ResearchHighlightsStudent projects

Offered projects for internship students and final year graduation projects


2024-10-08

Data Fusion and AI in Indoor Smart Farming

This internship focuses on the integration of data fusion techniques and artificial intelligence (AI) to enhance indoor smart farming practices. The intern will explore how to collect, analyze, and utilize diverse agricultural sensor data to monitor and optimize plant growth, resource management and operational efficiency. The objectives are: gather data from various sensors and other relevant sources; implement methods for the integration of heterogeneous data set to provide valuable insights into indoor smart farming; implement machine learning algorithms to predict plant growth, detect diseases, and automate irrigation and nutrient delivery to indoor smart farming

Advisor: Romuald Jolivot

Description: Expected Outcomes: Develop a prototype of a smart farming solution that gather sensors data, perform data fusion and use it them in a machine learning framework. Duration 3-6 months Number of students: 1 Prerequisite: data science, AI Development on Python, Pandas, Scikit-learn

2024-10-08

Development of nutrient sensors based on light attenuation

The internship focuses on the investigation of a new sensor that utilize light attenuation technique to quantify different nutrient concentrations in the soil (Nitrogen, Phosphorus, Potassium). The student will engage in the research and development of sensor prototypes aimed at accurately measuring nutrient level for smart farming. The first stage involves performing simulations using Monte Carlo or other light propagation model to estimate the potential effectiveness of these sensors in real-world applications. This will be followed by experimentation and data analysis to investigate the relation between light absorption and nutrient concentrations.

Advisor: Waleed Mohammed, Romuald Jolivot

Description: Expected outcome: Light propagation model in soil, NPK light based sensor Duration: 3-9 months Number of students: 1 Prerequisite: Physics/optics knowledge, programming skills, Hardware: LED, light sensor, 3D printer, Software: Python, Arduino

2024-10-08

Image Processing monitoring for indoor smart farm

This internship focuses on the application of image processing and artificial intelligence (AI) to enhance indoor smart farming practices. The intern will explore how to capture, analyze, and utilize data from plant images to monitor and optimize growth conditions, disease detection and resource management. The objectives are: gather image data set from various sources and from our own growing plants, perform a state of the art of the image techniques used for indoor farming, implement advanced image processing algorithms to extract meaningful information; and apply machine learning techniques to identify plant health and automate responses for irrigation and nutrient delivery.

Advisor: Romuald Jolivot

Description: Expected outcome: Image processing algorithms and AI models Duration: 3-6 months Number of students: 1 Prerequisite: Programming skills, deep learning knowledge, image processing Hardware: Computer and webcam Software: Python, Deep learning tools, OpenCV

2024-10-08

Development of robot for data collection and acquisition using VLP

This internship focuses on creating a robotic system specifically designed for data collection and acquisition in indoor smart farming, employing visible light positioning techniques to accurately track the location of measurements. The project will explore the integration of multiple sensors within the robot, enabling it to gather data from various locations across the smart farm. Objectives: Design a robot that effectively combines these sensors to perform comprehensive data acquisition while ensuring precise localization of each measurement. This will enhance the ability to monitor and optimize farming conditions, ultimately contributing to improved crop management and resource efficiency.

Advisor: Waleed Mohammed

Description: Expected outcome: Robot with sensors Duration: 3-6 months Number of students: 1-2 Prerequisite: mechanical engineering, electrical engineering Hardware: Motor, 3D printers, sensors Software: Python, Arduino

2024-10-08

Image processing for Smart Interactive Museum Display

The overall goal of this project is to create an engaging interactive experience for users by enabling them to interact with holographic images representing real artifacts, thereby overcoming the no-touching policy applied to physical items. Currently, the holograms are displayed using a four-view acrylic pyramid and an acrylic cone. The aim of the internship is to develop algorithms that facilitate interaction with the displayed holograms. There are two main components to this interaction. First, the intern will develop algorithms using the MediaPipe library to control the rotation, zoom, and display of additional textual information related to the hologram. Second, the project will incorporate a fisheye camera positioned above the hologram display to detect user presence. Image processing algorithms will be developed to track the user’s location and rotate the hologram accordingly. Depending on the progress made during the internship, additional functionalities and enhancements may be explored to further enrich the interactive experience.

Advisor: Romuald Jolivot

Description: Expected outcome: Algorithms using MediaPipe to control hologram display. Algorithm for the detection of a visitor using fisheye camera to simulate real object in a hologram display. Duration: 3-6 months Number of students: 1 Prerequisite: Image processing, programming skills Hardware: Raspberry Pi, Fisheye Camera, Webcam Software: Python, OpenCV, AI

2024-10-08

Development of acquisition systems for holographic-like artifacts

The overall goal of this project is to create advanced acquisition systems for holographic representations of real artifacts, enabling in-depth study without physical contact. The internship will focus on developing two innovative systems for data acquisition. The first system involves designing a small robot capable of performing a 360-degree rotation around an object to gather detailed visual data. This automated approach ensures thorough documentation while adhering to the no-touching policy. The second system will leverage smartphone technology to create 360-degree photogrammetry images of the artifact. This method will allow for high-quality visual representation and analysis without the need for direct interaction with the item. Together, these systems will enhance the ability to acquire and study artifacts interactively, providing users with a rich and immersive experience while maintaining the integrity of the original objects.

Advisor: Romuald Jolivot

Description: Expected outcome: 2 acquisition systems for holographic-like artifacts Duration: 3-6 months Number of students: 1-2 Prerequisite: Image processing, mechanical knowledge Hardware: Raspberry Pi, Webcam, Arduino Software: Python, OpenCV, AI

2024-09-27

Inverse Panorama Acquisition System

The internship subject is part of the Interactive Museum Display project. The goal is to develop an object panorama acquisition system for the digitization of antique ceramics. For safety reason, the ceramics need to be carefully handled, therefore, the development of a low-cost system for the digitization of ceramics is expected. By the nature of the ceramics, object panorama (also called inverse panorama) is required. The goal is to develop a system that automatically remove the background around of the ceramics and generate a 360 degree video of the object.

Advisor: Romuald Jolivot

Description: Expected outcome: Algorithms generating an inverse panorama of the digitized ceramics. 
Duration: 3-6 months 
Number of students: 1 
Prerequisite: Image processing, programming skills 
Hardware: Laptop, cameras or smartphone Software: Python, OpenCV

2023-11-26

AI for gas detection

The goal of the project is to develop an AI platform that automatically detects selected gases. The data are obtained from a set of 6 newly developed sensors that records change in resonance spectra in time-series format. The system should perform signal processing, classification and detection on records of 7 VOC (volatile organic compounds) at different concentrations.The project is currently being extended as a matrix of 81 sensors that will be recorded using a camera, switching to image processing. New AI algorithms will be required to process the new large set of data. This work is a collaboration with a national research institute that is developing new sensors, while we are working on data processing.

Advisor: Romuald Jolivot

Description: Expected outcome: AI algorithms 
Duration: 3-9 months 
Number of students: 1 
Prerequisite: Signal Processing background, image processing knowledge, AI, Programming skills: Matlab, Python, OpenCV, Scikit-learn

2023-11-26

Development of a mobile robot system for collecting and transporting infectious waste in hospital

The aim of this project present an idea concept of service robots for hospitals which an autonomous hospital logistics systems which unmanned control especially for infectious waste transport management system in the smart city. Now the prototype module of a mobile robot system for collecting and transporting infectious waste in hospital has been already finished in basically and ready to use, but for more available benefits usage of this robot system must be create in the future work such as an intelligent system ,smart and a long distance controlled. So some topics for developing are composed of camera vision with AI control, mobile robot localization control or mobile application control or cloud network control.

Advisor: Ajarn Songkran Kantawong

Description:

2023-11-26

AI for wearable VOC detection on smart clothes

The work package involves the development of the read out system. There a python code is to be developed on Android platform to read the images from the camera while using the built in white LED as a source of excitation. Using classification algorithm and AI, the software should be able to return the concentration with predicted accuracy that would be obtained from the training and testing stages. Finally, the produced software will be tested in both lab and field environments to estimate the efficiency, durability and accuracy of the device.

Advisor: Romuald Jolivot

Description: Expected outcome: Experimental unit to measure VOC for smart clothes 
Duration: 3-9 months 
Number of students: 1 
Prerequisite: Programming skills, basic image processing, AI knowledge. 
Software: Python, OpenCV, AI toolboxes

2023-11-15

3D laser scanner using Arduino platform

The project aims to develop a low cost 3D scanner using laser diode, servo motor and Arduino platform. A cylindrical lens is placed in front of the laser to generate a line profile.Both lens and laser are placed on the motor to allow angular scan using Arduino. A webcam is used to capture a frame for each angular scan. Image processing is then used to construct the 3D dot space. This is then converted in standard 3D object format.

Advisor: Waleed Mohammed

Description: The work involves: 1- Building the setup using laser, servo and arduino. 2- Developing the Arduino interface with the motor through and PC using pyFirmata2 library in Python library. 3- Building a GUI that controls the scan and capturing the images. 4- Transferring the image frames into 3D dot space. 5- Conversion to 3D object format.

2023-11-15

Multispectral scanning microscope

The project aims to develop a low cost multispectral scanning microscope that records both microscopic images of the sample and spectral information. The sample is placed on x-y moving stages that are to be built locally. The stages and image acquisition are to be performed by PC interfaced with Arduino through pyformata library. The spectrometer is to be built using a grating and a webcam.

Advisor: Waleed Mohammed

Description: The work involves: 1- Building a microscope using a webcam, optical lens and 3d printing. 2- Building a low cost optical spectrometer using grating and a webcam. 3- Building an x-y moving stage using DC motors and Arduino control. 4- Setup assembly to form the desired system. 4- Image acquisition and processing to extract the microscope images as well as the optical spectrum. 5- Generate an array of images and spectrum for each point in the two dimensional scans.

2023-10-02

Flexible waveguide sensors

Use of flexible substrate as a waveguide for optical sensing of strain, heat and humidity sensing. The work focuses on utilizing available optical materials such as transparent papers and transparent PLA 3D printing for the formation of the device. The project as well utilizes the concepts of wave guiding, scattering and surface Plasmon resonance for the sensing mechanism.

Advisor: Waleed Mohammed

Description: The work involves: 1- Building basic understanding of light, wave guiding and sensing. 2- Desing and building optical components using available materials. 3- Optical characterization using spectrometry and photometers. 4- Using IoT platform for data collection and analysis.

2023-10-02

Plastic optical fiber volatile oraganic compounds sensor

Plastic optical fibers are easy to handle and are cheap in cost. The project uses plastic optical fiber as a guiding region from source to detector. Scattering region is induced on the fiber using polishing techniques to generate a loss mechanism. When volatile compounds condense on the fiber, scattering is reduced and signal increases. The change of the light intensity with the concentration of the compound determines the device sensitivity. Inctreasing the sensitivity requires optimization of the polishing process and the segment length. Several fibers can be used as well in parallel to enhance the signal to noise ratio.

Advisor: Waleed Mohammed

Description: The work involves: 1- Building basic understanding of light, wave guiding and sensing.2- Desing and building optical sensor using plastic fiber and polishing technique. 3- Using IoT platform for light launching and data collection and analysis.

2023-10-02

Theoretical modeling of nano-particles in polymer for optical spectrum manipulation

Embedding nanoparticles in polymer is a promising topic due to the flexibility of implementation and the many degrees of freedom that one has when designing an optical device. When impending particles, there are few parameters to control such as particles concentration and the thickness to which these particles travel inside the polymer. When the particles are included a film is formed with typically higher refractive index. That allows for the manipulation of the transmitted light spectrum. Hence, with proper particles type and parameters selection a specific optical spectrum can be achieved.

Advisor: Waleed Mohammed

Description: The work involves: 1- Building basic understanding of light, effective medium theory, optical interference and guiding. 2- Using Python as the programming tool. 3- Building a software package for estimating the optical device performance.

2023-08-13

Demonstration of Digital Wireless Transmissions Using Software Defined Radio with HackRF One Modules

The student will demonstrate a digital wireless transmission system using software defined radio with the GNU Radio software and HackRF One hardware. Commonly used modulation schemes, e.g., quadrature amplitude modulation (QAM), will be considered. In addition to learning about the fundamentals of digital communication systems, the developed demonstration systems may later be used in laboratory experiments for teaching digital communications.

Advisor: Poompat Saengudomlert

Description: Expected outcome: A demonstration wireless transmission system that can operate using one of multiple modulation schemes, including QAM, and some experimental results with comparison to theoretical predictions; Duration: 3-6 months; Hardware: HackRF One modules; Software: GNU Radio, Python

2023-08-13

Development of an Indoor Object Tracking System Using Visible Light Communications

The student will develop and test an indoor object tracking system prototype using visible light communications (VLC) through commercial LED lamps. Its potential application is tracking a moving robot in a smart warehouse. For energy savings, dimming techniques will be implemented so that localization can be done even when different LED lamps operate at different dimming levels. The developed system will offer an alternative to GPS based tracking, which is not available for indoor environments.

Advisor: Poompat Saengudomlert

Description: Expected outcome: A prototype system with LED lamps and a mobile VLC receiver sending its location to a server that displays its location and records data; Duration: 3-6 months; Hardware: LED lamps, photodiodes, related circuit components, microcontrollers (e.g., Arduino, NodeMCU), FPGAs; Software: Verilog/VHDL, Arduino IDE, Python

2023-03-21

1. Optical Bioimaging Device and Image Processing Algorithm for Detecting a Non-invasive Biomarker on Skin for Medical Diagnosis

Skin autofluorescence (AF) is a noninvasive measure of the level of tissue accumulation of advanced glycation end products. The value of skin AF has a strong correlation with microvascular complication from hyperglycemia. The skin AF can be used to predict the microvascular complications which is one of the risk factors to develop organ damage. This project aims to develop biomedical imaging system to detect the AF to reduce the risk of microvascular complications. The system includes the development of optical bioimaging device and image processing algorithm. This proposed preventive medicine will help improve the quality of life to the patients.

Advisor: Wisarn Patchoo

Description:

2023-03-21

FPGA-Based Digital Lock-in Amplifier

The detection of weak signals under complex background noise is a cutting-edge technology in scientific research, geo- logical exploration, biomedical science, military, aerospace, and other fields [1]–[3]. Relevant scholars have done a lot of fruitful research in this key field and proposed a variety of detection methods, from the detection methods of linear theory such as the conventional time domain, frequency domain, and time-frequency domain, to the detection methods of non- linear theory such as chaos and stochastic resonance. Lock-in amplifier is a mature solution with strong detection ability and high reliability in many weak signal detection schemes. This project is trying to implement Digital Lock-In Amplifier (DLIA) using FPGA and DSP builder.

Advisor: Wisarn Patchoo

Description:

2022-11-09

Development of AI-based Bakery Cashier

In this project, you will design and build a semi-automatic breads scanner that can recognize different kind of breads in a bakery. The bread scanning and recognizing are done via the well established object detection procedure which is widely used in the field of image and video analysis. The system shall also be able to compute the total cost for the recognized breads. Therefore, the database and related user interface shall also be designed and developed. The object detection part of the system is meant to be implemented on the edge device such as nvidia jetson or other tinyML micro-controllers. Target industry: Bakery shops in Thailand. Keywords: Object detection, Machine learning, Edge computing.

Advisor: Dr. Pakorn Ubolkosold

Description: Expected outcome: A system prototype that can scan and recognize different type of breads available in a bakery. It can also compute the total amount of cost associated with the recognized breads. Used tools and software: Python, Nvidia Jetson, MySQL (database)

2022-10-11

Combination of Visible Light Communication (VLC) and Power Line Communication (PLC) allowing for data signals to be transported over in-house lighting infrastructures.

Due to their capacity of switching on and off rapidly, LEDs for general lighting can also be used to transmit communication signals, a concept that is known as Visible Light Communication (VLC). General lighting uses copper wire to connect the various lamps. The concept to transport communication signals over copper wire that is simultaneous used as a power line is known as Power Line Communication (PLC). In this project, the modulation method for PLC signal will be Frequency Shift Keying (FSK), whereas VLC employs the Intensity Modulation/Direct Detection (IM/DD) format. At the start of the project, students will be given a thorough introduction about the overall system after which they start working at certain areas of the system. Whenever required, students will also be given a hands-on tutorial on software packages they may need to employ.

Advisor: Karel Sterckx

Description: Expected outcome: Students are required to simulate and create hardware (including PCB design) of certain areas of the system.Number of students: 1-2Prerequisite: Knowledge of both analogue electronics, especially RLC circuitry and transformers, digital electronics. For the latter, knowledge of FPGA and its programming is helpful though not a must.Hardware: Terasic DE0-CV Development board, Software: Intel Quartus Prime, RS DesignSpark PCB

2022-10-11

Extending the transmission bandwidth of Light Emitting Diodes (LEDs)

The bandwidth of LEDs for general lighting is about 10-20 MHz when a blue filter is place in front of a photodiode. The reason for the blue filter is that LEDs for general lighting are in fact blue lights with a yellow phosphor place in front of them. The yellow phosphor acts also as a Low Pass Filter (LPF), which causes the bandwidth of the LED to drop to about an order of magnitude. In order to extend this bandwidth with external electronic circuitry, the equivalent circuit of LEDs needs to be determined. Actually, the equivalent circuit of LEDs is known and the values of the components can be determined by means of a network analyser. However, a network analyser is expensive and the measurement method complicated. As such, a simpler procedure with less expensive measurement equipment needs to be developed. After the specifics of the LED’s equivalent circuit have been determined an electronic circuit counteracts the needs to be developed and implemented on PCB. Towards this end, hands-on training on Printed Circuit Board (PCB) design using the Electronic Design Environment (EDA) RS DesignSpark PCB will be provided. The developed circuitry will be tested with various LEDs and LED lamps.

Advisor: Karel Sterckx

Description: Expected outcome: A low-cost method to determine the values of the components in the equivalent circuit of LEDs. A PCB with circuitry that counteracts the LPF characteristic of the LED and extends the LED’s bandwidth.

Data Fusion and AI in Indoor Smart Farming

Development of nutrient sensors based on light attenuation

Image Processing monitoring for indoor smart farm

Development of robot for data collection and acquisition using VLP

Image processing for Smart Interactive Museum Display

Development of acquisition systems for holographic-like artifacts

Inverse Panorama Acquisition System

AI for gas detection

Development of a mobile robot system for collecting and transporting infectious waste in hospital

AI for wearable VOC detection on smart clothes

3D laser scanner using Arduino platform

Multispectral scanning microscope

Flexible waveguide sensors

Plastic optical fiber volatile oraganic compounds sensor

Theoretical modeling of nano-particles in polymer for optical spectrum manipulation

Demonstration of Digital Wireless Transmissions Using Software Defined Radio with HackRF One Modules

Development of an Indoor Object Tracking System Using Visible Light Communications

1. Optical Bioimaging Device and Image Processing Algorithm for Detecting a Non-invasive Biomarker on Skin for Medical Diagnosis

FPGA-Based Digital Lock-in Amplifier

Development of AI-based Bakery Cashier

Combination of Visible Light Communication (VLC) and Power Line Communication (PLC) allowing for data signals to be transported over in-house lighting infrastructures.

Extending the transmission bandwidth of Light Emitting Diodes (LEDs)