Industrial Internet of Things: Challenges, Opportunities, and Directions
Abstract
Internet of Things (IoT) is an emerging domain that promises ubiquitous connection to the Internet, turning common objects into connected devices. The IoT paradigm is changing the way people interact with things around them. It paves the way for creating pervasively connected infrastructures to support innovative services and promises better flexibility and efficiency. Such advantages are attractive not only for consumer applications, but also for the industrial domain. Over the last few years, we have been witnessing the IoT paradigm making its way into the industry marketplace with purposely designed solutions. In this paper, we clarify the concepts of IoT, Industrial IoT, and Industry 4.0. We highlight the opportunities brought in by this paradigm shift as well as the challenges for its realization. In particular, we focus on the challenges associated with the need of energy efficiency, real-time performance, coexistence, interoperability, and security and privacy. We also provide a systematic overview of the state-of-the-art research efforts and potential research directions to solve Industrial IoT challenges.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The physical isolation model of OT security has eroded rapidly.
“This model has eroded rapidly.[5], [29]”
From Zero Trust Architecture for Smart Factories: Securing Digital Twins and Cyber-Physical OT Systems (2026) · cites this paper as [29]
Early industrial control systems employed proprietary fieldbus protocols PROFIBUS, Modbus, and DNP3 over dedicated hardware links largely inaccessible to adversaries without physical proximity.
“Early industrial control systems employed proprietary fieldbus protocols PROFIBUS, Modbus, and DNP3 over dedicated hardware links largely inaccessible to adversaries without physical proximity.[29], [12]”
From Zero Trust Architecture for Smart Factories: Securing Digital Twins and Cyber-Physical OT Systems (2026) · cites this paper as [29]
Operational Technology security has historically relied on the physical isolation paradigm.
“Operational Technology security has historically relied on the physical isolation paradigm.”
From Zero Trust Architecture for Smart Factories: Securing Digital Twins and Cyber-Physical OT Systems (2026) · cites this paper as [29]
Edge gateways authenticate the originating device via mutual TLS (mTLS), verify each telemetry payload's digital signature, and forward only cryptographically verified payloads to the transport layer.
“Edge gateways perform the first verification step: they authenticate the originating device via mutual TLS (mTLS), verify each telemetry payload's digital signature, and forward only cryptographically verified payloads to the transport layer.[29]”
From Zero Trust Architecture for Smart Factories: Securing Digital Twins and Cyber-Physical OT Systems (2026) · cites this paper as [29]
When mobile edge computing (MEC) is used, it makes network congestion worse, especially for tasks requiring a lot of data bits, which could result in task failure and a long queue.
“When mobile edge computing (MEC) is used, it makes network congestion worse, especially for tasks requiring a lot of data bits, which could result in task failure and a long queue [36].”
From A Critical Overview of Industrial Internet of Things Security and Privacy Issues Using a Layer-Based Hacking Scenario (2023) · cites this paper as [36]
PI organizes data around named tags inside asset hierarchies; enterprise systems organize data around relational keys and dimensional models.
“PI organizes data around named tags inside asset hierarchies; enterprise systems organize data around relational keys and dimensional models.”
From Data Observability Framework for Mission-Critical Industrial ETL Pipelines: Anomaly Detection, SLA Modeling, and Proactive Failure Identification (2026) · cites this paper as [7]
Cites
The Internet of Things: A survey
Atzori, L., Iera, A., & Morabito, G. (2010) · Computer Networks · doi:10.1016/j.comnet.2010.05.010 · Cited by 15,613 · see citing works
Internet of Things (IoT): A vision, architectural elements, and future directions
Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013) · Future Generation Computer Systems · doi:10.1016/j.future.2013.01.010 · Cited by 12,293 · see citing works
Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications
Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., & Ayyash, M. (2015) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2015.2444095 · Cited by 8,630 · see citing works
Internet of Things in industries: A survey
Xu, L. D., He, W., & Li, S. (2014) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2014.2300753 · Cited by 5,172 · see citing works
Closing yield gaps through nutrient and water management
Mueller, N. D., Gerber, J., Johnston, M., Ray, D. K., Ramankutty, N., & Foley, J. A. (2012) · Nature · doi:10.1038/nature11420 · Cited by 2,832 · see citing works
Wollschlaeger, M., Sauter, T., & Jasperneite, J. (2017) · IEEE Industrial Electronics Magazine · doi:10.1109/mie.2017.2649104 · Cited by 1,726 · see citing works
Internet of Things: Applications and Challenges in Technology and Standardization
Bandyopadhyay, D., & Sen, J. (2011) · Wireless Personal Communications · doi:10.1007/s11277-011-0288-5 · Cited by 1,507 · see citing works
Internet of Things in the 5G Era: Enablers, Architecture, and Business Models
Palattella, M. R., Dohler, M., Grieco, A., Rizzo, G., Torsner, J., Engel, T., & Ladid, L. (2016) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2016.2525418 · Cited by 1,459 · see citing works
Energy efficiency in wireless sensor networks: A top-down survey
Rault, T., Bouabdallah, A., & Challal, Y. (2014) · Computer Networks · doi:10.1016/j.comnet.2014.03.027 · Cited by 936 · see citing works
Security and privacy challenges in industrial internet of things
Sadeghi, A., Wachsmann, C., & Waidner, M. (2015) · Proceedings - ACM IEEE Design Automation Conference · doi:10.1145/2744769.2747942 · Cited by 920 · see citing works
IoT Security: Ongoing Challenges and Research Opportunities
Zhang, Z., Cho, M. C. Y., Wang, C., Hsu, C.-W., Chen, C.-K., & Shieh, S. W. (2014) · IEEE International Conference on Service-Oriented Computing and Applications (SOCA) · doi:10.1109/soca.2014.58 · Cited by 746 · see citing works
DNS Security Introduction and Requirements
Arends, R., Austein, R., Larson, M., et al. (2005) · doi:10.17487/rfc4033 · Cited by 683 · see citing works
An overview of the Internet of Things for people with disabilities
Domingo, M. C. (2012) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2011.10.015 · Cited by 638 · see citing works
WirelessHART: Applying Wireless Technology in Real-Time Industrial Process Control
Song, J., Han, S., Mok, A., Chen, D., Lucas, M., Nixon, M. S., & Pratt, W. (2008) · IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS) · doi:10.1109/rtas.2008.15 · Cited by 619 · see citing works
Self-citationPrivacy in the Internet of Things: threats and challenges
Ziegeldorf, J. H., Morchon, O. G., & Wehrle, K. (2013) · Security and Communication Networks · doi:10.1002/sec.795 · Cited by 613 · see citing works
RFID technology and its applications in Internet of Things (IoT)
Jia, X., Feng, Q., Fan, T., & Lei, Q. (2012) · International Conference on Consumer Electronics, Communications and Networks (CECNet) · doi:10.1109/cecnet.2012.6201508 · Cited by 542 · see citing works
Reference Architectures for the Internet of Things
Weyrich, M., & Ebert, C. (2016) · IEEE Software · doi:10.1109/ms.2016.20 · Cited by 446 · see citing works
Real-Time Wireless Sensor-Actuator Networks for Industrial Cyber-Physical Systems
Lu, C., Saifullah, A., Li, B., Sha, M., González, H., Gunatilaka, D., Wu, C., Nie, L., & Chen, Y. (2015) · Proceedings of the IEEE · doi:10.1109/jproc.2015.2497161 · Cited by 391 · see citing works
Self-citationSecurity Challenges in the IP-based Internet of Things
Heer, T., García-Morchón, Ó., Hummen, R., Keoh, S. L., Kumar, S., & Wehrle, K. (2011) · Wireless Personal Communications · doi:10.1007/s11277-011-0385-5 · Cited by 378 · see citing works
IoT-based real-time production logistics synchronization system under smart cloud manufacturing
Qu, T., Lei, S. P., Wang, Z. Z., et al. (2015) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-015-7220-1 · Cited by 360 · see citing works
Future research challenges in wireless sensor and actuator networks targeting industrial automation
Åkerberg, J., Gidlund, M., & Björkman, M. (2011) · 2022 IEEE 20th International Conference on Industrial Informatics (INDIN) · doi:10.1109/indin.2011.6034912 · Cited by 344 · see citing works
Self-citationO’Donovan, P., Leahy, K., Bruton, K., & O’Sullivan, D. T. J. (2015) · Journal Of Big Data · doi:10.1186/s40537-015-0034-z · Cited by 313 · see citing works
Coexistence of IEEE802.15.4 with other Systems in the 2.4 GHz-ISM-Band
Sikora, A., & Groza, V. F. (2006) · Conference proceedings - IEEE Instrumentation/Measurement Technology Conference · doi:10.1109/imtc.2005.1604479 · Cited by 280 · see citing works
Real-Time Scheduling for WirelessHART Networks
Saifullah, A. M., Xu, Y., Lu, C., et al. (2010) · Proceedings/Proceedings - Real-Time Systems Symposium · doi:10.1109/rtss.2010.41 · Cited by 279 · see citing works
Self-citationA state-of-the-art survey of cloud manufacturing
He, W., & Xu, L. (2014) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2013.874595 · Cited by 234 · see citing works
Kim, S. M., & He, T. (2015) · Proceedings of the 28th Annual International Conference on Mobile Computing And Networking · doi:10.1145/2789168.2790098 · Cited by 229 · see citing works
Evaluation of the IoT LoRaWAN Solution for Distributed Measurement Applications
Rizzi, M., Ferrari, P., Flammini, A., & Sisinni, E. (2017) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2017.2746378 · Cited by 212 · see citing works
Self-citationSoil macronutrient sensing for precision agriculture
Kim, H.-J., Sudduth, K. A., & Hummel, J. W. (2009) · Journal of Environmental Monitoring · doi:10.1039/b906634a · Cited by 211 · see citing works
Reliable and Real-Time Communication in Industrial Wireless Mesh Networks
Han, S., Zhu, X., Mok, A. K., et al. (2011) · Proceedings - Real-Time Technology and Applications Symposium · doi:10.1109/rtas.2011.9 · Cited by 206 · see citing works
Self-citationToward better horizontal integration among IoT services
Al‐Fuqaha, A., Khreishah, A. A., Guizani, M., Rayes, A., & Mohammadi, M. (2015) · IEEE Communications Magazine · doi:10.1109/mcom.2015.7263375 · Cited by 198 · see citing works
Narrowband Wireless Access for Low-Power Massive Internet of Things: A Bandwidth Perspective
Yang, W., Wang, M., Zhang, J., Zou, J., Hua, M., Xia, T., & You, X. (2017) · IEEE Wireless Communications · doi:10.1109/mwc.2017.1600298 · Cited by 190 · see citing works
Scheduling Efficiency of Distributed Greedy Scheduling Algorithms in Wireless Networks
Wu, X., Srikant, R., & Perkins, J. R. (2007) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2007.1061 · Cited by 186 · see citing works
Distributed fair scheduling in a wireless LAN
Vaidya, N. H., Dugar, A., Gupta, S., et al. (2005) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2005.87 · Cited by 180 · see citing works
Threat-Based Security Analysis for the Internet of Things
Atamli, A. W., & Martin, A. (2014) · 2014 International Workshop on Secure Internet of Things · doi:10.1109/siot.2014.10 · Cited by 169 · see citing works
Semantic Interoperability Architecture for Pervasive Computing and Internet of Things
Kiljander, J., D'elia, A., Morandi, F., Hyttinen, P., Takalo-Mattila, J., Ylisaukko-Oja, A., Soininen, J.-P., & Cinotti, T. S. (2014) · IEEE Access · doi:10.1109/access.2014.2347992 · Cited by 166 · see citing works
Efficient naming, addressing and profile services in Internet-of-Things sensory environments
Liu, C. H., Yang, B. S., & Liu, T. (2013) · Ad Hoc Networks · doi:10.1016/j.adhoc.2013.02.008 · Cited by 153 · see citing works
Using Cognitive Radio for Interference-Resistant Industrial Wireless Sensor Networks: An Overview
Chiwewe, T. M., Mbuya, C. F., & Hancke, G. P. (2015) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2015.2491267 · Cited by 153 · see citing works
Low-Complexity Distributed Scheduling Algorithms for Wireless Networks
Gupta, A., Lin, X., & Srikant, R. (2009) · IEEE/ACM Transactions on Networking · doi:10.1109/tnet.2009.2021609 · Cited by 152 · see citing works
Wei, Y.-H., Leng, Q., Han, S., et al. (2013) · Proceedings/Proceedings - Real-Time Systems Symposium · doi:10.1109/rtss.2013.22 · Cited by 144 · see citing works
Self-citationNB-IoT Technology Overview and Experience from Cloud-RAN Implementation
Beyene, Y. D., Jäntti, R., Tirkkonen, O., et al. (2017) · IEEE Wireless Communications · doi:10.1109/mwc.2017.1600418 · Cited by 141 · see citing works
End-to-End Communication Delay Analysis in Industrial Wireless Networks
Saifullah, A. M., Xu, Y., Lu, C., et al. (2014) · IEEE Transactions on Computers · doi:10.1109/tc.2014.2322609 · Cited by 134 · see citing works
Self-citationUsing LoRa for industrial wireless networks
Rizzi, M., Ferrari, P., Flammini, A., Sisinni, E., & Gidlund, M. (2017) · IEEE International Workshop on Factory Communication Systems (WFCS) · doi:10.1109/wfcs.2017.7991972 · Cited by 128 · see citing works
Self-citationIsmail, D., Rahman, M., & Saifullah, A. M. (2018) · International Conference on Distributed Computing and Networking (ICDCN) · doi:10.1145/3170521.3170529 · Cited by 121 · see citing works
Self-citationDelay Estimation of Industrial IoT Applications Based on Messaging Protocols
Ferrari, P., Flammini, A., Sisinni, E., Rinaldi, S., Brandão, D., & Rocha, M. S. (2018) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2018.2813798 · Cited by 119 · see citing works
Self-citationEnd-to-End Reliability-Aware Scheduling for Wireless Sensor Networks
Dobslaw, F., Zhang, T., & Gidlund, M. (2014) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2014.2382335 · Cited by 115 · see citing works
Self-citationWireless Coexistence between IEEE 802.11- and IEEE 802.15.4-Based Networks: A Survey
Yang, D., Xu, Y., & Gidlund, M. (2011) · International Journal of Distributed Sensor Networks · doi:10.1155/2011/912152 · Cited by 103 · see citing works
Self-citationFlatt, H., Schriegel, S., Jasperneite, J., Trsek, H., & Adamczyk, H. (2016) · IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) · doi:10.1109/etfa.2016.7733634 · Cited by 101 · see citing works
RERUM: Building a reliable IoT upon privacy- and security- enabled smart objects
Pöhls, H. C., Angelakis, V., Suppan, S., Fischer, K., Oikonomou, G., Τράγος, Η., Rodriguez, R. D., & Mouroutis, T. (2014) · IEEE Wireless Communications and Networking Conference Workshops (WCNCW) · doi:10.1109/wcncw.2014.6934872 · Cited by 100 · see citing works
Bello, L. L., & Toscano, E. (2009) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2009.2018541 · Cited by 94 · see citing works
Rhythmic Tasks: A New Task Model with Continually Varying Periods for Cyber-Physical Systems
Kim, J., Lakshmanan, K., & Rajkumar, R. (2012) · doi:10.1109/iccps.2012.14 · Cited by 81 · see citing works
Evaluating Bluetooth Low Energy Suitability for Time-Critical Industrial IoT Applications
Rondón, R., Gidlund, M., & Landernäs, K. (2017) · International Journal of Wireless Information Networks · doi:10.1007/s10776-017-0357-0 · Cited by 81 · see citing works
Self-citationSaifullah, A. M., Rahman, M., Ismail, D., et al. (2016) · doi:10.1145/2994551.2994552 · Cited by 77 · see citing works
Self-citationWirArb: A New MAC Protocol for Time Critical Industrial Wireless Sensor Network Applications
Zheng, T., Gidlund, M., & Åkerberg, J. (2015) · IEEE Sensors Journal · doi:10.1109/jsen.2015.2504948 · Cited by 76 · see citing works
Self-citationModeling of the Fading Statistics of Wireless Sensor Network Channels in Industrial Environments
Olofsson, T., Åhlén, A., & Gidlund, M. (2016) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2016.2539142 · Cited by 72 · see citing works
Self-citationLong Term Channel Characterization for Energy Efficient Transmission in Industrial Environments
Agrawal, P., Åhlén, A., Olofsson, T., et al. (2014) · IEEE Transactions on Communications · doi:10.1109/tcomm.2014.2332876 · Cited by 71 · see citing works
A Bluetooth Low Energy real-time protocol for Industrial Wireless mesh Networks
Patti, G., Leonardi, L., & Bello, L. L. (2016) · Annual Conference of the IEEE Industrial Electronics Society (IECON) · doi:10.1109/iecon.2016.7793093 · Cited by 69 · see citing works
Near optimal rate selection for wireless control systems
Saifullah, A. M., Wu, C., Tiwari, P. B., et al. (2014) · ACM Transactions on Embedded Computing Systems · doi:10.1145/2584652 · Cited by 68 · see citing works
Self-citationSchedulability Analysis under Graph Routing in WirelessHART Networks
Saifullah, A. M., Gunatilaka, D., Tiwari, P. B., et al. (2015) · Proceedings/Proceedings - Real-Time Systems Symposium · doi:10.1109/rtss.2015.23 · Cited by 66 · see citing works
Self-citationCoexistence of IEEE802.15.4 based networks: A survey
Yang, D., Xu, Y., & Gidlund, M. (2010) · Proceedings of the Annual Conference of the IEEE Industrial Electronics Society · doi:10.1109/iecon.2010.5675277 · Cited by 50 · see citing works
Self-citationAscorti, L., Savazzi, S., Soatti, G., Nicoli, M., Sisinni, E., & Galimberti, S. (2017) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2016.2640579 · Cited by 48 · see citing works
Self-citationSupporting consumer services in a deterministic industrial internet core network
Szymanski, T. H. (2016) · IEEE Communications Magazine · doi:10.1109/mcom.2016.7498096 · Cited by 45 · see citing works
Low-Power Wide-Area Network Over White Spaces
Saifullah, A. M., Rahman, M., Ismail, D., et al. (2018) · IEEE/ACM Transactions on Networking · doi:10.1109/tnet.2018.2856197 · Cited by 45 · see citing works
Self-citationShen, W., Zhang, T., Gidlund, M., et al. (2012) · Wireless Networks · doi:10.1007/s11276-012-0524-2 · Cited by 44 · see citing works
Self-citationRate-adaptive tasks: model, analysis, and design issues
Buttazzo, G., Bini, E., & Buttle, D. (2014) · Lund University Publications (Lund University) · doi:10.5555/2616606.2616984 · Cited by 44 · see citing works
Constant-Time Distributed Scheduling Policies for Ad Hoc Wireless Networks
Lin, X., & Rasool, S. B. (2009) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2008.2010888 · Cited by 44 · see citing works
Interference-Aware Real-Time Flow Scheduling for Wireless Sensor Networks
Chipara, O., Wu, C., Lu, C., et al. (2011) · Proceedings - Euromicro Workshop on Real-Time Systems/Proceedings · doi:10.1109/ecrts.2011.15 · Cited by 43 · see citing works
Pease, S. G., Trueman, R., Davies, C., et al. (2017) · Future Generation Computer Systems · doi:10.1016/j.future.2017.09.026 · Cited by 43 · see citing works
Scrutinizing Bit- and Symbol-Errors of IEEE 802.15.4 Communication in Industrial Environments
Barać, F., Gidlund, M., & Zhang, T. (2014) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2013.2293235 · Cited by 42 · see citing works
Self-citationAlmarshadi, M. H., Ismail, S. M., & Arabia, S. (2011) · Cited by 41 · see citing works
Saifullah, A. M., Rahman, M., Ismail, D., et al. (2017) · ACM Conference on Embedded Networked Sensor Systems (SenSys) · doi:10.1145/3131672.3131676 · Cited by 40 · see citing works
Self-citationLightweight Security Solutions for the Internet of Things
Raza, S. (2013) · Cited by 39 · see citing works
Distributed Dynamic Packet Scheduling for Handling Disturbances in Real-Time Wireless Networks
Zhang, T., Gong, T., Gu, C., et al. (2017) · Proceedings - Real-Time Technology and Applications Symposium · doi:10.1109/rtas.2017.11 · Cited by 39 · see citing works
Channel Diagnostics for Wireless Sensor Networks in Harsh Industrial Environments
Barać, F., Caiola, S., Gidlund, M., et al. (2014) · IEEE Sensors Journal · doi:10.1109/jsen.2014.2356972 · Cited by 38 · see citing works
Self-citationWill 5G become yet another wireless technology for industrial automation?
Gidlund, M., Lennvall, T., & Åkerberg, J. (2017) · IEEE International Conference on Industrial Technology (ICIT) · doi:10.1109/icit.2017.7915554 · Cited by 38 · see citing works
Self-citationImproving Control Performance by Minimizing Jitter in RT-WiFi Networks
Leng, Q., Wei, Y.-H., Han, S., et al. (2014) · Proceedings/Proceedings - Real-Time Systems Symposium · doi:10.1109/rtss.2014.26 · Cited by 36 · see citing works
Self-citationGrimaldi, S., Mahmood, A., & Gidlund, M. (2017) · Journal of Sensor and Actuator Networks · doi:10.3390/jsan6020009 · Cited by 33 · see citing works
Self-citationReal-Time Query Scheduling for Wireless Sensor Networks
Chipara, O., Lu, C., & Roman, G.-C. (2012) · IEEE Transactions on Computers · doi:10.1109/tc.2012.172 · Cited by 32 · see citing works
Implementation and evaluation of error control schemes in Industrial Wireless Sensor Networks
Yitbarek, Y. H., Yu, K., Åkerberg, J., et al. (2014) · IEEE International Conference on Industrial Technology (ICIT) · doi:10.1109/icit.2014.6895022 · Cited by 32 · see citing works
Crenshaw, T. L., Hoke, S., Tirumala, A., et al. (2007) · ACM Transactions on Embedded Computing Systems · doi:10.1145/1274858.1274866 · Cited by 30 · see citing works
CapNet: A Real-Time Wireless Management Network for Data Center Power Capping
Saifullah, A. M., Sankar, S., Liu, J., et al. (2014) · Proceedings/Proceedings - Real-Time Systems Symposium · doi:10.1109/rtss.2014.35 · Cited by 30 · see citing works
Self-citationZhang, T., Gong, T., Yun, Z., et al. (2018) · Proceedings - Real-Time Technology and Applications Symposium · doi:10.1109/rtas.2018.00007 · Cited by 29 · see citing works
Ubiquitous, Yet Deceptive: Hardware-Based Channel Metrics on Interfered WSN Links
Barać, F., Gidlund, M., & Zhang, T. (2014) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2014.2334494 · Cited by 27 · see citing works
Self-citationOn the evaluation of LoRaWAN virtual channels orthogonality for dense distributed systems
Ferrari, P., Flammini, A., Rizzi, M., et al. (2017) · doi:10.1109/iwmn.2017.8078371 · Cited by 23 · see citing works
Distributed scheduling schemes for wireless mesh networks
Vijayalayan, K. S., Harwood, A., & Karunasekera, S. A. (2013) · ACM Computing Surveys · doi:10.1145/2522968.2522982 · Cited by 18 · see citing works
Rate-adaptive tasks: Model, analysis, and design issues
Buttazzo, G., Bini, E., & Buttle, D. (2014) · Design, Automation, and Test in Europe · doi:10.7873/date2014.266 · Cited by 14 · see citing works
An Exploratory Study of the Impact of the Internet of Things (IoT) on Business Model Innovation
Lee, I. (2016) · International Journal of Information Systems and Social Change · doi:10.4018/ijissc.2016070101 · Cited by 14 · see citing works
Integrating Low-Power Wide-Area Networks in White Spaces
Rahman, M., & Saifullah, A. M. (2018) · IEEE/ACM International Conference on Internet-of-Things Design and Implementation (IoTDI) · doi:10.1109/iotdi.2018.00033 · Cited by 13 · see citing works
Self-citationReal-Time Analysis and Design of a Dual Protocol Support for Bluetooth LE Devices
Marinoni, M., Biondi, A., Buonocunto, P., Franchino, G., Cesarini, D., & Buttazzo, G. (2016) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2016.2624020 · Cited by 10 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Edge artificial intelligence for 6g: vision, enabling technologies, and applications
Letaief, K. B., Shi, Y., Lu, J., & Lu, J. (2022) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2021.3126076 · Cited by 829 · see citing works
“processing and exchanging generated data, as well as optimizing the production system [307].”
BackgroundCyber-security on smart grid: Threats and potential solutions
Gunduz, M. Z., & Das, R. (2020) · Computer Networks · doi:10.1016/j.comnet.2019.107094 · Cited by 717 · see citing works
Tange, K., De Donno, M., Fafoutis, X., & Dragoni, N. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.3011208 · Cited by 410 · see citing works
“Within the context provided by IoT and IIoT applications, this brings some extra challenges [15], [17], [49].”
BackgroundCommunication-Efficient Federated Learning for Digital Twin Edge Networks in Industrial IoT
Lu, Y., Huang, X., Zhang, K., Maharjan, S., & Zhang, Y. (2021) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2020.3010798 · Cited by 316 · see citing works
A global manufacturing big data ecosystem for fault detection in predictive maintenance
Yu, W., Dillon, T., Mostafa, F., Rahayu, W., & Liu, Y. (2020) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2019.2915846 · Cited by 225 · see citing works
Blockchain for Edge of Things: Applications, Opportunities, and Challenges
Gadekallu, T. R., Pham, Q.-V., Nguyen, D. C., Maddikunta, P. K. R., Deepa, N., Prabadevi, B., Pathirana, P. N., Zhao, J., & Hwang, W.-J. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3119639 · Cited by 217 · see citing works
Djenna, A., Harous, S., & Saidouni, D. E. (2021) · Applied Sciences · doi:10.3390/app11104580 · Cited by 199 · see citing works
Federated Learning for Industrial Internet of Things in Future Industries
Nguyen, D. C., Ding, M., Pathirana, P. N., Seneviratne, A., Li, J., Niyato, D., & Poor, H. V. (2021) · IEEE Wireless Communications · doi:10.1109/mwc.001.2100102 · Cited by 166 · see citing works
A Blockchain-Based Secure Image Encryption Scheme for the Industrial Internet of Things
Khan, P. W., & Byun, Y. (2020) · Entropy · doi:10.3390/e22020175 · Cited by 137 · see citing works
Zeb, S., Mahmood, A., Hassan, S. A., Piran, M. J., Gidlund, M., & Guizani, M. (2022) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2021.103309 · Cited by 132 · see citing works
Self-citationTrustFed: A Framework for Fair and Trustworthy Cross-Device Federated Learning in IIoT
Rehman, M. H. U., Dirir, A. M., Salah, K., Damiani, E., & Svetinovic, D. (2021) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2021.3075706 · Cited by 132 · see citing works
Dew-Cloud-Based Hierarchical Federated Learning for Intrusion Detection in IoMT
Singh, P., Gaba, G. S., Kaur, A., Hedabou, M., & Gurtov, A. (2023) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2022.3186250 · Cited by 103 · see citing works
An Experimental Analysis of Security Vulnerabilities in Industrial IoT Devices
Jiang, X., Lora, M., & Chattopadhyay, S. (2020) · ACM Transactions on Internet Technology · doi:10.1145/3379542 · Cited by 101 · see citing works
Key Challenges and Emerging Technologies in Industrial IoT Architectures: A Review
Mirani, A. A., Velasco-Hernandez, G., Awasthi, A., & Walsh, J. (2022) · Sensors · doi:10.3390/s22155836 · Cited by 119 · see citing works
SDN-Enabled Energy-Efficient Routing Optimization Framework for Industrial Internet of Things
Naeem, F., Tariq, M., & Poor, H. V. (2021) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2020.3006885 · Cited by 83 · see citing works
Self-Sovereign Identity: Use-cases, Technologies, and Challenges for Industrial IoT
Bartolomeu, P. C., Vieira, E., Hosseini, S. M., & Ferreira, J. (2019) · 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) · doi:10.1109/etfa.2019.8869262 · Cited by 79 · see citing works
Sverko, M., Grbac, T. G., & Mikuc, M. (2022) · IEEE Access · doi:10.1109/access.2022.3211288 · Cited by 71 · see citing works
“ing plant facility boundaries, the left horizontal axis relies on the IEC 62890 standard and represents life cycles with associated value streams followed by continuous data acquisition enabling rapid and dynamic response to demand changes [76].”
BackgroundInfluentialSecuring IIoT using Defence-in-Depth: Towards an End-to-End secure Industry 4.0
Mosteiro-Sanchez, A., Barcelo, M., Astorga, J., & Urbieta, A. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.10.011 · Cited by 64 · see citing works
Kebande, V. R. (2022) · Forensic Science International Reports · doi:10.1016/j.fsir.2022.100257 · Cited by 58 · see citing works
Supervisory control and data acquisition approach in node-RED: Application and discussions
Nițulescu, I.-V., & Korodi, A. (2020) · IoT · doi:10.3390/iot1010005 · Cited by 53 · see citing works
Secure Partial Aggregation: Making Federated Learning More Robust for Industry 4.0 Applications
Gao, J., Zhang, B., Guo, X., Baker, T., Li, M., & Liu, Z. (2022) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2022.3145837 · Cited by 41 · see citing works
Eyeleko, A. H., & Feng, T. (2023) · IEEE Internet of Things Journal · doi:10.1109/jiot.2023.3308195 · Cited by 38 · see citing works
“However, the architecture itself poses difficulties in terms of communication protocol inefficiencies, network congestion, and latency problems [34], [35], [36].”
BackgroundDataStream XES Extension: Embedding IoT Sensor Data into Extensible Event Stream Logs
Mangler, J., Grüger, J., Malburg, L., Ehrendorfer, M., Bertrand, Y., Benzin, J.-V., Rinderle-Ma, S., Serral Asensio, E., & Bergmann, R. (2023) · Future Internet · doi:10.3390/fi15030109 · Cited by 33 · see citing works
“The recent developments and technologies used in the Industrial Internet of Things ( IIoT ) [1] demand a more intelligent and interconnected process-based control of IoT devices [2].”
MethodA Survey on Internet of Things (IoT), Industrial IoT (IIoT) and Industry 4.0
Deshpande, S. N., & Jogdand, R. M. (2020) · International Journal of Computer Applications · doi:10.5120/ijca2020920790 · Cited by 16 · see citing works
Securing Remote User Authentication in Industrial Internet of Things
Nimmy, K., Sankaran, S., Achuthan, K., & Calyam, P. (2022) · 2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC) · doi:10.1109/ccnc49033.2022.9700512 · Cited by 13 · see citing works
Wireless Technologies and Applications for Industrial Internet of Things: A Review
Bahri, N., Saadaoui, S., Tabaa, M., Sadik, M., & Medromi, H. (2021) · Advances in Intelligent Systems and Computing · doi:10.1007/978-981-15-6048-4_44 · Cited by 9 · see citing works
Industrial IoT: Challenges and Mitigation Policies
Kumar, P., Singh, A., & Sengupta, A. (2021) · Lecture Notes on Data Engineering and Communications Technologies · doi:10.1007/978-981-16-0965-7_13 · Cited by 1 · see citing works
Zero Trust Architecture for Smart Factories: Securing Digital Twins and Cyber-Physical OT Systems
Alagappan, V. (2026) · International Journal of Artificial Intelligence, Data Science, and Machine Learning · doi:10.63282/3050-9262.ijaidsml-v7i2p109
Sojitra, E. (2026) · American International Journal of Computer Science and Technology · doi:10.63282/3117-5481/aijcst-v8i3p101
- Authors
- Sisinni, E., Saifullah, A., Han, S., Jennehag, U., & Gidlund, M.
- Affiliations
- University of Brescia (IT)
- Wayne State University (US)
- University of Connecticut (US)
- Venue
- IEEE Transactions on Industrial Informatics
- Published
- 2018-11
- Volume
- 14
- Issue
- 11
- Pages
- 4724-4734
- ISSN
- 1551-3203 (ISSN-L)
- 1941-0050
- OpenAlex
- W2811266402
- Cited by
- 2,380
- References
- 88
- Citations by year
- 2026: 189 · 2025: 287 · 2024: 346 · 2023: 372 · 2022: 417 · 2021: 384 · 2020: 251 · 2019: 119 · 2018: 14 · 2014: 1
- FWCI
- 159.05
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Industrial Informatics (publishedVersion)
- Institutional Research Information System (Università degli Studi di Brescia) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Keywords
- Industrial Internet of Things, Industry 4.0, energy efficiency, real-time performance, coexistence, interoperability, privacy and security, IoT devices, research challenges
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
