Now showing 1 - 10 of 16
  • Publication
    Connected car: Engines diagnostic via Internet of Things (IoT)
    This paper is about an experiment for performing engines diagnostic using wireless sensing Internet of Thing (IoT). The study is to overcome problem of current standard On Board Diagnosis (OBD-II) data acquisition method that only can be perform in offline or wired method. From this paper it show a method to determined how the data from engines can be collected, make the data can be easily understand by human and sending data over the wireless internet connection via platform of IOT. This study is separate into three stages that is CAN-bus data collection, CAN data conversion and send data to cloud storage. Every stage is experimented with a two different method and consist five data parameter that is Revolution per Minute (RPM), Manifold Air Pressure (MAP), load-fuel, barometric pressure and engine temperature. The experiment use Arduino Uno as microcontroller, CAN-bus converter and ESP8266 wifi board as transfer medium for data to internet.
  • Publication
    IoT Based Smart Betta Fish Monitoring system with fish fatality prediction.
    This study enlightens the importance of rearing water quality to Betta fish health. A water quality monitoring system was developed based on water quality parameters namely water pH, temperature (°C) and TDS level (ppm). Fuzzy Logic Algorithm was applied to predict the possibility of the fish to get infected by the disease using combination of the water quality parameters value. Graphical User Interface (GUI) was developed to test the efficiency of the fish disease prediction system using fuzzy logic algorithm before the fuzzy rule been embedded to the IOT system. Arduino Uno Wi-Fi R2.0 and Blynk Apps used for enabling the system to update the aquarium water quality to owner in real-time. Hydroponic technology implemented in this project for recirculate rearing water inside the fish tank. Theoretically, the aquaponic system will help regulate the water tank parameters in optimum range and Betta Splendens should be free from all diseases.
      1
  • Publication
    Effect of Strength and Conditioning Trainings on Lower Limb Muscles Activity of High-Jumping Athletes
    In recent years, there has been a proliferation of technology and sport science utilized within an athlete’s physical activity and exercise. This study aims to assess the effectiveness of two strength and conditioning exercises, namely, a customized free-weight exercise and plate-loaded machine exercise, on the lower limb muscle activities of the amateur high jumpers. Six amateur high jumpers were divided into two groups, a customized free-weight group and plate-loaded machine group (control group) and performed exercises as instructed by the coach. The EMG signal of the Rectus Femoris and Bicep Femoris muscles were recorded during the exercises. Metronome was used to control the speed of the exercise and it was standardized for all subjects. The harmstring’s cable pull exercise (customized free-weight) triggered Bicep Femoris more compared to the leg curl exercise (plate-loaded exercise). Similarly, in the case of Rectus Femoris muscle, the front squat exercise (customized free-weight exercise) triggered higher muscular activities compared to the leg extension exercise (plate-loaded exercise). In conclusion, the customized free-weight exercise has indicated higher muscle activities compared to the plate-loaded exercise.
      1
  • Publication
    Rssi-based for device-free localization using deep learning technique
    Device-free localization (DFL) has become a hot topic in the paradigm of the Internet of Things. Traditional localization methods are focused on locating users with attached wearable devices. This involves privacy concerns and physical discomfort especially to users that need to wear and activate those devices daily. DFL makes use of the received signal strength indicator (RSSI) to characterize the user’s location based on their influence on wireless signals. Existing work utilizes statistical features extracted from wireless signals. However, some features may not perform well in different environments. They need to be manually designed for a specific application. Thus, data processing is an important step towards producing robust input data for the classification process. This paper presents experimental procedures using the deep learning approach to automatically learn discriminative features and classify the user’s location. Extensive experiments performed in an indoor laboratory environment demonstrate that the approach can achieve 84.2% accuracy compared to the other basic machine learning algorithms.
      1
  • Publication
    Development of Artificial Stingless Bee Hive Monitoring using IoT System on Developing Colony
    ( 2024-01-01)
    Ali M.A.A.C.
    ;
    ; ; ; ;
    Saad M.A.H.
    ;
    Hassan M.F.A.
    The trend of stingless bees’ farm in Malaysia has increased recently as it has been proven that its honey gives various benefits to human beings. This trend requires beekeepers to do more frequent inspections of beehives. However, the current practice of opening the cover to inspect the colony and honey will disrupt colony activity. According to a recent study, these stingless bees can only survive between 22 and 38 degrees Celsius, and harsh weather conditions might lead to the collapse of bee colonies. In order to ensure a consistent honey production, the IoT monitoring system will be implemented on an artificial stingless beehive. The system is equipped with an embedded system that utilizes a NodeMCU ESP8266, temperature and humidity sensors, and load cell sensors. Next, honey compartment weight, temperature and humidity inside stingless beehive, and temperature and humidity outside stingless beehive will be uploaded to the Internet of Things (IoT) platforms, namely Thingspeak and Cayenne. The data is sent to Thingspeak via the REST API while to Cayenne by the MQTT API. All data from the artificial stingless bee hive indicating the occurrence of colony rising and has been uploaded to the IoT platform. By analysing the data that were recorded for 13 days, all of the input data such as the weight of the honey compartment, the temperature in the hive, and the humidity in the hive, display its respective characteristics. For the honey compart weight, it has been found that the stingless bee colony is rising as a result of the increasing honey and colony in the compartment weight. Regarding the hive temperature, it has been determined that the temperature inside the hive is stable around 26°C to 38°C in normal weather conditions. Whereas for humidity inside the hive, it is remained between 76.5% and 85.6% due to the moisture from the honey inside the compartment. Lastly, these results indicate that the colony living in the artificial hive of stingless bees is healthy and growing.
      1
  • Publication
    Analysis of Soil Nutrient (NPK) Test Value - Relative yield Relationship for Harumanis Mango using Modification Arcsine-Log Calibration Curve.
    The cultivation of Harumanis mango (Mangifera indica) is of significant agricultural importance, especially in tropical regions like Malaysia, where it is renowned for its exceptional taste and quality. Maximizing mango yield and maintaining fruit quality are vital aspects of successful cultivation, relying on optimal soil nutrient management, particularly nitrogen (N), phosphorus (P), and potassium (K). In this research, the soil nutrient test value - relative yield relationship for Harumanis mango is investigated using a modification arcsine-log calibration curve. Traditional linear calibration curves may not fully capture the nonlinearities observed in crop responses, potentially leading to inaccurate nutrient requirements for optimal yield. By employing the innovative modification arcsine-log calibration curve, a more precise and robust relationship between soil nutrient test values and relative mango yield is established. Soil samples are collected from mango orchards, and NPK levels are measured using standardized laboratory techniques, alongside corresponding relative mango yields. This study advances precision agriculture by offering precise soil nutrient recommendations for mango farmers. Utilizing calibrated curves improves mango yield, minimizes nutrient waste, and encourages sustainable farming. In conclusion, the modified arcsine-log calibration curve reveals vital insights for optimal Harumanis mango production, benefiting the industry and sustainability.
      1
  • Publication
    Human breathing assessment using Electromyography signal of respiratory muscles
    ( 2017-04-05) ; ;
    Zulkifli Zakaria
    ;
    ;
    Sathees Kumar Nataraj
    Breathing is one of the human physiological activities that catch the interest of researchers especially in the area of medical diagnosis and human physiological performance. Mostly, the measurement and data are in form of pressure and volume variables of air intake and outflow. However, using airflow pressure and volume require installment of certain sensor usually on subject's mouth which could discomfort the subject. Another possible method for assessing the breathing pattern is through human respiratory muscles, which are via electromyography signal. In this paper, experiment is done on acquiring the electromyography signal from four respiratory muscles namely sternocleidomastoid, scalene, intercostal muscle and diaphragm with subjects performing four different breathing tasks. Analysis-of-variance test has been done on the Electromyography (EMG) feature data of the four muscles for the four breathing tasks. Results of ANOVA analysis, show that the p-values has a significant different in the four breathing tasks for each muscle.
  • Publication
    CFD Analysis of Pure Waterjet Nozzle for Fruit Peeling and Cutting Process
    Waterjet Technology has been used vastly in our world nowadays due to its advantages and it can be implemented in many industrial sectors or even in the medical sector and food industry sector. Nozzle is a component that has been utilized in waterjet which is employed in a wide range of engineering applications to control the rate of flow, velocity, and the jet pressure of the water. This paper discusses the CFD analysis on a pure waterjet nozzle to obtain the output of the water that jets out from three different diameters of nozzle and select the effective nozzle diameter to be used for the fruit peeling and cutting process. The pressure used for the analysis are 200MPa, 300MPa and 400MPa, which was analysed for three different nozzle diameter 0.76mm, 1.02mm and 1.27mm. From CFD analysis, it is established that as the pressure loss of the water jet increases, the outlet velocity of the jet increases. Furthermore, for fruit peeling and cutting process the impact angle of the nozzle should be prioritised as the peeling of the fruit should be smooth and even before cutting the fruit. Thus, the most suitable parameters were found to be 400MPa and 1.02mm of pressure and nozzle diameter respectively. This will allow for the intended fruit cutting process with a stand-off distance that can be ranged from 1mm to 9mm.
      2
  • Publication
    Nutrient Requirements and Growth Response of Harumanis Mango (Mangiferaindica L.) during Vegetative Shoot Growth Stages: A Mitscherlich Law Analysis
    This study investigates the nutrient requirements of Harumanis mango (Mangifera indica L) during different vegetative shoot growth stages by analyzing the soil nutrient test value-relative growth relationships. The research utilizes the Mitscherlich Law to model the response of mango yield in relation to varying nutrient levels. The data came from experimental plots, and the results show the asymptotic behavior of mango yield for three essential nutrients: nitrogen (N), phosphorus (P), and potassium (K). For vegetative shoot growth1, the asymptotic yield was estimated at 665.5 with a decline rate of -3.39 concerning N, -2.17 concerning P, and -1.35 concerning K. The coefficient of determination (R2) was 0.934, indicating a high goodness of fit for the model. Similar trends were observed for vegetative shoot growth2 and 3, where the asymptotic yields and nutrient decline rates varied accordingly. This study provides crucial insights into Harumanis mango nutrient needs across growth stages, aiding orchard management for sustainable yields. Applying the Mitscherlich Law enhances our understanding of how nutrients affect mango growth. These findings support targeted fertilization, boosting productivity and orchard efficiency. Future research can explore more growth factors and long-term nutrient impacts.
      1
  • Publication
    Surface Reconstruction from Unstructured Point Cloud Data for Building Digital Twin
    ( 2023-01-01)
    Ismail F.A.
    ;
    ; ;
    Wong R.
    This study highlights on the methods used for surface reconstruction from unstructured point cloud data, characterized by simplicity, robustness and broad applicability from 3D point cloud data. The input data consists of unstructured 3D point cloud data representing a building. The reconstruction methods tested here are Poisson Reconstruction Algorithm, Ball Pivoting Algorithm, Alpha Shape Algorithm and 3D surface refinement, employing mesh refinement through Laplacian smoothing and Simple Smoothing techniques. Analysis on the algorithm parameters and their influence on reconstruction quality, as well as their impact on computational time are discussed. The findings offer valuable insights into parameter behavior and its effects on computational efficiency and level of detail in the reconstruction process, contributing to enhanced 3D modeling and digital twin for buildings.
      1