Indonesian Journal of Electrical Engineering and Computer Science Vol. 13, No. 3, March 2019, pp. 1208~1220 ISSN: 2502-4752, DOI: 10.11591/ijeecs.v13.i3.pp1208-1220  1208 Journal homepage: http://iaescore.com/journals/index.php/ijeecs Multiple error correction towards optimisation of energy in sensor network Samirah Razali, Kamaruddin Mamat, Nor Shahniza Kamal Bashah Faculty of Computer and Mathematical Sciences, Universiti Technology of MARA, Shah Alam, Malaysia Article Info ABSTRACT Article history: Received Sep 15, 2018 Revised Dec 10, 2018 Accepted Dec 25, 2018 Hybrid ARQ (HARQ) is among the optimum error controls implemented in Wireless Sensor Network as it reduces the overhead from retransmission and error correcting codes. The advancement in WSN includes the usage of high number of nodes and the increase in traffic with large data transmitted among the nodes had concerned the need for a new approach in error control algorithm. This paper proposed the multiple error correction based on HARQ process to aid the changes in channel with proper error correction assignment towards optimising the performances of WSN in terms of bit error rates, remaining energy, and latency for different types of congestion and channel conditions. In this study, we have developed the channel adaptation algorithm that can adapt to sudden changes and demonstrated the optimal error correcting codes as well as adjustment on the transmit power for the given channel condition and congestion presented. From the result analysed, the optimisation between the remaining energy and Bit Error rates happened on the basis of adapting to these different channel condition and congestion to minimize redundancies appended. From the result obtained, we concluded that by using multiple error correction algorithm with the aid of adjustment on the transmit power, the remaining energy can be optimised together with Bit Error rates and the excessive redundancies can be reduced. Keywords: HARQ Kalman filter Remaining energy SNR channel adaptation Wireless sensor network Copyright © 2019 Institute of Advanced Engineering and Science. All rights reserved. Corresponding Author: Kamaruddin Mamat, Faculty of Computer and Mathematical Sciences, Universiti Technology of MARA, Shah Alam, Malaysia. Email: kamar@tmsk.uitm.edu.my 1. INTRODUCTION The Wireless Sensor Network (WSN) is very crucial in monitoring field such as habitat monitoring, environmental, agricultural, military, and tracking field. Recently, there are some emerging applications of WSN in big data [1],[2] and internet of things (IoT) [3],[4]. The existing technology of WSN critically benefits in terms of cost, scalability, and also provide supports towards human-work constrained when monitoring dangerous places such as natural disasters and unfriendly environments [5]. As WSN is energy-constrained and error-prone, researchers have established many methods and ways to overcome these problems. Researches back then provided the method to reduce energy consumption through calibrating or adjusting the transmission power such as by estimating the Signal to Noise Ratio (SNR) [6] and Received Signal Strength Indicator RSSI [7] using Kalman Filter (KF) in order to adjust the transmission power. The important aspect of high error rates in a network cannot be cast aside although minimizing the energy usage using transmission power control (TPC) is an effective method to maintain the lifetime as high error rates cause retransmission to flood the network and this consumes more energy. Thus, the problem of high energy usage needs to be tackled alongside with high error rates. In addition, some