Mohd Saiful Azimi Mahmud
Universiti Teknologi Malaysia

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Enhanced Fertigation Control System towards Higher Water Saving Irrigation Muhammad Khairie Idham Abd Rahman; Mohamad Shukri Zainal Abidin; Salinda Buyamin; Mohd Saiful Azimi Mahmud
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 3: June 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i3.pp859-866

Abstract

Water saving in agriculture is increasingly important due to critical issues of water and climatic crisis. The focus of agricultural researches nowadays is to minimize the water consumption and at the same time increasing the agricultural yield.   This paper presents the three-types of automatic fertigation controller for irrigation system with different application tools. A weather station, soil moisture and timer based system were used to determine the volume of water supply needed by plants to calculate an accurate irrigation operation timing. The experiment was conducted by supplying water for capsicum annum test crop located in a greenhouse. The plant water demand parameter was calculated and compared for each application tools and the best application tool was chosen to be implemented in controlling the irrigation system.
Internet of Things based Smart Environmental Monitoring for Mushroom Cultivation Mohd Saiful Azimi Mahmud; Salinda Buyamin; Musa Mohd Mokji; M.S. Zainal Abidin
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 3: June 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i3.pp847-852

Abstract

Environmental condition is a significant factor that needs to be controlled in mushroom production. Mushrooms are unable to grow if the temperature is higher than 33°C or lower than 25°C. Thus, this work focuses on developing an automatic environmental control system to provide optimum condition to mushroom production house. Environmental factors considered in the system are temperature, humidity and carbon dioxide. For this, DHT11 temperature humidity sensor and MQ135 CO2 sensor are connected to the ESP8266 Wi-Fi module to become IoT (Internet of Things) sensors that send big amount of data to the internet for monitoring and assessment. This enable users to monitor the environmental condition anywhere whenever accessing the internet. Based on the analysis of the data, the system will automatically on and off the irrigation system to put the temperature at an optimum level.
Enhanced outdoor localization of low-cost personal mobility vehicles using Extended Kalman Filter sensor fusion Vita Susanti; Mohd Saiful Azimi Mahmud; Roni Permana Saputra
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 16, No 2 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2025.1294

Abstract

Personal mobility vehicles (PMVs) are gaining popularity for short urban trips, reducing car reliance and urban pollution. The development of autonomous PMVs heavily relies on accurate localization, often using the global positioning system (GPS) as a primary sensor. However, standard GPS suffers from poor accuracy, which requires data fusion with supplementary sensors to improve precision. This study presents a sensor fusion approach using low-cost, consumer-grade hardware to enhance the PMV localization. The fusion system integrates data from an inertial measurement unit (IMU) and wheel odometry with GPS, fusing them via Kalman Filter (KF) and Extended Kalman Filter (EKF) methods. A field experiment was conducted along a 67-meter route at velocities ranging from 0.25 to 1.23 m/s. Comparative analysis has shown that the EKF method consistently outperforms the standard KF, improving positioning accuracy by approximately 29 % and reducing the maximum deviation to a range of 1.8 m to 2.7 m across different velocities. The results have confirmed the EKF as an effective and reliable strategy for achieving high-precision localization with affordable sensors, a key step towards scalable autonomous navigation for PMVs.