Internet of Robotic Things: Current Technologies, Challenges, Applications, and Future Research Topics

. 2025 Jan 27 ; 25 (3) : . [epub] 20250127

Status PubMed-not-MEDLINE Jazyk angličtina Země Švýcarsko Médium electronic

Typ dokumentu časopisecké články, přehledy

Perzistentní odkaz   https://www.medvik.cz/link/pmid39943403

Grantová podpora
CZ.10.03.01/00/22_003/0000048 European Union under the RE-FRESH

This article focuses on the integration of the Internet of Things (IoT) and the Internet of Robotic Things, representing a dynamic research area with significant potential for industrial applications. The Internet of Robotic Things (IoRT) integrates IoT technologies into robotic systems, enhancing their efficiency and autonomy. The article provides an overview of the technologies used in IoRT, including hardware components, communication technologies, and cloud services. It also explores IoRT applications in industries such as healthcare, agriculture, and more. The article discusses challenges and future research directions, including data security, energy efficiency, and ethical issues. The goal is to raise awareness of the importance of IoRT and demonstrate how this technology can bring significant benefits across various sectors.

Zobrazit více v PubMed

Al-Fuqaha A., Guizani M., Mohammadi M., Aledhari M., Ayyash M. Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications. IEEE Commun. Surv. Tutor. 2015;17:2347–2376. doi: 10.1109/COMST.2015.2444095. DOI

Gubbi J., Buyya R., Marusic S., Palaniswami M. Internet of Things (IoT): A vision, architectural elements, and future directions. Future Gener. Comput. Syst. 2013;29:1645–1660. doi: 10.1016/j.future.2013.01.010. DOI

Xu L.D., He W., Li S. Internet of things in industries: A survey. IEEE Trans. Ind. Inform. 2014;10:2233–2243. doi: 10.1109/TII.2014.2300753. DOI

Khan Y., Ostfeld A.E., Lochner C.M., Pierre A., Arias A.C. Monitoring of Vital Signs with Flexible and Wearable Medical Devices. Adv. Mater. 2016;28:4373–4395. doi: 10.1002/adma.201504366. PubMed DOI

Rahmani A.M., Gia T.N., Negash B., Anzanpour A., Azimi I., Jiang M., Liljeberg P. Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach. Future Gener. Comput. Syst. 2018;78:641–658. doi: 10.1016/j.future.2017.02.014. DOI

Dimitrov D.V. Medical internet of things and big data in healthcare. Healthc. Inform. Res. 2016;22:156–163. doi: 10.4258/hir.2016.22.3.156. PubMed DOI PMC

Tzounis A., Katsoulas N., Bartzanas T., Kittas C. Internet of Things in agriculture, recent advances and future challenges. Biosyst. Eng. 2017;164:31–48. doi: 10.1016/j.biosystemseng.2017.09.007. DOI

Ayaz M., Ammad-Uddin M., Sharif Z., Mansour A., Aggoune E.H.M. Internet-of-Things (IoT)-based smart agriculture: Toward making the fields talk. IEEE Access. 2019;7:129551–129583. doi: 10.1109/ACCESS.2019.2932609. DOI

Talavera J.M., Tobón L.E., Gómez J.A., Culman M.A., Aranda J.M., Parra D.T., Quiroz L.A., Hoyos A., Garreta L.E. Review of IoT applications in agro-industrial and environmental fields. Comput. Electron. Agric. 2017;142:283–297. doi: 10.1016/j.compag.2017.09.015. DOI

Kott A., Swami A., West B.J. The Internet of Battle Things. Computer. 2016;49:70–75. doi: 10.1109/MC.2016.355. DOI

Shi W., Cao J., Zhang Q., Li Y., Xu L. Edge Computing: Vision and Challenges. IEEE Internet Things J. 2016;3:637–646. doi: 10.1109/JIOT.2016.2579198. DOI

Chiang M., Zhang T. Fog and IoT: An Overview of Research Opportunities. IEEE Internet Things J. 2016;3:854–864. doi: 10.1109/JIOT.2016.2584538. DOI

Naik N. Choice of effective messaging protocols for IoT systems: MQTT, CoAP, AMQP and HTTP; Proceedings of the 2017 IEEE International Systems Engineering Symposium (ISSE); Vienna, Austria. 11–13 October 2017; DOI

Botta A., De Donato W., Persico V., Pescapé A. Integration of Cloud computing and Internet of Things: A survey. Future Gener. Comput. Syst. 2016;56:684–700. doi: 10.1016/j.future.2015.09.021. DOI

Kiesler N., Impagliazzo J. Internet of Everything. Volume 458. Springer; Cham, Swizerland: 2023. Perspectives on the Internet of Everything; pp. 3–17. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST. DOI

Jin B., Khan F., Alturki R., Ikram M.A. Computational intelligence-enabled prediction and communication mechanism for IoT-based autonomous systems. ISA Trans. 2023;132:146–154. doi: 10.1016/j.isatra.2022.06.007. PubMed DOI

Wang B., Tao F., Fang X., Liu C., Liu Y., Freiheit T. Smart Manufacturing and Intelligent Manufacturing: A Comparative Review. Engineering. 2021;7:738–757. doi: 10.1016/j.eng.2020.07.017. DOI

Oztemel E., Gursev S. Literature review of Industry 4.0 and related technologies. J. Intell. Manuf. 2020;31:127–182. doi: 10.1007/s10845-018-1433-8. DOI

Wall D., McCullagh P., Cleland I., Bond R. Development of an Internet of Things solution to monitor and analyse indoor air quality. Internet Things. 2021;14:100392. doi: 10.1016/j.iot.2021.100392. DOI

Lombardi M., Pascale F., Santaniello D. Internet of things: A general overview between architectures, protocols and applications. Information. 2021;12:87. doi: 10.3390/info12020087. DOI

Mousavi S.K., Ghaffari A., Besharat S., Afshari H. Security of internet of things based on cryptographic algorithms: A survey. Wirel. Netw. 2021;27:1515–1555. doi: 10.1007/s11276-020-02535-5. DOI

Bragança S., Costa E., Castellucci I., Arezes P.M. Occupational and Environmental Safety and Health. Springer; Cham, Switzerland: 2019. A brief overview of the use of collaborative robots in industry 4.0: Human role and safety; pp. 641–650.

Sagiroglu S., Sinanc D. Big data: A review; Proceedings of the 2013 international conference on collaboration technologies and systems (CTS); San Diego, CA, USA. 20–24 May 2013; Piscataway, NJ, USA: IEEE; 2013. pp. 42–47.

Soori M., Arezoo B., Dastres R. Internet of things for smart factories in industry 4.0, a review. Internet Things-Cyber-Phys. Syst. 2023;3:192–204. doi: 10.1016/j.iotcps.2023.04.006. DOI

Hussain R., Zeadally S. Autonomous cars: Research results, issues, and future challenges. IEEE Commun. Surv. Tutor. 2018;21:1275–1313. doi: 10.1109/COMST.2018.2869360. DOI

Dudhe P., Kadam N., Hushangabade R.M., Deshmukh M.S. Internet of Things (IOT): An overview and its applications; Proceedings of the 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS); Chennai, India. 1–2 August 2017; pp. 2650–2653. DOI

Sayeed A., Verma C., Kumar N., Koul N., Illés Z. Approaches and Challenges in Internet of Robotic Things. Future Internet. 2022;14:265. doi: 10.3390/fi14090265. DOI

Masuda Y., Zimmermann A., Shirasaka S., Nakamura O. Internet of robotic things with digital platforms: Digitization of robotics enterprise. Smart Innov. Syst. Technol. 2021;189:381–391. doi: 10.1007/978-981-15-5784-2_31. DOI

ElBanhawy M., Mohamed A., Saber W., Rizk R.Y. The Internet of Robotic Things: A Review of Concept, Challenges and Applications. Lect. Notes Data Eng. Commun. Technol. 2023;184:316–326. doi: 10.1007/978-3-031-43247-7_28. DOI

Paolone G., Iachetti D., Paesani R., Pilotti F., Marinelli M., Di Felice P. A Holistic Overview of the Internet of Things Ecosystem. IoT. 2022;3:398–434. doi: 10.3390/iot3040022. DOI

Kabir H., Tham M.L., Chang Y.C. Internet of robotic things for mobile robots: Concepts, technologies, challenges, applications, and future directions. Digit. Commun. Netw. 2023;9:1265–1290. doi: 10.1016/j.dcan.2023.05.006. DOI

Raza A., Baloch M.H., Ali I., Ali W., Hassan M., Karim A. Artificial Intelligence and IoT-Based Autonomous Hybrid Electric Vehicle with Self-Charging Infrastructure; Proceedings of the 2022 International Conference on Emerging Technologies in Electronics, Computing and Communication (ICETECC); Jamshoro, Pakistan. 7–9 December 2022; pp. 1–6. DOI

Balasubramaniam P., Muthurajan A.K., Arivazhagan A.R., Jayaprakasam H. IoT based multitasking robotic vehicle. AIP Conf. Proc. 2023;2857:020075. doi: 10.1063/5.0169337. DOI

Romeo L., Petitti A., Marani R., Milella A. Internet of Robotic Things in Smart Domains: Applications and Challenges. Sensors. 2020;20:3355. doi: 10.3390/s20123355. PubMed DOI PMC

Eder A., Koller W., Mahlberg B. The contribution of industrial robots to labor productivity growth and economic convergence: A production frontier approach. J. Product. Anal. 2024;61:157–181. doi: 10.1007/s11123-023-00707-x. DOI

Hjorth S., Chrysostomou D. Human–robot collaboration in industrial environments: A literature review on non-destructive disassembly. Robot. Comput.-Integr. Manuf. 2022;73:102208. doi: 10.1016/j.rcim.2021.102208. DOI

Maurtua I., Ibarguren A., Kildal J., Susperregi L., Sierra B. Human–robot collaboration in industrial applications: Safety, interaction and trust. Int. J. Adv. Robot. Syst. 2017;14:1729881417716010. doi: 10.1177/1729881417716010. DOI

Othman U., Yang E. Human–Robot Collaborations in Smart Manufacturing Environments: Review and Outlook. Sensors. 2023;23:5663. doi: 10.3390/s23125663. PubMed DOI PMC

Guerra-Zubiaga D.A., Luong K.Y. Energy consumption parameter analysis of industrial robots using design of experiment methodology. Int. J. Sustain. Eng. 2021;14:996–1005. doi: 10.1080/19397038.2020.1805040. DOI

Wang X., Chi Y., Li F., Gao L., Peng Y. The research of industrial robots design based on synchronous technology. Appl. Mech. Mater. 2012;233:347–350. doi: 10.4028/www.scientific.net/AMM.233.347. DOI

Amiri P., Müller M., Southgate M., Theodoridis T., Wei G., Richards-Brown M., Holderbaum W. A Statistical Analysis of Commercial Articulated Industrial Robots and Cobots. J. Manuf. Mater. Process. 2024;8:216. doi: 10.3390/jmmp8050216. DOI

Dzedzickis A., Subačiūtė-Žemaitienė J., Šutinys E., Samukaitė-Bubnienė U., Bučinskas V. Advanced Applications of Industrial Robotics: New Trends and Possibilities. Appl. Sci. 2022;12:135. doi: 10.3390/app12010135. DOI

Siemasz R., Tomczuk K., Malecha Z. 3D printed robotic arm with elements of artificial intelligence. Procedia Comput. Sci. 2020;176:3741–3750. doi: 10.1016/j.procs.2020.09.013. DOI

Wu K., Li J., Zhao H., Zhong Y. Review of Industrial Robot Stiffness Identification and Modelling. Appl. Sci. 2022;12:8719. doi: 10.3390/app12178719. DOI

Tipary B., Erdős G. Tolerance analysis for robotic pick-and-place operations. Int. J. Adv. Manuf. Technol. 2021;117:1405–1426. doi: 10.1007/s00170-021-07672-5. DOI

Ji W., Wang L. Industrial robotic machining: A review. Int. J. Adv. Manuf. Technol. 2019;103:1239–1255. doi: 10.1007/s00170-019-03403-z. DOI

Martinova L.I., Sokolov S.S., Nikishechkin P.A. Advances in Swarm and Computational Intelligence. Volume 9141. Springer; Cham, Switzerland: 2015. Tools for monitoring and parameter visualization in computer control systems of industrial robots; pp. 200–207. Lecture Notes in Computer Science. DOI

Hoang M., Chen S., Go M., Yu Z., Lo A., Brumley A., Li M., Santiago R., Dobbs S.K., Ocampo J. Designing Regenerative and Sustainable High Endurance Unmanned Aerial Vehicles; Proceedings of the 2024 IEEE Conference on Technologies for Sustainability (SusTech); Portland, OR, USA. 14–17 April 2024; pp. 212–219. DOI

Airbus Defence and Space Zephyr: The Stratospheric UAS. 2024. [(accessed on 9 October 2024)]. Available online: https://www.airbus.com/en/products-services/defence/uas/uas-solutions/zephyr.

Sharma N., Pandey J.K., Mondal S. A Review of Mobile Robots: Applications and Future Prospect. Int. J. Precis. Eng. Manuf. 2023;24:1695–1706. doi: 10.1007/s12541-023-00876-7. DOI

Rubio F., Valero F., Llopis-Albert C. A review of mobile robots: Concepts, methods, theoretical framework, and applications. Int. J. Adv. Robot. Syst. 2019;16:1729881419839596. doi: 10.1177/1729881419839596. DOI

Hijikata M., Miyagusuku R., Ozaki K. Wheel Arrangement of Four Omni Wheel Mobile Robot for Compactness. Appl. Sci. 2022;12:5798. doi: 10.3390/app12125798. DOI

Dhanush D., Raghul K.R., KR S.R., Mukund P.G., Ganesan M. An Omni-Directional Self driving Robot for Indoor Surveillance; Proceedings of the 2024 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT); Karaikal, India. 4–5 July 2024; pp. 1–6. DOI

Hwang S.H., Jang I.S., Kim D.H., Kim H.J. Safe Motion Planning and Control for Mobile Robots: A Survey. Int. J. Control. Autom. Syst. 2024;22:2955–2969. doi: 10.1007/s12555-024-0784-5. DOI

Bradshaw J.M. An introduction to software agents. Softw. Agents. 1997;4:3–46.

Rawassizadeh R., Sen T., Kim S.J., Meurisch C., Keshavarz H., Mühlhäuser M., Pazzani M. Manifestation of virtual assistants and robots into daily life: Vision and challenges. CCF Trans. Pervasive Comput. Interact. 2019;1:163–174. doi: 10.1007/s42486-019-00014-1. DOI

Aylett R., Ballin D. Intelligent Virtual Agents. Springer; Berlin/Heidelberg, Germany: 2013.

Sandini G., Sciutti A., Morasso P. Artificial cognition vs. artificial intelligence for next-generation autonomous robotic agents. Front. Comput. Neurosci. 2024;18:1349408. doi: 10.3389/fncom.2024.1349408. PubMed DOI PMC

Rohit K., Shankar A., Katiyar G., Mehrotra A., Alzeiby E.A. Consumer engagement in chatbots and voicebots. A multiple-experiment approach in online retailing context. J. Retail. Consum. Serv. 2024;78:103728. doi: 10.1016/j.jretconser.2024.103728. DOI

Patrício L., Varela L., Silveira Z. Integration of Artificial Intelligence and Robotic Process Automation: Literature Review and Proposal for a Sustainable Model. Appl. Sci. 2024;14:9648. doi: 10.3390/app14219648. DOI

Gopal L.S., Prabha R., Pullarkatt D., Ramesh M.V. Machine Learning based Classification of Online News Data for Disaster Management; Proceedings of the 2020 IEEE Global Humanitarian Technology Conference (GHTC); Seattle, WA, USA. 29 October–1 November 2020; pp. 1–8. DOI

Qiu B., Chen S., Gu Y., Zhang C., Yang G. Concurrent layout and trajectory optimization for robot workcell toward energy-efficient and collision-free automation. Int. J. Adv. Manuf. Technol. 2022;122:263–275. doi: 10.1007/s00170-022-09398-4. DOI

Siciliano B., Khatib O., editors. Springer Handbook of Robotics. Springer International Publishing; Cham, Switzerland: 2016. DOI

Flammini A., Ferrari P., Marioli D., Sisinni E., Taroni A. Wired and wireless sensor networks for industrial applications. Microelectron. J. 2009;40:1322–1336. doi: 10.1016/j.mejo.2008.08.012. DOI

Deveci B.U., Bas H., Ummak E., Albayrak O., Unal P. A Thorough Analysis and Comparison of Data Communication Protocols Used in Industry 4.0: The Case of Smart-CNC; Proceedings of the 2022 9th International Conference on Future Internet of Things and Cloud (FiCloud); Rome, Italy. 22–24 August 2022; pp. 199–206. DOI

Wollschlaeger M., Sauter T., Jasperneite J. The Future of Industrial Communication: Automation Networks in the Era of the Internet of Things and Industry 4.0. IEEE Ind. Electron. Mag. 2017;11:17–27. doi: 10.1109/MIE.2017.2649104. DOI

Chettri L., Bera R. A Comprehensive Survey on Internet of Things (IoT) Toward 5G Wireless Systems. IEEE Internet Things J. 2020;7:16–32. doi: 10.1109/JIOT.2019.2948888. DOI

Sufyan A., Khan K.B., Khashan O.A., Mir T., Mir U. From 5G to beyond 5G: A Comprehensive Survey of Wireless Network Evolution, Challenges, and Promising Technologies. Electronics. 2023;12:2200. doi: 10.3390/electronics12102200. DOI

Mosenia A., Jha N.K. A Comprehensive Study of Security of Internet-of-Things. IEEE Trans. Emerg. Top. Comput. 2017;5:586–602. doi: 10.1109/TETC.2016.2606384. DOI

Xu X., Zang S., Bilal M., Xu X., Dou W. Intelligent architecture and platforms for private edge cloud systems: A review. Future Gener. Comput. Syst. 2024;160:457–471. doi: 10.1016/j.future.2024.06.024. DOI

Vermesan O., Bahr R., Ottella M., Serrano M., Karlsen T., Wahlstrøm T., Sand H.E., Ashwathnarayan M., Gamba M.T. Internet of Robotic Things Intelligent Connectivity and Platforms. Front. Robot. AI. 2020;7:104. doi: 10.3389/frobt.2020.00104. PubMed DOI PMC

Bhat K.U., Kumar N., Koul N., Verma C., Enescu F.M., Raboaca M.S. Intelligent Communication for Internet of Things (IoRT) In: Singh Y., Verma C., Zoltán I., Chhabra J.K., Singh P.K., editors. Proceedings of the International Conference on Recent Innovations in Computing. Springer; Singapore: 2023. pp. 313–328.

Paul B. Internet of Things (IoT), Three-Layer Architecture, Security Issues and Counter Measures. In: Fong S., Dey N., Joshi A., editors. Proceedings of the ICT Analysis and Applications. Springer; Singapore: 2022. pp. 23–34.

Adi P.D.P., Kitagawa A., Akita J. Finger Robotic control use M5Stack board and MQTT Protocol based; Proceedings of the 2020 7th International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE); Semarang, Indonesia. 24–25 September 2020; pp. 1–6. DOI

Li X.Q., Ding X., Zhang Y., Sun Z.P., Zhao H.W. IoT family robot based on raspberry Pi; Proceedings of the 2016 International Conference on Information System and Artificial Intelligence (ISAI); Hong Kong, China. 24–26 June 2016; pp. 622–625. DOI

Joshi J., Kurian D., Awasthi S.B.P., Mukherjee S., Mittal S., Sharma S. Health Monitoring Using Wearable Sensor and Cloud Computing; Proceedings of the 2016 International Conference on Cybernetics, Robotics and Control; Hong Kong, China. 19–21 August 2016; pp. 104–108. DOI

Kim W.S., Lee W.S., Kim Y.J. A Review of the Applications of the Internet of Things (IoT) for Agricultural Automation. J. Biosyst. Eng. 2020;45:385–400. doi: 10.1007/s42853-020-00078-3. DOI

Sharma A., Kapoor D.S., Nayyar A., Qureshi B., Singh K.J., Thakur K. Exploration of IoT Nodes Communication Using LoRaWAN in Forest Environment. Comput. Mater. Contin. 2022;71:6240–6256. doi: 10.32604/cmc.2022.024639. DOI

Samuel S.S.I. A review of connectivity challenges in IoT-smart home; Proceedings of the 2016 3rd MEC International Conference on Big Data and Smart City (ICBDSC); Muscat, Oman. 15–16 March 2016; pp. 364–367. DOI

Al-Sarawi S., Anbar M., Alieyan K., Alzubaidi M. Internet of Things (IoT) communication protocols: Review; Proceedings of the 2017 8th International Conference on Information Technology (ICIT); Amman, Jordan. 17–18 May 2017; pp. 685–690. DOI

Amaran M.H., Noh N.A.M., Rohmad M.S., Hashim H. A Comparison of Lightweight Communication Protocols in Robotic Applications. Procedia Comput. Sci. 2015;76:400–405. doi: 10.1016/j.procs.2015.12.318. DOI

Zhang J., Ma M., Wang P., dong Sun X. Middleware for the Internet of Things: A survey on requirements, enabling technologies, and solutions. J. Syst. Archit. 2021;117:102098. doi: 10.1016/j.sysarc.2021.102098. DOI

Ngu A.H., Gutierrez M., Metsis V., Nepal S., Sheng Q.Z. IoT Middleware: A Survey on Issues and Enabling Technologies. IEEE Internet Things J. 2017;4:1–20. doi: 10.1109/JIOT.2016.2615180. DOI

Babiuch M., Foltýnek P. Creating a Mobile Application with the ESP32 Azure IoT Development Board Using a Cloud Platform; Proceedings of the 2021 22nd International Carpathian Control Conference (ICCC); Velké Karlovice, Czech Republic. 31 May–1 June 2021; pp. 1–4. DOI

Ayaida M., Messai N., Valentin F., Marcheras D. TalkRoBots: A Middleware for Robotic Systems in Industry 4.0. Future Internet. 2022;14:109. doi: 10.3390/fi14040109. DOI

The Open Source Robotics Foundation Robot Operating System (ROS) 2025. [(accessed on 6 January 2025)]. Available online: https://ros.org/

The Open Source Robotics Foundation Micro ROS. 2025. [(accessed on 6 January 2025)]. Available online: https://micro.ros.org/

Aleem S., Ahmed F., Batool R., Khattak A. Empirical Investigation of Key Factors for SaaS Architecture. IEEE Trans. Cloud Comput. 2021;9:1037–1049. doi: 10.1109/TCC.2019.2906299. DOI

Saraswat M., Tripathi R. Cloud Computing: Analysis of Top 5 CSPs in SaaS, PaaS and IaaS Platforms; Proceedings of the 9th International Conference on System Modeling & Advancement in Research Trends (SMART); Moradabad, India. 4–5 December 2020; Piscataway, NJ, USA: IEEE; 2020. pp. 300–305. DOI

Kim J.H., Starr J.W., Lattimer B.Y. Firefighting Robot Stereo Infrared Vision and Radar Sensor Fusion for Imaging through Smoke. Fire Technol. 2015;51:823–845. doi: 10.1007/s10694-014-0413-6. DOI

The MathWorks, Inc MATLAB–The Language of Technical Computing. 2025. [(accessed on 6 January 2025)]. Available online: https://www.mathworks.com/products/matlab.html.

Mangiaracina G., Plebani P., Salnitri M., Vitali M. Efficient Data as a Service in Fog Computing: An Adaptive Multi-Agent Based Approach. IEEE Trans. Cloud Comput. 2022;11:2646–2663. doi: 10.1109/TCC.2022.3220811. DOI

Soori M., Arezoo B., Dastres R. Artificial intelligence, machine learning and deep learning in advanced robotics, a review. Cogn. Robot. 2023;3:54–70. doi: 10.1016/j.cogr.2023.04.001. DOI

Jeong H., Lee H., Kim C., Shin S. A Survey of Robot Intelligence with Large Language Models. Appl. Sci. 2024;14:8868. doi: 10.3390/app14198868. DOI

Cao S., Parviziomran I., Yang H., Park S., Won D. Prediction of component shifts in pick and place process of surface mount technology using support vector regression. Procedia Manuf. 2019;39:210–217. doi: 10.1016/j.promfg.2020.01.316. DOI

Ullah I., Adhikari D., Khan H., Anwar M.S., Ahmad S., Bai X. Mobile robot localization: Current challenges and future prospective. Comput. Sci. Rev. 2024;53:100651. doi: 10.1016/j.cosrev.2024.100651. DOI

TensorFlow TensorFlow Learn. [(accessed on 26 January 2025)]. Available online: https://www.tensorflow.org/learn.

Abadi M., Barham P., Chen J., Chen Z., Davis A., Dean J., Devin M., Ghemawat S., Irving G., Isard M., et al. TensorFlow: A system for large-scale machine learning; Proceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI 16); Savannah, GA, USA. 2–4 November 2016; pp. 265–283.

Chollet, F. & contributors. Keras. 2015. [(accessed on 9 March 2023)]. Available online: https://keras.io/

Paszke A., Gross S., Chintala S., Chanan G., Yang E., DeVito Z., Lin Z., Desmaison A., Antiga L., Lerer A. PyTorch: An Imperative Style, High-Performance Deep Learning Library. 2019. [(accessed on 9 March 2023)]. Available online: https://pytorch.org/

Pedregosa F., Varoquaux G., Gramfort A., Michel V., Thirion B., Grisel O., Blondel M., Prettenhofer P., Weiss R., Dubourg V., et al. Scikit-Learn: Machine Learning in Python. 2011. [(accessed on 22 March 2023)]. Available online: https://scikit-learn.org/

Hall M., Frank E., Holmes G., Pfahringer B., Reutemann P., Witten I.H. Weka: Data Mining Software in Java. 2009. [(accessed on 22 March 2023)]. Available online: https://www.cs.waikato.ac.nz/ml/weka/

Python Software Foundation Python. 2023. [(accessed on 9 March 2023)]. Available online: https://www.python.org/

R Core Team R: A Language and Environment for Statistical Computing. 2022. [(accessed on 9 March 2023)]. Available online: https://www.r-project.org/

The Julia Language Julia. 2023. [(accessed on 9 March 2023)]. Available online: https://julialang.org/

Krejčí J., Babiuch M., Babjak J., Suder J., Wierbica R. Implementation of an Embedded System into the Internet of Robotic Things. Micromachines. 2022;14:113. doi: 10.3390/mi14010113. PubMed DOI PMC

Kasiviswanathan S., Gnanasekaran S., Thangamuthu M., Rakkiyannan J. Machine-Learning- and Internet-of-Things-Driven Techniques for Monitoring Tool Wear in Machining Process: A Comprehensive Review. J. Sens. Actuator Netw. 2024;13:53. doi: 10.3390/jsan13050053. DOI

Tubis A.A., Rohman J. Intelligent Warehouse in Industry 4.0—Systematic Literature Review. Sensors. 2023;23:4105. doi: 10.3390/s23084105. PubMed DOI PMC

Singh H., Veeraiah V., Khan H., Kumar D., Talukdar V., Anand R., Sindhwani N. Robotics and Automation in Industry 4.0. Volume 1–2. CRC Press; Boca Raton, FL, USA: 2024. Investigating Scope and Applications for the Internet of Robotics in Industrial Automation; pp. 132–151. DOI

Srivastava S.K., Bag S. Recent Developments on Flexible Manufacturing in the Digital Era: A Review and Future Research Directions. Glob. J. Flex. Syst. Manag. 2023;24:483–516. doi: 10.1007/s40171-023-00351-2. DOI

Kalsoom T., Ramzan N., Ahmed S., Ur-Rehman M. Advances in Sensor Technologies in the Era of Smart Factory and Industry 4.0. Sensors. 2020;20:6783. doi: 10.3390/s20236783. PubMed DOI PMC

Maddikunta P.K.R., Pham Q.V., B P., Deepa N., Dev K., Gadekallu T.R., Ruby R., Liyanage M. Industry 5.0: A survey on enabling technologies and potential applications. J. Ind. Inf. Integr. 2022;26:100257. doi: 10.1016/j.jii.2021.100257. DOI

Li C., Zheng P., Yin Y., Wang B., Wang L. Deep reinforcement learning in smart manufacturing: A review and prospects. CIRP J. Manuf. Sci. Technol. 2023;40:75–101. doi: 10.1016/j.cirpj.2022.11.003. DOI

Carrese F., Sportiello S., Zhaksylykov T., Colombaroni C., Carrese S., Papaveri M., Patella S.M. The Integration of Shared Autonomous Vehicles in Public Transportation Services: A Systematic Review. Sustainability. 2023;15:13023. doi: 10.3390/su151713023. DOI

Oladimeji D., Gupta K., Kose N.A., Gundogan K., Ge L., Liang F. Smart Transportation: An Overview of Technologies and Applications. Sensors. 2023;23:3880. doi: 10.3390/s23083880. PubMed DOI PMC

Alverhed E., Hellgren S., Isaksson H., Olsson L., Palmqvist H., Flodén J. Autonomous last-mile delivery robots: A literature review. Eur. Transp. Res. Rev. 2024;16:4. doi: 10.1186/s12544-023-00629-7. DOI

Mukta M.Y., Rahman M.A., Asyhari A.T., Alam Bhuiyan M.Z. IoT for energy efficient green highway lighting systems: Challenges and issues. J. Netw. Comput. Appl. 2020;158:102575. doi: 10.1016/j.jnca.2020.102575. DOI

Chaudhari P., Xiao Y., Cheng M.M.C., Li T. Fundamentals, Algorithms, and Technologies of Occupancy Detection for Smart Buildings Using IoT Sensors. Sensors. 2024;24:2123. doi: 10.3390/s24072123. PubMed DOI PMC

Fang B., Yu J., Chen Z., Osman A.I., Farghali M., Ihara I., Hamza E.H., Rooney D.W., Yap P.S. Artificial intelligence for waste management in smart cities: A review. Environ. Chem. Lett. 2023;21:1959–1989. doi: 10.1007/s10311-023-01604-3. PubMed DOI PMC

Kim H., Choi H., Kang H., An J., Yeom S., Hong T. A systematic review of the smart energy conservation system: From smart homes to sustainable smart cities. Renew. Sustain. Energy Rev. 2021;140:110755. doi: 10.1016/j.rser.2021.110755. DOI

Nguyen D.C., Ding M., Pathirana P.N., Seneviratne A., Li J., Vincent Poor H. Federated Learning for Internet of Things: A Comprehensive Survey. IEEE Commun. Surv. Tutor. 2021;23:1622–1658. doi: 10.1109/COMST.2021.3075439. DOI

Jiang J.C., Kantarci B., Oktug S., Soyata T. Federated learning in smart city sensing: Challenges and opportunities. Sensors. 2020;20:6230. doi: 10.3390/s20216230. PubMed DOI PMC

Dritsas E., Trigka M. Machine Learning for Blockchain and IoT Systems in Smart Cities: A Survey. Future Internet. 2024;16:324. doi: 10.3390/fi16090324. DOI

Gebbers R., Adamchuk V.I. Precision agriculture and food security. Science. 2010;327:828–831. doi: 10.1126/science.1183899. PubMed DOI

Dhanaraju M., Chenniappan P., Ramalingam K., Pazhanivelan S., Kaliaperumal R. Smart Farming: Internet of Things (IoT)-Based Sustainable Agriculture. Agriculture. 2022;12:1745. doi: 10.3390/agriculture12101745. DOI

Navarro E., Costa N., Pereira A. A systematic review of iot solutions for smart farming. Sensors. 2020;20:4231. doi: 10.3390/s20154231. PubMed DOI PMC

Tang Y., Dananjayan S., Hou C., Guo Q., Luo S., He Y. A survey on the 5G network and its impact on agriculture: Challenges and opportunities. Comput. Electron. Agric. 2021;180:105895. doi: 10.1016/j.compag.2020.105895. DOI

Jan F., Min-Allah N., Düştegör D. IoT based smart water quality monitoring: Recent techniques, trends and challenges for domestic applications. Water. 2021;13:1729. doi: 10.3390/w13131729. DOI

Sharma A., Jain A., Gupta P., Chowdary V. Machine Learning Applications for Precision Agriculture: A Comprehensive Review. IEEE Access. 2021;9:4843–4873. doi: 10.1109/ACCESS.2020.3048415. DOI

Ecke S., Dempewolf J., Frey J., Schwaller A., Endres E., Klemmt H.J., Tiede D., Seifert T. UAV-Based Forest Health Monitoring: A Systematic Review. Remote Sens. 2022;14:3205. doi: 10.3390/rs14133205. DOI

Islam M.Z., Sagar A.S.M.S., Kim H.S. Enabling Pandemic-Resilient Healthcare: Edge-Computing-Assisted Real-Time Elderly Caring Monitoring System. Appl. Sci. 2024;14:8486. doi: 10.3390/app14188486. DOI

Salama R., Al-Turjman F., Chaudhary P., Yadav S.P. Benefits of Internet of Things (IoT) Applications in Health care—An Overview; Proceedings of the 2023 International Conference on Computational Intelligence, Communication Technology and Networking (CICTN); Ghaziabad, India. 20–21 April 2023; pp. 778–784. DOI

Peters B.S., Armijo P.R., Krause C., Choudhury S.A., Oleynikov D. Review of emerging surgical robotic technology. Surg. Endosc. 2018;32:1636–1655. doi: 10.1007/s00464-018-6079-2. PubMed DOI

Dupont P.E., Nelson B.J., Goldfarb M., Hannaford B., Menciassi A., O’Malley M.K., Simaan N., Valdastri P., Yang G.Z. A decade retrospective of medical robotics research from 2010 to 2020. Sci. Robot. 2021;6:eabi8017. doi: 10.1126/scirobotics.abi8017. PubMed DOI PMC

Soto F., Wang J., Ahmed R., Demirci U. Medical Micro/Nanorobots in Precision Medicine. Adv. Sci. 2020;7:2002203. doi: 10.1002/advs.202002203. PubMed DOI PMC

Gifari M.W., Naghibi H., Stramigioli S., Abayazid M. A review on recent advances in soft surgical robots for endoscopic applications. Int. J. Med Robot. Comput. Assist. Surg. 2019;15:e2010. doi: 10.1002/rcs.2010. PubMed DOI PMC

Thalman C., Artemiadis P. A review of soft wearable robots that provide active assistance: Trends, common actuation methods, fabrication, and applications. Wearable Technol. 2020;1:e3. doi: 10.1017/wtc.2020.4. PubMed DOI PMC

Vélez-guerrero M.A., Callejas-cuervo M., Mazzoleni S. Artificial intelligence-based wearable robotic exoskeletons for upper limb rehabilitation: A review. Sensors. 2021;21:2146. doi: 10.3390/s21062146. PubMed DOI PMC

Chitikena H., Sanfilippo F., Ma S. Robotics in Search and Rescue (SAR) Operations: An Ethical and Design Perspective Framework for Response Phase. Appl. Sci. 2023;13:1800. doi: 10.3390/app13031800. DOI

Battistuzzi L., Recchiuto C., Sgorbissa A. Ethical concerns in rescue robotics: A scoping review. Ethics Inf. Technol. 2021;23:863–875. doi: 10.1007/s10676-021-09603-0. DOI

Sepasgozar S., Karimi R., Farahzadi L., Moezzi F., Shirowzhan S.M., Ebrahimzadeh S., Hui F., Aye L. A Systematic Content Review of Artificial Intelligence and the Internet of Things Applications in Smart Home. Appl. Sci. 2020;10:3074. doi: 10.3390/app10093074. DOI

Maswadi K., Ghani N.B.A., Hamid S.B. Systematic Literature Review of Smart Home Monitoring Technologies Based on IoT for the Elderly. IEEE Access. 2020;8:92244–92261. doi: 10.1109/ACCESS.2020.2992727. DOI

Song Y., Yu F.R., Zhou L., Yang X., He Z. Applications of the Internet of Things (IoT) in Smart Logistics: A Comprehensive Survey. IEEE Internet Things J. 2021;8:4250–4274. doi: 10.1109/JIOT.2020.3034385. DOI

Tang Y., Zhao C., Wang J., Zhang C., Sun Q., Zheng W.X., Du W., Qian F., Kurths J. Perception and Navigation in Autonomous Systems in the Era of Learning: A Survey. IEEE Trans. Neural Netw. Learn. Syst. 2023;34:9604–9624. doi: 10.1109/TNNLS.2022.3167688. PubMed DOI

Dorigo M., Theraulaz G., Trianni V. Swarm Robotics: Past, Present, and Future [Point of View] Proc. IEEE. 2021;109:1152–1165. doi: 10.1109/JPROC.2021.3072740. DOI

Khorasani M., Loy J., Ghasemi A.H., Sharabian E., Leary M., Mirafzal H., Cochrane P., Rolfe B., Gibson I. A review of Industry 4.0 and additive manufacturing synergy. Rapid Prototyp. J. 2022;28:1462–1475. doi: 10.1108/RPJ-08-2021-0194. DOI

Hu K., Zou L., Chen Z., Jiang J., Jiang F., Tao X. Wireless Multi-Robot Collaboration: Communications, Perception, Control and Planning. IEEE Netw. 2024 doi: 10.1109/MNET.2024.3483829. DOI

Anusha S., Ezhilvandan M., Gayathri S., Sivaraman V., Anish T., Siva Subramanian R. AI Innovations in Service and Tourism Marketing. IGI Global; Hershey, PA, USA: 2024. Emerging trends in edge AI for Industry 4.0 and 5.0: Technologies, applications, and challenges; pp. 211–228. DOI

Bouzarkouna I., Sahnoun M., Bettayeb B., Baudry D., Gout C. Optimal Deployment of Fog-Based Solution for Connected Devices in Smart Factory. IEEE Trans. Ind. Inform. 2024;20:5137–5146. doi: 10.1109/TII.2023.3330336. DOI

Shata E., Chen B., Hu L., Seskar I., Guo Y., Mahmoudi C., Shekhar S., Zou Q. 5G-Cloud-based real-time robotic part repairing for advanced manufacturing via computer vision. Manuf. Lett. 2024;41:1398–1404. doi: 10.1016/j.mfglet.2024.09.166. DOI

Mohammad Z., Qattam T.A., Saleh K. Security weaknesses and attacks on the internet of things applications; Proceedings of the 2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT); Amman, Jordan. 9–11 April 2019; pp. 431–436. DOI

Almazroi A.A. Security mechanism in the internet of things by interacting HTTP and MQTT protocols; Proceedings of the 2019 IEEE 11th International Conference on Communication Software and Networks (ICCSN); Chongqing, China. 12–15 June 2019; pp. 181–186. DOI

Dutta V., Zielińska T. Cybersecurity of Robotic Systems: Leading Challenges and Robotic System Design Methodology. Electronics. 2021;10:2850. doi: 10.3390/electronics10222850. DOI

Zafir E.I., Akter A., Islam M., Hasib S.A., Islam T., Sarker S.K., Muyeen S. Enhancing security of Internet of Robotic Things: A review of recent trends, practices, and recommendations with encryption and blockchain techniques. Internet Things. 2024;28:101357. doi: 10.1016/j.iot.2024.101357. DOI

Tanimu J.A., Abada W. Addressing cybersecurity challenges in robotics: A comprehensive overview. Cyber Secur. Appl. 2025;3:100074. doi: 10.1016/j.csa.2024.100074. DOI

Younas M.I., Iqbal M.J., Aziz A., Sodhro A.H. Toward QoS Monitoring in IoT Edge Devices Driven Healthcare—A Systematic Literature Review. Sensors. 2023;23:8885. doi: 10.3390/s23218885. PubMed DOI PMC

Mazhar T., Malik M.A., Mohsan S.A.H., Li Y., Haq I., Ghorashi S., Karim F.K., Mostafa S.M. Quality of Service (QoS) Performance Analysis in a Traffic Engineering Model for Next-Generation Wireless Sensor Networks. Symmetry. 2023;15:513. doi: 10.3390/sym15020513. DOI

Sahoo S., Sahoo S., Kabat M. A Pragmatic Review of QoS Optimisations in IoT Driven Networks. Wirel. Pers. Commun. 2024;137:325–366. doi: 10.1007/s11277-024-11412-9. DOI

An X., Wu C., Lin Y., Lin M., Yoshinaga T., Ji Y. Multi-Robot Systems and Cooperative Object Transport: Communications, Platforms, and Challenges. IEEE Open J. Comput. Soc. 2023;4:23–36. doi: 10.1109/OJCS.2023.3238324. DOI

Corradini F., Pettinari S., Re B., Ruschioni L., Tiezzi F. ER2023: Companion, Proceedings of the 42nd International Conference on Conceptual Modeling: ER Forum, 7th SCME, Project Exhibitions, Posters and Demos, and Doctoral Consortium, Lisbon, Portugal, 6–9 November 2023. Volume 3618 Rheinisch Westfälische Technische Hochschule; Aachen, Germany: 2023. Enhancing compatibility in QoS communication for the Internet of Robotic Things.

Dey E., Walczak M., Anwar M.S., Roy N., Freeman J., Gregory T., Suri N., Busart C. A Novel ROS2 QoS Policy-Enabled Synchronizing Middleware for Co-Simulation of Heterogeneous Multi-Robot Systems; Proceedings of the 2023 32nd International Conference on Computer Communications and Networks (ICCCN); Honolulu, HI, USA. 24–27 July 2023; pp. 1–10. DOI

Pasricha S., Ayoub R., Kishinevsky M., Mandal S.K., Ogras U.Y. A Survey on Energy Management for Mobile and IoT Devices. IEEE Des. Test. 2020;37:7–24. doi: 10.1109/MDAT.2020.2976669. DOI

Siderska J., Aunimo L., Süße T., von Stamm J., Kedziora D., Aini S.N.B.M. Towards Intelligent Automation (IA): Literature review on the evolution of Robotic Process Automation (RPA), its challenges, and future trends. Eng. Manag. Prod. Serv. 2023;15:90–103. doi: 10.2478/emj-2023-0030. DOI

van der Aalst W.M.P., Bichler M., Heinzl A. Robotic Process Automation. Bus. Inf. Syst. Eng. 2018;60:269–272. doi: 10.1007/s12599-018-0542-4. DOI

Maraveas C. Incorporating Artificial Intelligence Technology in Smart Greenhouses: Current State of the Art. Appl. Sci. 2023;13:14. doi: 10.3390/app13010014. DOI

Sutikno T. The future of artificial intelligence-driven robotics: Applications and implications. IAES Int. J. Robot. Autom. 2024;13:361–372. doi: 10.11591/ijra.v13i4.pp361-372. DOI

Shahraki A., Haugen Ø. Social ethics in Internet of Things: An outline and review; Proceedings of the 2018 IEEE Industrial Cyber-Physical Systems (ICPS); St. Petersburg, Russia. 15–18 May 2018; pp. 509–516. DOI

Chamola V., Hassija V., Sulthana A.R., Ghosh D., Dhingra D., Sikdar B. A Review of Trustworthy and Explainable Artificial Intelligence (XAI) IEEE Access. 2023;11:78994–79015. doi: 10.1109/ACCESS.2023.3294569. DOI

Barata J., Kayser I. Industry 5.0–Past, Present, and Near Future. Procedia Comput. Sci. 2023;219:778–788. doi: 10.1016/j.procs.2023.01.351. DOI

Zhang C., Wang Z., Zhou G., Chang F., Ma D., Jing Y., Cheng W., Ding K., Zhao D. Towards new-generation human-centric smart manufacturing in Industry 5.0: A systematic review. Adv. Eng. Inform. 2023;57:102121. doi: 10.1016/j.aei.2023.102121. DOI

Liang P., Sun X., Qi L. Does artificial intelligence technology enhance green transformation of enterprises: Based on green innovation perspective. Environ. Dev. Sustain. 2024;26:21651–21687. doi: 10.1007/s10668-023-04225-6. DOI

Orr J., Dutta A. Multi-Agent Deep Reinforcement Learning for Multi-Robot Applications: A Survey. Sensors. 2023;23:3625. doi: 10.3390/s23073625. PubMed DOI PMC

Iftikhar S., Gill S.S., Song C., Xu M., Aslanpour M.S., Toosi A.N., Du J., Wu H., Ghosh S., Chowdhury D., et al. AI-based fog and edge computing: A systematic review, taxonomy and future directions. Internet Things. 2023;21:100674. doi: 10.1016/j.iot.2022.100674. DOI

Gkagkas G., Vergados D.J., Michalas A., Dossis M. The Advantage of the 5G Network for Enhancing the Internet of Things and the Evolution of the 6G Network. Sensors. 2024;24:2455. doi: 10.3390/s24082455. PubMed DOI PMC

Lessi C.C., Gavrielides A., Solina V., Qiu R., Nicoletti L., Li D. 5G and Beyond 5G Technologies Enabling Industry 5.0: Network Applications for Robotics. Procedia Comput. Sci. 2024;232:675–687. doi: 10.1016/j.procs.2024.01.067. DOI

Tian W., Gu C., Guo M., He S., Kang J., Niyato D., Chen J. Large-Scale Deterministic Networks: Architecture, Enabling Technologies, Case Study, and Future Directions. IEEE Netw. 2024;38:284–291. doi: 10.1109/MNET.2024.3355116. DOI

Ferdaus M.M., Dam T., Anavatti S., Das S. Digital technologies for a net-zero energy future: A comprehensive review. Renew. Sustain. Energy Rev. 2024;202:114681. doi: 10.1016/j.rser.2024.114681. DOI

Pizoń J., Gola A. Human–Machine Relationship—Perspective and Future Roadmap for Industry 5.0 Solutions. Machines. 2023;11:203. doi: 10.3390/machines11020203. DOI

Xiang W., Yu K., Han F., Fang L., He D., Han Q.L. Advanced Manufacturing in Industry 5.0: A Survey of Key Enabling Technologies and Future Trends. IEEE Trans. Ind. Inform. 2024;20:1055–1068. doi: 10.1109/TII.2023.3274224. DOI

Alojaiman B. Technological Modernizations in the Industry 5.0 Era: A Descriptive Analysis and Future Research Directions. Processes. 2023;11:1318. doi: 10.3390/pr11051318. DOI

Golovianko M., Terziyan V., Branytskyi V., Malyk D. Industry 4.0 vs. Industry 5.0: Co-existence, Transition, or a Hybrid. Procedia Comput. Sci. 2023;217:102–113. doi: 10.1016/j.procs.2022.12.206. DOI

Mäntymäki M., Minkkinen M., Birkstedt T., Viljanen M. Putting AI Ethics into practice: The hourglass model of organizational AI governance. arXiv. 20222206.00335

Birkstedt T., Minkkinen M., Tandon A., Mäntymäki M. AI governance: Themes, knowledge gaps and future agendas. Internet Res. 2023;33:133–167. doi: 10.1108/INTR-01-2022-0042. DOI

Botta A., Rotbei S., Zinno S., Ventre G. Cyber security of robots: A comprehensive survey. Intell. Syst. Appl. 2023;18:200237. doi: 10.1016/j.iswa.2023.200237. DOI

Najít záznam

Citační ukazatele

Nahrávání dat ...

Možnosti archivace

Nahrávání dat ...