Analog and Digital Signal Monitoring Over Rs-485 using Modbus RTU
DOI:
https://doi.org/10.15662/IJEETR.2026.0802130Keywords:
Arduino Uno, RS-485, Modbus RTU, Industrial Monitoring, Fault Detection, Signal Acquisition, Embedded SystemsAbstract
In modern industrial applications, reliable monitoring of electrical systems is essential to ensure safety, efficiency and uninterrupted operation. This project presents an Analog and Digital Signal Monitoring System developed with a focus on robust communication and centralized supervision. The local End has an Arduino Uno that acquires analog and digital signals, convert using its 10-bit ADC, and performs threshold-based fault detection. Immediate fault detection is provided locally through LEDs and a Buzzer, ensuring rapid alerting at the site of operation. For centralized supervision, data from the Local end ARDUINO Uno is transmitted over RS-485, a noise- resistant and scalable communication standard capable of supporting long distances up to 1200 meters, and the structured using the Modbus RTU protocol. The Remote end, equipped with another Arduino Uno, receives the data, extracts it, and displays real-time voltage readings, system status and fault conditions on a 16x2 LCD, allowing operators to monitor the system without physically being present at the local end. The system is modular and scalable, supporting multiple Local ends for large industrial setups. Experimental results confirm accurate signal acquisition, reliable communication, immediate local fault alerts and centralized visualization highlighting the system as a practical, robust and scalable solution for industrial monitoring applications
References
1. P. Gupta and A. Sharma, “Design of industrial monitoring system using RS-485 communication,” International Journal of Engineering Research & Technology, vol. 9, no. 5, pp. 120–124, 2020.
2. R. Kumar and S. Singh, “Modbus RTU based industrial automation system,” International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, vol. 8, no. 3, pp. 876–882, 2019.
3. C.Nagarajan and M.Madheswaran - ‘Stability Analysis of Series Parallel Resonant Converter with Fuzzy Logic Controller Using State Space Techniques’- Taylor &Francis, Electric Power Components and Systems, Vol.39 (8), pp.780-793, May 2011. DOI: 10.1080/15325008.2010.541746
4. C.Nagarajan and M.Madheswaran - ‘Experimental verification and stability state space analysis of CLL-T Series Parallel Resonant Converter’ - Journal of Electrical Engineering, Vol.63 (6), pp.365-372, Dec.2012. DOI: 10.2478/v10187-012-0054-2
5. C.Nagarajan and M.Madheswaran - ‘Performance Analysis of LCL-T Resonant Converter with Fuzzy/PID Using State Space Analysis’- Springer, Electrical Engineering, Vol.93 (3), pp.167-178, September 2011. DOI 10.1007/s00202-011-0203-9
6. S.Tamilselvi, R.Prakash, C.Nagarajan,“Solar System Integrated Smart Grid Utilizing Hybrid Coot-Genetic Algorithm Optimized ANN Controller” Iranian Journal Of Science And Technology-Transactions Of Electrical Engineering, DOI10.1007/s40998-025-00917-z,2025
7. S.Tamilselvi, R.Prakash, C.Nagarajan,“ Adaptive sliding mode control of multilevel grid-connected inverters using reinforcement learning for enhanced LVRT performance” Electric Power Systems Research 253 (2026) 112428, doi.org/10.1016/j.epsr.2025.112428
8. S.Thirunavukkarasu, C. Nagarajan, 2024, “Performance Investigation on OCF and SCF study in BLDC machine using FTANN Controller," Journal of Electrical Engineering And Technology, Volume 20, pages 2675–2688, (2025), doi.org/10.1007/s42835-024-02126-w
9. C. Nagarajan, M.Madheswaran and D.Ramasubramanian- ‘Development of DSP based Robust Control Method for General Resonant Converter Topologies using Transfer Function Model’- Acta Electrotechnica et Informatica Journal , Vol.13 (2), pp.18-31,April-June.2013, DOI: 10.2478/aeei-2013-0025.
10. C.Nagarajan and M.Madheswaran - ‘DSP Based Fuzzy Controller for Series Parallel Resonant converter’- Springer, Frontiers of Electrical and Electronic Engineering, Vol. 7(4), pp. 438-446, Dec.12. DOI 10.1007/s11460-012-0212-0.
11. C.Nagarajan and M.Madheswaran - ‘Experimental Study and steady state stability analysis of CLL-T Series Parallel Resonant Converter with Fuzzy controller using State Space Analysis’- Iranian Journal of Electrical & Electronic Engineering, Vol.8 (3), pp.259-267, September 2012.
12. C.Nagarajan and M.Madheswaran, “Analysis and Simulation of LCL Series Resonant Full Bridge Converter Using PWM Technique with Load Independent Operation” has been presented in ICTES’08, a IEEE / IET International Conference organized by M.G.R.University, Chennai.Vol.no.1, pp.190-195, Dec.2007
13. Suganthi Mullainathan, Ramesh Natarajan, “An SPSS and CNN modelling based quality assessment using ceramic materials and membrane filtration techniques”, Revista Materia (Rio J.) Vol. 30, 2025, DOI: https://doi.org/10.1590/1517-7076-RMAT-2024-0721
14. M Suganthi, N Ramesh, “Treatment of water using natural zeolite as membrane filter”, Journal of Environmental Protection and Ecology, Volume 23, Issue 2, pp: 520-530,2022
15. S. Patel and M. Shah, “Real-time industrial parameter monitoring using Arduino and RS-485,” IEEE Access, vol. 7, pp. 56789–56796, 2019.
16. A. Verma and K. Rao, “Embedded system-based fault detection and monitoring for industrial applications,” International Journal of Embedded Systems, vol. 12, no. 2, pp. 45–52, 2021.
17. D. Singh and R. Patel, “Modbus protocol implementation for industrial communication systems,” IEEE International Conference on Communication Systems, pp. 210–214, 2020.
18. Selvi, G. V., Anbarasan, A. B., Murthy, B. A., & Prabavathy, S. (2023). An Application Oriented Integrated Unequal Clustering Algorithm for Wireless Sensor Network. In Underwater Vehicle Control and Communication Systems Based on Machine Learning Techniques (pp. 140-154). CRC Press.
19. Sugumar, R. (2026). Performance Optimization Frameworks for Financial Web Platforms with Real-Time Transaction Processing. International Journal of Engineering & Extended Technologies Research (IJEETR), 8(2), 600-611.
20. Mathew, A. (2024). Cloud data sovereignty governance and risk implications of cross-border cloud storage. Information Systems Audit and Control Association.
21. Garg, V. K., Soundappan, S. J., & Kaur, E. M. (2020). Enhancement in intrusion detection system for WLAN using genetic algorithms. South Asian Research Journal of Engineering and Technology, 2(6), 62–64.
22. Udayakumar, R., Yogesh Pansambal, S., Anbazhagan, K., & Sugumar, R. Real-time Migration Risk Analysis Model for Improved Immigrant Development Using Psychological Factors. Migr Lett. 2023; 20 (4): 33–42. Modbus Organization, “Modbus Application Protocol Specification V1.1b3,” 2012.
23. Texas Instruments, “SN65HVD485E RS-485 Transceiver Datasheet,” 2015.
24. Arduino, “Arduino Uno Rev3 Datasheet,” Arduino.cc, 2021.
25. MAXIM Integrated, “MAX485 Low-Power RS-485 Transceiver Datasheet,” 2014.
26. Anand, L. (2023). An Intelligent AI and ML–Driven Cloud Security Framework for Financial Workflows and Wastewater Analytics. International Journal of Humanities and Information Technology, 5(02), 87-94.
27. Murugeshwari, B., Sudharson, K., Panimalar, S. P., Shanmugapriya, M., & Abinaya, M. (2020). SAFE–Secure Authentication in Federated Environment using CEG Key code.
28. Sugumar, R. (2025). Cyber-Secure Cloud Architecture Integrating Network and API Controls for Risk-Aware SAP Healthcare Data Platforms. International Journal of Humanities and Information Technology, 7(4), 53-60.
29. Sharma, K. P., Kumar, I., Singh, P. P., Anbazhagan, K., Albarakati, H. M., Bhatt, M. W., ... & Rana, A. (2024). Advancing spacecraft rendezvous and docking through safety reinforcement learning and ubiquitous learning principles. Computers in Human Behavior, 153, 108110.





