remote sensing. Adv. Meteorol. 2020;2020:8396164. doi: 10.1155/2020/8396164. DOI
Widianto M.H., Ranny R. Message querying telemetry transfer on IoT applications to enhance technology: A systematic review. Int. J. Reconfig. Embed. Syst. 2022;11:265. doi: 10.11591/ijres.v11.i3.pp265-274. DOI
Ullo S.L., Sinha G.R. Advances in smart environment monitoring systems using IoT and sensors. Sensors. 2020;20:3113. doi: 10.3390/s20113113. PubMed DOI PMC
Yu M. Network telemetry: Towards a top-down approach. ACM SIGCOMM Comput. Commun. Rev. 2019;49:11–17. doi: 10.1145/3314212.3314215. DOI
Zhang W., Yue M. The application of building energy management system based on IoT technology in smart city. Int. J. Syst. Assur. Eng. Manag. 2021;12:617–628. doi: 10.1007/s13198-021-01054-6. DOI
Okafor N.U., Alghorani Y., Delaney D.T. Improving data quality of low-cost IoT sensors in environmental monitoring networks using data fusion and machine learning approach. ICT Express. 2020;6:220–228. doi: 10.1016/j.icte.2020.06.004. DOI
Greco A., Gundabattini E., Solomon D.G., Singh Rassiah R., Masselli C. A Review on Geothermal Renewable Energy Systems for Eco-Friendly Air-Conditioning. Energies. 2022;15:5519. doi: 10.3390/en15155519. DOI
Li B.Q., Zheng S.Y. Application research of intelligent monitoring system of longsheng hot spring water temperature based on Internet of Things. Therm. Sci. 2019;23:2613–2622. doi: 10.2298/TSCI181127150L. DOI
Chang V., Martin C. An industrial IoT sensor system for high-temperature measurement. Comput. Electr. Eng. 2021;95:107439. doi: 10.1016/j.compeleceng.2021.107439. DOI
Onumanyi A.J., Abu-Mahfouz A.M., Hancke G.P. Low power wide area network, cognitive radio and the Internet of Things: Potentials for integration. Sensors. 2020;20:6837. doi: 10.3390/s20236837. PubMed DOI PMC
Liu Y., Dhakal S. Internet of Things technology in mineral remote sensing monitoring. Int. J. Circuit Theory Appl. 2020;48:2065–2077. doi: 10.1002/cta.2890. DOI