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Hla, Tin Tin
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Computer Science & IT Electrical & Electronics Engineering Engineering

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IoT Based Environmental Monitoring System for Residential Building with LoRa Technology Zin Mar; Lwin, Zin Mar; Hla, Tin Tin
The Indonesian Journal of Computer Science Vol. 14 No. 1 (2025): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i1.4745

Abstract

This paper introduces an environmental monitoring system for residential buildings that combines PIC microcontroller functionality with LoRa technology. The system integrates motion, flame, gas, vibration, temperature, and humidity sensors to provide real-time monitoring of environmental conditions and safety risks. The PIC microcontroller acts as the system's core, gathering and processing data from the sensors before transmitting it over a LoRa network to a remote station. LoRa technology is employed for its long-range and low-power communication capabilities, making the system energy-efficient and reliable for residential applications. By delivering timely alerts and insights into potential hazards, this system enhances safety and livability in residential settings. The results highlight the practicality of the proposed design and its potential for integration into smart building applications, offering a scalable and efficient solution for modern environmental monitoring challenges.
Analysis on Light Extraction Efficiency of Aluminum Gallium Nitride-Based Ultraviolet-C Light Emitting Diode with Patterned Surface in FDTD Htwe Ei Ei Khin; Hla, Tin Tin
The Indonesian Journal of Computer Science Vol. 14 No. 1 (2025): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i1.4746

Abstract

This paper presents the analysis on light extraction efficiency (LEE) of each polarization mode for Aluminum Gallium Nitride (AlGaN)-based Ultraviolet-C (UV-C) light emitting diodes(LEDs) with patterned substrate surfaces. LEE is severely constrained by the substantial refractive index contrast and polarization-dependent losses, especially transverse magnetic (TM) mode polarized light that predominates at shorter wavelengths. This study employs two dimension (2D) Finite-Difference Time-Domain (FDTD) simulations to investigate the effects of flat, equal triangular patterned, and isosceles triangular patterned surfaces on the LEE of both transverse electric (TE) and transverse magnetic (TM) modes in order to solve this issue. The specific objective of this study is to evaluate the maximum light extraction efficiency for each polarization mode of AlGaN-based UV-C LED with flat surface and patterned surfaces. Simulation results show that the patterned surfaces have better performance than flat surface. This study concludes that isosceles triangular patterning is the most effective approach for maximizing light extraction efficiency compared with equal triangular patterning and flat surfaces in AlGaN-based UV-C LEDs, providing a pathway toward the development of high-efficiency deep UV emitters.
PLC Based Automatic Stamping Machine for labelling the Boxes Pie, Khin Thet; Hlaing, May Su; Hla, Tin Tin
The Indonesian Journal of Computer Science Vol. 14 No. 1 (2025): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i1.4747

Abstract

Stamping machine plays a vital role for automation industy. There have consisted of two main parts. The results of this system has been demonstrated with supervisory control and data acquisition (SCADA) systems software and hardware. MS 32MT PLC has been applied to control and sensors and limit switches has been used to get good accuracy and start and stop condition of this system. The combination of PID and PLC have been and the desired value in conveyor system aims to maintain and the the system is stable. This system has been used for labelling the boxes in automation industry that have been carried on conveyor and chosen the box’s size by the use of laser distance sensors at robot arm system. The correct box’s size has been detected with proximity sensor and stamped the boxes. The aim of automatic stamping machine is the prototye machine to apply in automation industry.
Weather Monitoring and Prediction System for Rice Cultivation in Mandalay Using IoT and Machine Learning Khaing Zar Zar Myint; Aye, Maung; Hla, Tin Tin
The Indonesian Journal of Computer Science Vol. 14 No. 1 (2025): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i1.4749

Abstract

The purpose of this research is to monitor and predict temperature, humidity and carbon-dioxide with the objective of increasing rice yields in the rice fields located east of Mandalay. This research focuses on monitoring the temperature and humidity of rice fields near MTU. The data are displayed on a LCD and uploaded to a server to ensure timely access for farmers. Monthly weather forecasts are provided to assist farmers in making advance preparations. The energy generated by the solar system is sufficient to meet the system’s low power consumption requirements. An ESP32 collects weather data from DHT11 sensor. CO2 data from the DM118 sensor is sent to the ESP32 via Arduino UNO using the UART protocol. These data are uploaded to the AWS Lightsail server. LSTM well-suited for time-series and sequence prediction tasks. Additionally, the data is presented in the farmers’ native language to ensure readability for non-English speakers.
Comparative Evaluation of Inception V3 and YOLOv8 for Strawberry Plant Diseases Classification Using Deep Learning Models Tin Tin Wai; Aye, Maung; Hla, Tin Tin
The Indonesian Journal of Computer Science Vol. 14 No. 1 (2025): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i1.4750

Abstract

Plant diseases and pests threaten agricultural productivity, with leaf diseases causing major crop losses. Early detection is essential to mitigate these impacts. This study presents a system for detecting strawberry leaf diseases using deep learning-based Convolutional Neural Networks (CNNs) by utilizing two pre-trained models, Inception V3 and YOLOv8, to classify leaves as healthy or diseased. A custom dataset of 5,192 images, comprising one healthy class and four disease-infected categories (leaf blight, blotch, scorch, and spot), is used. Inception V3 achieved 93.8% accuracy, while YOLOv8 outperformed it with 95.4% accuracy, a mAP of 78.6%, and precision, recall, and F1-scores of 89%, 88%, and 89%, respectively. With a compact size of 12 MB and a rapid inference time of 10 ms per image, YOLOv8 is highly suitable for real-time applications. These findings highlight YOLOv8's potential to improve agricultural productivity and food security through precise and efficient disease detection.
Performance Analysis and Optimization of a Microstrip Parallel Coupled Line Bandpass Filter for C-Band Satellite Receiver Applications Moe Myint Aung; Hla, Tin Tin
The Indonesian Journal of Computer Science Vol. 14 No. 1 (2025): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i1.4751

Abstract

The design and optimization of a microstrip parallel coupled line bandpass filter (BPF) for C-band satellite receiver applications are the main focus of this work. Various filter orders (third order to seventh order) were analyzed and compared based on key performance parameters, including insertion loss, return loss, bandwidth, and shape factor. The optimized fifth order filter was selected as the most suitable due to its low insertion loss of -0.625 dB, deep return loss of -31.443 dB, and adequate bandwidth of 565 MHz, ensuring efficient signal transmission with minimal reflection. The calculated shape factor of 1.7 indicates a sharp roll-off, enabling effective rejection of out-of-band interference while maintaining a well-defined passband. The proposed design achieves a balance between performance, complexity, and real-world applicability, making it a reliable and efficient solution for C-band satellite communication systems.
Investigation of Macrobending Losses in Single Mode Optical Fiber Han, War War Moe Myint; Hla, Tin Tin
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4804

Abstract

Microbending losses are initiated by bending the optical fiber and caused escaping the light from the cladding and core. Macrobending losses degrade the signal quality in long-haul data communication. In the proposed system, macrobending losses are measured by different bending diameters of patch cord single-mode fiber G.652 optical fiber cable by using an Optical Time Domain Reflectometer (OTDR) and an optical power meter to identify the bending losses. The investigation of macro-bending losses aims to analyze the signal power loss in single-mode fiber. The proposed system is investigated by measuring the optical power losses at different bending diameters ranging from 200 mm to 80 mm and the number of turns up to 5 turns and comparison of losses variation for wavelengths 1310 nm and 1550 nm, which are affected by macrobending. The results are compared with theoretical calculations and the practical measurements.
Deep Learning based Channel Estimation and Hybrid Beamforming for 5G Massive MIMO Wireless Communications Tun, Thwe Zin; Lwin, Zin Mar; Hla, Tin Tin
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.3941

Abstract

Hybrid beamforming (BF), which divides beamforming operation into radio frequency (RF) and baseband (BB) domains, will play a critical role in MIMO communication at millimeter-wave(mmWave) frequencies. This paper also introduce offline training and prediction schemes for channel estimation and hybrid beamforming. The aim of this paper is that to increase spectral efficiency over more data streams by leveraging the deep learning based LSTM network. The LSTM network is used to train the numeric values from sequence data and predict on new sequence data. The performance is evaluated under different parameters including number of data streams (1, 2, 3 and 4) with different signal-to-noise ratio (SNR) for different carrier frequencies (28GHz, 38GHz, 60GHz and 73GHz) through computer simulation using MATLAB. The simulation results verified that the proposed method can achieve higher spectral efficiency when the number of data streams increases and the value of SNR-Test increases too.
Enhancing Agricultural Efficiency: Deep Learning-Based Soil Crack Detection for Water Irrigation Myint, Khin Moe; Aye, Maung; Hla, Tin Tin
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.3979

Abstract

The escalating demand for agricultural precision and environmental monitoring underscores the necessity for effective soil crack detection methods. This study explores the feasibility of employing a Raspberry Pi-powered camera system and deep learning image recognition to detect soil cracks and control agricultural irrigation. The purpose is to develop a soil crack detection system using deep learning techniques, sustain plant growth process, increase productivity, and optimize water irrigation practice. Our approach leverages TensorFlow to craft a convolutional neural network tailored specifically for execution on a Raspberry Pi 3B+. A dataset comprises manually captured images and is trained with the InceptionV3 model categorized into crack or nocrack classes. The accuracy is achieved ranging from 97% to 99%. These results underscore deep learning image recognition models on Raspberry Pi for cost-effective soil crack monitoring and controlling the plants watering system.
Performance Evaluation of Physical Properties on Zinc Sulfide (ZnS)-based Field Effect Transistor Mya Su Kyi; Aye, Maung; Hla, Tin Tin
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.3968

Abstract

The paper presents the performance evaluation of physical properties on Zinc Sulfide (ZnS)-based Field Effect Transistor. The most famous III-V compound-based semiconductor devices have several affected to the environment and the toxic contents are directly responded to the society. Due to the lack of technology on nontoxic compound-based semiconductor device fabrications, the novel device with II-VI compound materials are challenging issues for the environments. The specific objectives of doing research on fabrication of II-VI compound-based semiconductor devices in advanced laboratories are to emphasize the numerical modeling of the device structure and designing the FET based on ZnS material, to contribute the mathematical model for physical characteristics of the FET structure and the modification of the device structure will be easily established by using numerical simulation. The mathematical analyses on physical properties of device structure with ZnS material are confirmed and observed the several properties of electrical and electronic characteristics. The detailed implementations for ZnS-based FET devices are performed and evaluated the performance of the developed FET devices. There are two steps analyses in physical properties of ZnS-based FET devices with numerical implementation by MATLAB languages. The results observed in this study could be confirmed with the recent works from several research laboratories and the developed ZnS-based FET devices could be utilized in high performance wide band applications on switching in the power electronics and amplification purposes in modern amplifier design in real world applications.
Co-Authors Aung, Mya Sandar Aye, Maung Han, War War Moe Myint Hlaing, May Su Htwe Ei Ei Khin Khaing Zar Zar Myint Lin, Khin Ohmar Lwin, Zin Mar Moe Myint Aung Mya Su Kyi Myint, Khin Moe Pie, Khin Thet Pwint, Hnin Ngwe Yee Tin Tin Wai Tun, Thwe Zin Win, Khin Thu Zar Zin Mar