Enhancing River Monitoring Embedded System using Time Redundancy Fault Tolerance to Resolve Transient Sensor Fault


  • Mochammad Hannats Hanafi Ichsan Brawijaya University, Malang
  • Muhammad Adinura Julian Habibie Brawijaya University, Malang
  • Wijaya Kurniawan Brawijaya University, Malang




Reading data from sensors in the context of the Internet of Things (IoT) is one of the main parameters of a high-reliability system. Data reading by sensors is prone to errors due to various variables that the problem cannot accommodate. One method to overcome this problem is the time redundancy algorithm, where the sensor takes data and its best value several times. In this study, the sensors used to calculate the water levels are ultrasonic sensors and resistance. At the river monitoring point, data is sent using the UDP (User Datagram Protocol) protocol that previous studies have used. This research has been done as a prototype with a maximum distance between sensor nodes of one meter. The results of sending data using UDP were successful, with an average delay of 3293 microseconds. And the ultrasonic sensor that has been tested based on transient fault against time redundancy has an accuracy of 94.5% based on a sampling delay of 1000ms.


P. Marwedel, Embedded system design: embedded systems foundations of cyber-physical systems, and the internet of things, Springer Nature, 2021.

M. Siek dan L. Larry, "Design and Implementation of Internet of Things and Cloud Technology in Flood Risk Mitigation," dalam 2021 3rd International Conference on Cybernetics and Intelligent System (ICORIS), Makasar, Indonesia, 2021.

H. R. Goyal, K. K. Ghanshala dan S. Sharma, “Intelligent Internet of Things based Flood Management System,” dalam 2022 6th International Conference on Intelligent Computing and Control Systems (ICICCS), Madurai, India, 2022.

S. S. Hussen Hajjaj, M. T. Hameed Sultan, M. H. Moktar dan S. H. Lee, "Utilizing the internet of things (IoT) to develop a remotely monitored autonomous floodgate for water management and control," Water, vol. 12, no. 2, p. 502, 2020.

M. A. Akkaş, R. Sokullu dan H. E. Cetin, "Healthcare and patient monitoring using IoT," Internet of Things, vol. 11, p. 100173, 2020.

K. M. de Bruijn, C. Maran, M. Zygnerski, J. Jurado, A. Burzel, C. Jeuken dan J. Obeysekera, "Flood resilience of critical infrastructure: Approach and method applied to Fort Lauderdale, Florida," Water, vol. 11, no. 3, p. 517, 2019.

D. Perera, J. Agnihotri, O. Seidou dan R. Djalante, "Identifying societal challenges in flood early warning systems," International Journal of Disaster Risk Reduction, vol. 51, p. 101794, 2020.

H. S. Munawar, F. Ullah, S. Qayyum, S. I. Khan dan M. Mojtahedi, "Uavs in disaster management: Application of integrated aerial imagery and convolutional neural network for flood detection," Sustainability, vol. 13, no. 4, p. 7547, 2021.

S. Puttinaovarat dan P. Horkaew, "Flood forecasting system based on integrated big and crowdsource data by using machine learning techniques," IEEE Access, vol. 8, pp. 5885-5905, 2020.

M. H. H. Ichsan dan A. E. Prasetya, "Fuzzy Logic and Simple Additive Weighting Implementation on River Flow Controlling System," dalam Journal of Physics: Conference Series, 2021.

M. H. H. Ichsan, W. Kurniawan dan A. T. Wulandari, "Fuzzy Logic for Flood Detection System in an Embedded System," Lombok, Indonesia, 2019.

E. Abdulhay, V. Elamaran, N. Arunkumar dan V. Venkataraman, "Fault-tolerant medical imaging system with quintuple modular redundancy (QMR) configurations," Journal of Ambient Intelligence and Humanized Computing, pp. 1-13, 2018.

S. Arslan dan O. Unsal, "Efficient selective replication of critical code regions for SDC mitigation leveraging redundant multithreading," The Journal of Supercomputing, vol. 77, no. 12, pp. 14130-14160, 2021.

Z. Noshad, N. Javaid, T. Saba, Z. Wadud, M. Q. Saleem, M. E. Alzahrani dan O. E. Sheta, "Fault detection in wireless sensor networks through the random forest classifier," Sensors, vol. 19, no. 7, p. 1568, 2019.

J. Zhou, X. S. Hu, Y. Ma, J. Sun, T. Wei dan S. Hu, "Improving availability of multicore real-time systems suffering both permanent and transient faults," IEEE Transactions on Computers, vol. 68, no. 12, pp. 1785-1801, 2019.

P. Sun; R. Bisschop; H. Niu; X. Huang, "A Review of Battery Fires in Electric Vehicles," Fire Technology, vol. 56, no. 1, p. 1361–1410, 2020.

A. Pérez, A. Rodríguez, A. Otero, D. G. Arjona, A. Jiménez-Peralo, M. Á. Verdugo dan E. De La Torre, "Run-time reconfigurable MPSoC-based on-board processor for vision-based space navigation," IEEE Access, vol. 8, pp. 59891-59905, 2020.

E. Dubrova, Fault-tolerant design, New York: Springer, 2013.

M. Dietze, R. Bell, U. Ozturk, K. L. Cook, C. Andermann, A. R. Beer dan A. H. Thieken, "More than heavy rain turning into fast-flowing water–a landscape perspective on the 2021 Eifel floods," Natural Hazards and Earth System Sciences, vol. 22, no. 6, pp. 1845-1856, 2022.

A. S. Pambudi, "Problems of Local Floods and Their Relation to Bogor City Drainage Infrastructure System," Indonesian Journal of Applied Research (IJAR), vol. 3, no. 1, pp. 10-22, 2022.

H. Tansar, H.-F. Duan dan O. Mark, "Catchment-scale and local-scale based evaluation of LID effectiveness on urban drainage system performance," Water Resources Management, vol. 36, no. 2, pp. 507-526, 2022.




How to Cite

Ichsan, M. H. H., Habibie, M. A. J. ., & Kurniawan, W. (2023). Enhancing River Monitoring Embedded System using Time Redundancy Fault Tolerance to Resolve Transient Sensor Fault. Journal of Information Technology and Computer Science, 8(1), 52–59. https://doi.org/10.25126/jitecs.202381453