Sukhairi Sudin
Thumbnail Image
Preferred name
Sukhairi Sudin
Official Name
Sukhairi, Sudin
Alternative Name
Sudin, S.
Main Affiliation
Scopus Author ID
56572705200
Researcher ID
GFW-2221-2022

Filters

Reset filters

Settings
Now showing 1 - 5 of 5
  • Publication
    Cycling performance prediction based on cadence analysis by using multiple regression
    ( 2021-12-01)
    Sukhairi Sudin
    ;
    Aziz Naim Abdul Aziz
    ;
    Fathinul Syahir Ahmad Sa'ad
    ;
    Nurul Syahirah Khalid
    ;
    Ismail Ishaq Ibrahim
    This project examined the influence of the cadence, speed, heart rate and power towards the cycling performance by using Garmin Edge 1000.Any change in cadence will affect the speed, heart rate and power of the novice cyclist and the changes pattern will be observed through mobile devices installed with Garmin Connect application. Every results will be recorded for the next task which analysis the collected data by using machine learning algorithm which is Regression analysis. Regression analysis is a statistical method for modelling the connection between one or more independent variables and a dependent (target) variable. Regression analysis is required to answer these types of prediction problems in machine learning. Regression is a supervised learning technique that aids in the discovery of variable correlations and allows for the prediction of a continuous output variable based on one or more predictor variables. A total of forty days' worth of events were captured in the dataset. Cadence act as dependent variable, (y) while speed, heart rate and power act as independent variable, (x) in prediction of the cycling performance. Simple linear regression is defined as linear regression with only one input variable (x). When there are several input variables, the linear regression is referred to as multiple linear regression. The research uses a linear regression technique to predict cycling performance based on cadence analysis. The linear regression algorithm reveals a linear relationship between a dependent (y) variable and one or more independent (y) variables, thus the name. Because linear regression reveals a linear relationship, it determines how the value of the dependent variable changes as the value of the independent variable changes. This analysis use the Mean Squared Error (MSE) expense function for Linear Regression, which is the average of squared errors between expected and real values. Value of R squared had been recorded in this project. A low R-squared value means that the independent variable is not describing any of the difference in the dependent variable-regardless of variable importance, this is letting know that the defined independent variable, although meaningful, is not responsible for much of the variance in the dependent variable's mean. By using multiple regression, the value of R-squared in this project is acceptable because over than 0.7 and as known this project based on human behaviour and usually the R-squared value hardly to have more than 0.3 if involve human factor but in this project the R-squared is acceptable.
      3  18
  • Publication
    IoT-based Carbon Monoxide (CO) Real-Time Warning System Application in Vehicles
    ( 2021-12-01)
    Kamarudin A.A.A.
    ;
    Nurul Syahirah Khalid
    ;
    Ismail Ishaq Ibrahim
    ;
    Muhammad Aizat Abu Bakar
    ;
    Mahadi M.Z.
    ;
    Shazmin Aniza Abdul Shukor
    ;
    Sukhairi Sudin
    ;
    Mohd Zamri Hasan
    ;
    Humairah Mansor
    The project is about develop a system and application for detect the presence of Carbon Monoxide(CO) in car, since recently there are many cases of drowning while sleeping in car due to inhaling CO. The build system are able to detect the presence of CO and provide warning about level of CO to the users. It uses Blynk application to monitors level of CO inside the vehicle, MQ-9 gas sensor as the input sensor, ESP 8266 as medium to send data to the application via IoT-based and the level concentration of CO is displayed on the LCD in real-time displayed. For the output, it has 3 different condition based on the level concentration of CO. This project has been testing in six different situation. Based on the result, ambience air and in car with open window situation have lowest of CO level. Meanwhile, the highest of CO level is detect in smoke that are produced from fuel combustion of the car exhaust at distance 5 cm. Additionally, Principal Component Analysis (PCA) is used to analysed the ability of this system in clustering for each situation. As a result, PCA have clearly clustering data for every situation with the value of PC1 is 71.82% and PC2 is 28.18%, hence it is verified that the build system is able to applied in detecting the presence of CO. This project is believed able in helping to reduce the numbers of cases people drowning while sleeping due to inhaling CO in the car.
      6  26
  • Publication
    Hand-held shelf life decay detector for non-destructive fruits quality assessment
    ( 2024)
    Nurul Syahirah Khalid
    ;
    Nordiana Shariffudiin
    ;
    Shazmin Aniza Abdul Shukor
    ;
    Humairah Mansor
    ;
    Masturah Tunnur Mohamad Talib
    ;
    Sukhairi Sudin
    ;
    Ismail I. Ibrahim
    ;
    Mohd Zamri Hasan
    ;
    Siti Marhainis Othman
    ;
    N.D.N Dalila
    ;
    M.Thaqif B.N Ashimi
    Perishable food such as fruits have a limited shelf life and can quickly degrade if not properly stored. One method for detecting decay in these foods is the use of ethylene gas. Ethylene is a naturally occurring hormone that is released by fruits as they ripen. By measuring the levels of ethylene in the storage area, it is possible to detect when fruits and vegetables are starting to degrade. This information can then be used to act, such as removing spoiled produce and adjusting storage conditions, to extend the shelf life of the remaining products. By utilizing ethylene gas for early detection of decay, it is possible to improve food safety and reduce food waste. The project aims to utilized ethylene gas from perishable food such as fruits before decay. This project proposed portable or hand-held detection ethylene gas by including temperature and humidity. The sensor will be measuring the level of ethylene gas, temperature and humidity. Next, machine learning method; K-Nearest Neighbour(KNN) were used to evaluate the accuracy of the proposed system. This project, a hand-held decay detector for perishable food products is believed can help to prevent food waste by detecting early signs of spoilage in fruits.
      4  2
  • Publication
    IoT-based Carbon Monoxide (CO) Real-Time Warning System Application in Vehicles
    ( 2021-12-01)
    Kamarudin A.A.A.
    ;
    Nurul Syahirah Khalid
    ;
    Ibrahim I.I.
    ;
    Muhammad Aizat Abu Bakar
    ;
    Mahadi M.Z.
    ;
    Shukor S.A.A.
    ;
    Sukhairi Sudin
    ;
    Hasan M.Z.
    ;
    Mansor H.
    The project is about develop a system and application for detect the presence of Carbon Monoxide(CO) in car, since recently there are many cases of drowning while sleeping in car due to inhaling CO. The build system are able to detect the presence of CO and provide warning about level of CO to the users. It uses Blynk application to monitors level of CO inside the vehicle, MQ-9 gas sensor as the input sensor, ESP 8266 as medium to send data to the application via IoT-based and the level concentration of CO is displayed on the LCD in real-time displayed. For the output, it has 3 different condition based on the level concentration of CO. This project has been testing in six different situation. Based on the result, ambience air and in car with open window situation have lowest of CO level. Meanwhile, the highest of CO level is detect in smoke that are produced from fuel combustion of the car exhaust at distance 5 cm. Additionally, Principal Component Analysis (PCA) is used to analysed the ability of this system in clustering for each situation. As a result, PCA have clearly clustering data for every situation with the value of PC1 is 71.82% and PC2 is 28.18%, hence it is verified that the build system is able to applied in detecting the presence of CO. This project is believed able in helping to reduce the numbers of cases people drowning while sleeping due to inhaling CO in the car.
      29  5
  • Publication
    Development of a Common Waste Combustion System for Generating Electricity at Remote Area
    ( 2023-01-01)
    Zaini A.S.A.
    ;
    Sukhairi Sudin
    ;
    Haris F.A.
    ;
    Nurul Syahirah Khalid
    ;
    Fathinul Syahir Ahmad Sa'ad
    ;
    Muhamad Khairul Ali Hassan
    ;
    Ibrahim I.I.
    Malaysia's daily amount of municipal solid waste (MSW) has rapidly increased. This causes the landfills number to increase due to inadequate waste management systems. Apart from that, Malaysia depends on non-renewable resources for electricity generation which could have a significant effect on the environment. Therefore, this study proposed to reduce landfills in Malaysia in a proper way and supply electricity using municipal solid waste as a renewable resource. In this study, the combustion of municipal solid waste (MSW) produces steam, which will rotate a turbine that is connected to a dynamo. Then, the energized dynamo will supply electricity to appliances including a direct current motor. The motor shaft then rotates the dynamo shaft in the pulley system which causes the electricity to flow in a closed loop. In this system, a pressurized container is crucial to produce sufficient steam. Based on the experimental setup, it was observed that continuous electricity was successfully achieved by looping the system using a pulley on the dynamo and motor.
      1  23