Effective Monitoring of Sensor-Actuator Integration Methods for Real-Time Controlling in Smart Device Networks
DOI:
https://doi.org/10.63282/3050-922X.IJERET-V3I1P115Keywords:
Sensor-Actuator Integration, Real-Time Monitoring, Iot, Smart Device Networks, Communication Protocols, Middleware, AI/ML, Smart EnvironmentsAbstract
The modern IoT and cyber-physical systems cannot be achieved without smart device networks since they enable real-time monitoring and control that, in its turn, is made possible by the successful interrelation of actuators and sensors. This paper explores different types of integration architectures such as direct coupling, middleware-based frameworks, cloud-centric models, and AI/ML-enhanced systems and how they affect the interoperability, scalability, and real-time responsiveness. The main communication protocols are considered in terms of their performance in facilitating low-power, low-latency, and dependable data communication. The proposed layered architecture of integration considers dimensions in design of system, data collection, control logic and synchronization. The importance of edge computing and distributed systems to reduce the communication overhead as well as to enhance responsiveness is highlighted. An additional assessment over real-world use cases of smart grids, precision agriculture, water quality, and construction automation use cases is presented, illustrating the role of machine learning models in improved decision-making and predictive control. The conclusion of the paper finds potential significant integration problems and indicates the future courses of action, which can enhance flexibility, the productivity as well as resiliency of sensor-actuator networks.
References
[1] M. zakaria Masoud, Y. Jaradat, A. Manasrah, and I. Jannoud, “Sensors of Smart Devices in the Internet of Everything (IoE) Era: Big Opportunities and Massive Doubts,” J. Sensors, vol. 2019, pp. 1–26, May 2019, doi: 10.1155/2019/6514520.
[2] A. Raj and S. Prakash, “Internet of Everything: A survey based on Architecture, Issues and Challenges,” in 2018 5th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), IEEE, Nov. 2018, pp. 1–6. doi: 10.1109/UPCON.2018.8596923.
[3] A. Al-Fuqaha, M. Guizani, M. Mohammadi, M. Aledhari, and M. Ayyash, “Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications,” IEEE Commun. Surv. Tutorials, vol. 17, no. 4, pp. 2347–2376, 2015, doi: 10.1109/COMST.2015.2444095.
[4] A. Ghasempour, “Internet of Things in Smart Grid: Architecture, Applications, Services, Key Technologies, and Challenges,” Inventions, vol. 4, no. 1, p. 22, Mar. 2019, doi: 10.3390/inventions4010022.
[5] Z. Shouran, A. Ashari, and T. Kuntoro, “Internet of Things (IoT) of Smart Home: Privacy and Security,” Int. J. Comput. Appl., vol. 182, no. 39, pp. 3–8, Feb. 2019, doi: 10.5120/ijca2019918450.
[6] P. Pathak, A. Shrivastava, and S. Gupta, “A survey on various security issues in delay tolerant networks,” J Adv Shell Progr., vol. 2, no. 2, pp. 12–18, 2015.
[7] C. Mallick and S. Satpathy, “Challenges and Design Goals of Wireless Sensor Networks: A Sate-of-the-art Review,” Int. J. Comput. Appl., vol. 179, no. 28, pp. 42–47, Mar. 2018, doi: 10.5120/ijca2018916667.
[8] S. Pahune, “sensor data collection and performance evaluation using a TK1 board,” Univ. Memphis Digit. Commons, 2019.
[9] T. Alam, “A reliable framework for communication in internet of smart devices using IEEE 802.15.4,” ARPN J. Eng. Appl. Sci., vol. 13, no. 10, pp. 3378–3387, 2018.
[10] S. Madakam, R. Ramaswamy, and S. Tripathi, “Internet of Things (IoT): A Literature Review,” J. Comput. Commun., vol. 03, no. 05, pp. 164–173, 2015, doi: 10.4236/jcc.2015.35021.
[11] H. G. M. Pakala and K. V. s. V. N. Raju, “Sensors and Actuators Integration in Embedded Systems,” ACEEE Int. J. Netw. Secur., vol. 02, 2011.
[12] S. Achouche, U. B. Yalamanchi, and N. Raveendran, “Method, apparatus, and computer-readable medium for performing a data exchange on a data exchange framework,” 2019
[13] Q. Sun, W. Yu, N. Kochurov, Q. Hao, and F. Hu, “A Multi-Agent-Based Intelligent Sensor and Actuator Network Design for Smart House and Home Automation,” J. Sens. Actuator Networks, vol. 2, no. 3, pp. 557–588, Aug. 2013, doi: 10.3390/jsan2030557.
[14] T. P. Raptis, A. Passarella, and M. Conti, “Performance Analysis of Latency-Aware Data Management in Industrial IoT Networks,” Sensors, vol. 18, no. 8, 2018, doi: 10.3390/s18082611.
[15] R. Morales-Herrera, A. Fernández-Caballero, J. A. Somolinos, and H. Sira-Ramírez, “Integration of Sensors in Control and Automation Systems,” J. Sensors, vol. 2017, pp. 1–2, 2017, doi: 10.1155/2017/6415876.
[16] P. S. Rao, “Literature review of Smart Materials / Actuators / Sensors in the Design of Smart flexible life saving Robots,” Int. J. Adv. Res. Sci. Eng. Technol., vol. 3, no. 5, pp. 2034–2040, 2016.
[17] A.-S. Shadi, A. Mohammed, A. Kamal, and A. Mahmood, “Internet of Things (IoT) communication protocols: Review,” in 2017 8th International Conference on Information Technology (ICIT), IEEE, May 2017, pp. 685–690. doi: 10.1109/ICITECH.2017.8079928.
[18] M. U. Aftab, O. Ashraf, M. Irfan, M. Majid, A. Nisar, and M. A. Habib, “A Review Study of Wireless Sensor Networks and Its Security,” Commun. Netw., vol. 07, no. 04, pp. 172–179, 2015, doi: 10.4236/cn.2015.74016.
[19] S. Marksteiner, V. J. E. Jimenez, H. Valiant, and H. Zeiner, “An overview of wireless IoT protocol security in the smart home domain,” Jt. 13th CTTE 10th C. Conf. Internet Things - Bus. Model. Users, Networks, vol. 2018-Janua, no. November, pp. 1–8, 2017, doi: 10.1109/CTTE.2017.8260940.
[20] D.-I. Curiac, “Towards wireless sensor, actuator and robot networks: Conceptual framework, challenges and perspectives,” J. Netw. Comput. Appl., vol. 63, pp. 14–23, Mar. 2016, doi: 10.1016/j.jnca.2016.01.013.
[21] M. Kocakulak and I. Butun, “An overview of Wireless Sensor Networks towards internet of things,” in 2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), IEEE, Jan. 2017, pp. 1–6. doi: 10.1109/CCWC.2017.7868374.
[22] S. Shin, L. Xu, S. Hong, and G. Gu, “Enhancing Network Security through Software Defined Networking (SDN),” in 2016 25th International Conference on Computer Communication and Networks (ICCCN), IEEE, Aug. 2016, pp. 1–9. doi: 10.1109/ICCCN.2016.7568520.
[23] B.-S. Kim, K.-I. Kim, B. Shah, F. Chow, and K. H. Kim, “Wireless Sensor Networks for Big Data Systems,” Sensors, vol. 19, no. 7, p. 1565, Apr. 2019, doi: 10.3390/s19071565.
[24] D. Sehrawat and N. S. Gill, “Smart Sensors: Analysis of Different Types of IoT Sensors,” in 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI), IEEE, Apr. 2019, pp. 523–528. doi: 10.1109/ICOEI.2019.8862778.
[25] H. M. T. Gadiyar, G. S. Thyagaraju, T. P. Bhavya, and R. Ahana, “Privacy and Security issues in IoT based Smart Home Applications,” Int. J. Eng. Res. Technol., vol. 6, no. 15, pp. 6–8, 2018, doi: 10.17577/IJERTCONV6IS15010.
[26] S. B. Saraf and D. H. Gawali, “IoT based smart irrigation monitoring and controlling system,” in 2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), IEEE, May 2018, pp. 815–819. doi: 10.1109/RTEICT.2017.8256711.
[27] A. J. C. Godoy and I. G. Pérez, “Integration of Sensor and Actuator Networks and the SCADA System to Promote the Migration of the Legacy Flexible Manufacturing System towards the Industry 4.0 Concept,” J. Sens. Actuator Networks, vol. 7, no. 2, p. 23, May 2018, doi: 10.3390/jsan7020023.
[28] A. Mejías, R. S. Herrera, M. A. Márquez, A. J. Andújar, I. González, and J. Manuel, “Easy Handling of Sensors and Actuators over TCP/IP Networks by Open Source Hardware/Software,” Sensors, vol. 17, no. 1, p. 94, Jan. 2017, doi: 10.3390/s17010094.
[29] I. González, A. J. Calderón, A. J. Barragán, and J. M. Andújar, “Integration of Sensors, Controllers and Instruments Using a Novel OPC Architecture,” Sensors, vol. 17, no. 7, p. 1512, Jun. 2017, doi: 10.3390/s17071512.
[30] P. Pathak, A. Shrivastava, and S. Gupta, “A survey on various security issues in delay tolerant networks,” J Adv Shell Progr., vol. 2, no. 2, pp. 12–18, 2015.
[31] I. Ud Din et al., “The Internet of Things: A Review of Enabled Technologies and Future Challenges,” IEEE Access, vol. 7, pp. 7606–7640, 2019, doi: 10.1109/ACCESS.2018.2886601.
[32] Y. Kim, J. Nam, T. Park, S. Scott-Hayward, and S. Shin, “SODA: A software-defined security framework for IoT environments,” Comput. Networks, vol. 163, p. 106889, Nov. 2019, doi: 10.1016/j.comnet.2019.106889.
[33] F. A. Ruambo and J. A. Mwakatobe, “Virtualizing the Iot Ecosystem: a Brief Review, Addressing Nfv Strategies,” Int. J. Eng. Appl. Sci. Technol., vol. 4, no. 3, pp. 322–331, 2019, doi: 10.33564/ijeast.2019.v04i03.053.
[34] R. Horvath, D. Nedbal, and M. Stieninger, “A Literature Review on Challenges and Effects of Software Defined Networking,” Procedia Comput. Sci., vol. 64, pp. 552–561, 2015, doi: 10.1016/j.procs.2015.08.563.
[35] Y. Li and M. Chen, “Software-Defined Network Function Virtualization: A Survey,” IEEE Access, vol. 3, pp. 2542–2553, 2015, doi: 10.1109/ACCESS.2015.2499271.
[36] W. Ben Jaballah, M. Conti, and C. Lal, “A Survey on Software-Defined VANETs: Benefits, Challenges, and Future Directions,” May 2019, doi: 10.48550/arXiv.1904.04577.
[37] Y. Lu, “Industry 4.0: A survey on technologies, applications and open research issues,” J. Ind. Inf. Integr., vol. 6, pp. 1–10, Jun. 2017, doi: 10.1016/j.jii.2017.04.005.
[38] B. Rodrigues, F. Cerveira, R. Barbosa, and J. Bernardino, “Virtualization: Past and Present Challenges,” in Proceedings of the 13th International Conference on Software Technologies, 2018, pp. 755–761. doi: 10.5220/0006910707550761.
[39] R. Mijumbi, J. Serrat, J.-L. Gorricho, N. Bouten, F. De Turck, and R. Boutaba, “Network Function Virtualization: State-of-the-Art and Research Challenges,” IEEE Commun. Surv. Tutorials, vol. 18, no. 1, pp. 236–262, 2016, doi: 10.1109/COMST.2015.2477041.
[40] I. Alam et al., “IoT Virtualization: A Survey of Software Definition & Function Virtualization Techniques for Internet of Things,” pp. 1–30, 2019.
[41] S. K. Tayyaba, M. A. Shah, O. A. Khan, and A. W. Ahmed, “Software Defined Network (SDN) Based Internet of Things (IoT),” in Proceedings of the International Conference on Future Networks and Distributed Systems, 2017, pp. 1–8. doi: 10.1145/3102304.3102319.
[42] C. Tipantuna and P. Yanchapaxi, “Network functions virtualization: An overview and open-source projects,” in 2017 IEEE Second Ecuador Technical Chapters Meeting (ETCM), IEEE, Oct. 2017, pp. 1–6. doi: 10.1109/ETCM.2017.8247541.
[43] X. Hesselbach, J. R. Amazonas, S. Villanueva, and J. F. Botero, “Coordinated node and link mapping VNE using a new paths algebra strategy,” J. Netw. Comput. Appl., vol. 69, pp. 14–26, Jul. 2016, doi: 10.1016/j.jnca.2016.02.025.
[44] A. Kushwaha, P. Pathak, and S. Gupta, “Review of optimize load balancing algorithms in cloud,” Int. J. Distrib. Cloud Comput., vol. 4, no. 2, pp. 1–9, 2016.
[45] K. E. U. Ahmed, J. Blech, M. A. Gregory, and H. (Heinz) W. Schmidt, “Software Defined Networks in Industrial Automation,” J. Sens. Actuator Networks, vol. 7, no. 3, p. 33, Aug. 2018, doi: 10.3390/jsan7030033.
[46] M. Karakus and A. Durresi, “A survey: Control plane scalability issues and approaches in Software-Defined Networking (SDN),” Comput. Networks, vol. 112, pp. 279–293, Jan. 2017, doi: 10.1016/j.comnet.2016.11.017.
[47] B. A. A. Nunes, M. Mendonca, X.-N. Nguyen, K. Obraczka, and T. Turletti, “A Survey of Software-Defined Networking: Past, Present, and Future of Programmable Networks,” IEEE Commun. Surv. Tutorials, vol. 16, no. 3, pp. 1617–1634, 2014, doi: 10.1109/SURV.2014.012214.00180.
[48] A. R, Samiksha, A. S, and J. S. K, “Efficient operating system level virtualization techniques for cloud resources,” IOP Conf. Ser. Mater. Sci. Eng., vol. 263, p. 042002, Nov. 2017, doi: 10.1088/1757-899X/263/4/042002.
[49] A. Wang, Z. Zha, Y. Guo, and S. Chen, “Software-Defined Networking Enhanced Edge Computing: A Network-Centric Survey,” Proc. IEEE, vol. 107, no. 8, pp. 1500–1519, Aug. 2019, doi: 10.1109/JPROC.2019.2924377.
[50] N. M. M. K. Chowdhury and R. Boutaba, “Network virtualization: state of the art and research challenges,” IEEE Commun. Mag., vol. 47, no. 7, pp. 20–26, Jul. 2009, doi: 10.1109/MCOM.2009.5183468.
[51] I. Ullah, S. Ahmad, F. Mehmood, and D. Kim, “Cloud Based IoT Network Virtualization for Supporting Dynamic Connectivity among Connected Devices,” Electronics, vol. 8, no. 7, p. 742, Jun. 2019, doi: 10.3390/electronics8070742.
[52] H. Yang, S. Kumara, S. T. S. Bukkapatnam, and F. Tsung, “The internet of things for smart manufacturing: A review,” IISE Trans., vol. 51, no. 11, pp. 1190–1216, Nov. 2019, doi: 10.1080/24725854.2018.1555383.
[53] I. Bedhief, L. Foschini, P. Bellavista, M. Kassar, and T. Aguili, “Toward Self-Adaptive Software Defined Fog Networking Architecture for IIoT and Industry 4.0,” in 2019 IEEE 24th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), 2019, pp. 1–5. doi: 10.1109/CAMAD.2019.8858499.
[54] Polu, A. R., Buddula, D. V. K. R., Narra, B., Gupta, A., Vattikonda, N., & Patchipulusu, H. (2021). Evolution of AI in Software Development and Cybersecurity: Unifying Automation, Innovation, and Protection in the Digital Age. Available at SSRN 5266517.
[55] Padur, S. K. R. (2020). From centralized control to democratized insights: Migrating enterprise reporting from IBM Cognos to Microsoft Power BI. Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol, 6(1), 218-225.
[56] Bitkuri, V., Kendyala, R., Kurma, J., Mamidala, V., Enokkaren, S. J., & Attipalli, A. (2021). Systematic Review of Artificial Intelligence Techniques for Enhancing Financial Reporting and Regulatory Compliance. International Journal of Emerging Trends in Computer Science and Information Technology, 2(4), 73-80.
[57] Padur, S. K. R. (2019). Machine learning for predictive capacity planning: Evolution from analytical modeling to autonomous infrastructure. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 5(5), 285-293.
[58] Attipalli, A., Enokkaren, S., BITKURI, V., Kendyala, R., KURMA, J., & Mamidala, J. V. (2021). Enhancing Cloud Infrastructure Security Through AI-Powered Big Data Anomaly Detection. Available at SSRN 5741305.
[59] Singh, A. A. S., Tamilmani, V., Maniar, V., Kothamaram, R. R., Rajendran, D., & Namburi, V. D. (2021). Predictive Modeling for Classification of SMS Spam Using NLP and ML Techniques. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 2(4), 60-69.
[60] Padur, S. K. R. (2020). AI augmented disaster recovery simulations: From chaos engineering to autonomous resilience orchestration. International Journal of Scientific Research in Science, Engineering and Technology, 7(6), 367-378.
[61] Reddy Padur, S. K. (2021). From Scripts to Platforms-as-Code: The Role of Terraform and Ansible in Declarative Infrastructure Rollouts. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 621-628.
[62] Kothamaram, R. R., Rajendran, D., Namburi, V. D., Singh, A. A. S., Tamilmani, V., & Maniar, V. (2021). A Survey of Adoption Challenges and Barriers in Implementing Digital Payroll Management Systems in Across Organizations. International Journal of Emerging Research in Engineering and Technology, 2(2), 64-72.
[63] Padur, S. K. R. (2018). Autonomous cloud economics: AI driven right sizing and cost optimization in hybrid infrastructures. International Journal of Scientific Research in Science and Technology, 4(5), 2090-2097.
[64] Rajendran, D., Namburi, V. D., Singh, A. A. S., Tamilmani, V., Maniar, V., & Kothamaram, R. R. (2021). Anomaly Identification in IoT-Networks Using Artificial Intelligence-Based Data-Driven Techniques in Cloud Environmen. International Journal of Emerging Trends in Computer Science and Information Technology, 2(2), 83-91.
[65] Padur, S. K. R. (2021). Bridging Human, System, and Cloud Integration through RESTful Automation and Governance. the International Journal of Science, Engineering and Technology, 9(6).
[66] Attipalli, A., BITKURI, V., KURMA, J., Enokkaren, S., Kendyala, R., & Mamidala, J. V. (2021). A Survey of Artificial Intelligence Methods in Liquidity Risk Management: Challenges and Future Directions. Available at SSRN 5741342.
[67] Padur, S. K. R. (2021). From Control to Code: Governance Models for Multi-Cloud ERP Modernization. International Journal of Scientific Research & Engineering Trends, 7(3).
[68] Routhu, K. K. (2021). Harnessing AI Dashboards in Oracle Cloud HCM: Advancing Predictive Workforce Intelligence and Managerial Agility. International Journal of Scientific Research & Engineering Trends, 7(6).
[69] Padur, S. K. R. (2021). Deep learning and process mining for ERP anomaly detection: Toward predictive and self-monitoring enterprise platforms. Available at SSRN 5605531.
