The Ginbanirose project aims to develop herbal extracts for alleviating menstrual pain using key ingredients: roselle, banana inflorescence, and ginger. These ingredients contain bioactive compounds with anti-inflammatory, antioxidant, and pain-relieving properties. The extracts are enhanced through liposome encapsulation technology, which improves absorption and stability. The production process involves herbal extraction, freeze-drying, and liposome formulation using lecithin and stabilizers. Experimental results demonstrate high phenolic content and antioxidant activity via the DPPH method. Ginbanirose addresses women’s quality of life concerns while offering significant business opportunities in the rapidly growing herbal market, particularly in the Asia-Pacific region.
ปัจจุบันผู้บริโภคให้ความสำคัญกับผลิตภัณฑ์จากธรรมชาติมากขึ้น โดยเฉพาะผลิตภัณฑ์ที่มีสารสกัดจากพืชสมุนไพรซึ่งมีคุณสมบัติที่ดีต่อสุขภาพและความงาม Ginbanirose เป็นหนึ่งในนวัตกรรมที่เกิดจากการผสานคุณสมบัติของพืชสมุนไพรไทยที่มีศักยภาพ เช่น กระเจี๊ยบแดง ขิง และปลีกล้วย ซึ่งอุดมไปด้วยสารต้านอนุมูลอิสระ และมีสรรพคุณที่เป็นประโยชน์ต่อร่างกาย การศึกษาคุณสมบัติของพืชเหล่านี้และพัฒนาให้เป็นผลิตภัณฑ์ที่สามารถใช้งานได้อย่างมีประสิทธิภาพจึงเป็นเรื่องสำคัญ ไม่เพียงแต่ช่วยเพิ่มมูลค่าให้กับพืชสมุนไพรไทยเท่านั้น แต่ยังเป็นแนวทางในการพัฒนาผลิตภัณฑ์ที่เป็นมิตรต่อสิ่งแวดล้อมและตอบสนองต่อความต้องการของตลาดสุขภาพและความงาม การใช้เทคนิค Liposome Encapsulation เพื่อเพิ่มความคงตัวและประสิทธิภาพของสารสำคัญจากพืช เป็นแนวทางหนึ่งที่ช่วยให้สามารถพัฒนา Ginbanirose ให้เป็นผลิตภัณฑ์ที่มีคุณภาพสูงและสามารถแข่งขันในตลาดได้ ดังนั้น งานวิจัยนี้จึงมีความสำคัญในการส่งเสริมการใช้ประโยชน์จากพืชสมุนไพรไทย พัฒนาผลิตภัณฑ์ที่มีคุณภาพ และสร้างมูลค่าเพิ่มให้กับวัตถุดิบธรรมชาติ เพื่อรองรับแนวโน้มของตลาดที่มุ่งสู่ผลิตภัณฑ์เพื่อสุขภาพและความงามที่ปลอดภัยและมีประสิทธิภาพสูง
คณะวิศวกรรมศาสตร์
The integration of intelligent robotic systems into human-centric environments, such as laboratories, hospitals, and educational institutions, has become increasingly important due to the growing demand for accessible and context-aware assistants. However, current solutions often lack scalability—for instance, relying on specialized personnel to repeatedly answer the same questions as administrators for specific departments—and adaptability to dynamic environments that require real-time situational responses. This study introduces a novel framework for an interactive robotic assistant (Beckerle et al. , 2017) designed to assist during laboratory tours and mitigate the challenges posed by limited human resources in providing comprehensive information to visitors. The proposed system operates through multiple modes, including standby mode and recognition mode, to ensure seamless interaction and adaptability in various contexts. In standby mode, the robot signals readiness with a smiling face animation while patrolling predefined paths or conserving energy when stationary. Advanced obstacle detection ensures safe navigation in dynamic environments. Recognition mode activates through gestures or wake words, using advanced computer vision and real-time speech recognition to identify users. Facial recognition further classifies individuals as known or unknown, providing personalized greetings or context-specific guidance to enhance user engagement. The proposed robot and its 3D design are shown in Figure 1. In interactive mode, the system integrates advanced technologies, including advanced speech recognition (ASR Whisper), natural language processing (NLP), and a large language model Ollama 3.2 (LLM Predictor, 2025), to provide a user-friendly, context-aware, and adaptable experience. Motivated by the need to engage students and promote interest in the RAI department, which receives over 1,000 visitors annually, it addresses accessibility gaps where human staff may be unavailable. With wake word detection, face and gesture recognition, and LiDAR-based obstacle detection, the robot ensures seamless communication in English, alongside safe and efficient navigation. The Retrieval-Augmented Generation (RAG) human interaction system communicates with the mobile robot, built on ROS1 Noetic, using the MQTT protocol over Ethernet. It publishes navigation goals to the move_base module in ROS, which autonomously handles navigation and obstacle avoidance. A diagram is explained in Figure 2. The framework includes a robust back-end architecture utilizing a combination of MongoDB for information storage and retrieval and a RAG mechanism (Thüs et al., 2024) to process program curriculum information in the form of PDFs. This ensures that the robot provides accurate and contextually relevant answers to user queries. Furthermore, the inclusion of smiling face animations and text-to-speech (TTS BotNoi) enhanced user engagement metrics were derived through a combination of observational studies and surveys, which highlighted significant improvements in user satisfaction and accessibility. This paper also discusses capability to operate in dynamic environments and human-centric spaces. For example, handling interruptions while navigating during a mission. The modular design allows for easy integration of additional features, such as gesture recognition and hardware upgrades, ensuring long-term scalability. However, limitations such as the need for high initial setup costs and dependency on specific hardware configurations are acknowledged. Future work will focus on enhancing the system’s adaptability to diverse languages, expanding its use cases, and exploring collaborative interactions between multiple robots. In conclusion, the proposed interactive robotic assistant represents a significant step forward in bridging the gap between human needs and technological advancements. By combining cutting-edge AI technologies with practical hardware solutions, this work offers a scalable, efficient, and user-friendly system that enhances accessibility and user engagement in human-centric spaces.
คณะวิศวกรรมศาสตร์
One of the most important aspects of responding to a medical case is the response time. In general, most fatalities are due to the patient not being able to reach the hands of the doctor in time. This also includes the arrival of medical equipment to the scene. The human brain will start to degrade in function after 3 minutes of oxygen starvation which conventional road transportation method first responders presently use is usually unable to reach the site in this golden 3 minutes, resulting in fatalities during transport or before the arrival of first responders at the scene. Therefore, medical equipment transport by fully autonomous aircraft is explored. This is done through drone deliveries which is much quicker than road methods as the equipment could be flown straight to the site as it is not affected by traffic, road conditions, and navigation. In this project, we will explore an aerial delivery system for medical equipment such as Automatic External Defibrillators (AEDs), First aid equipment, and other small requested medical devices. This will be done through a DJI drone platform and their SDK application. The main goal for this project is to decrease the response time by using an autonomous aerial drone to deliver medical equipment.
คณะเทคโนโลยีการเกษตร
Soil is home to a diverse array of living organisms that interact within a complex food web, facilitating energy and nutrient cycling essential for sustaining life above ground. Among these organisms, soil microbes play a crucial role in supporting plant growth. Beneficial microorganisms enhance nutrient availability, improve soil structure by increasing porosity, and strengthen plant resistance to diseases. Conversely, harmful microorganisms, such as plant pathogens, can hinder plant growth and reduce crop yields when present in high concentrations. Neutral microorganisms, which naturally inhabit the soil, contribute to the soil ecosystem without directly impacting plants. A single teaspoon of soil contains over a billion microorganisms, yet only about 1% of them can be cultured in laboratory conditions. This highlights soil as one of the richest reservoirs of microbial diversity on Earth.