Design and Development of a Remote Battery Management System This research focuses on the design and development of a battery management system that enables remote monitoring and control, allowing users to customize battery cell properties as needed. The system is specifically designed for use with graphene battery cells and can be effectively applied to alternative energy systems for residential use.
1. เพิ่มประสิทธิภาพการจัดการพลังงาน – ระบบบริหารจัดการแบตเตอรี่ที่สามารถควบคุมและมอนิเตอร์ระยะไกลช่วยให้สามารถจัดการพลังงานได้อย่างมีประสิทธิภาพ ลดการสูญเสียพลังงาน และเพิ่มอายุการใช้งานของแบตเตอรี่ 2. รองรับเทคโนโลยีแบตเตอรี่กราฟีน – แบตเตอรี่กราฟีนมีศักยภาพสูงในการเก็บพลังงานและมีอายุการใช้งานยาวนาน โครงการนี้ช่วยทดสอบและพัฒนาการนำแบตเตอรี่กราฟีนไปใช้ในระบบพลังงานทางเลือก 3. เพิ่มความสะดวกและความปลอดภัยในการใช้งาน – การควบคุมและมอนิเตอร์แบตเตอรี่จากระยะไกลช่วยลดความเสี่ยงจากการเกิดปัญหาทางเทคนิค เช่น การชาร์จไฟเกินหรืออุณหภูมิสูงเกินไป ทำให้ระบบมีความปลอดภัยมากขึ้น 4. ส่งเสริมการพัฒนาเทคโนโลยีภายในประเทศ – โครงการนี้ช่วยสนับสนุนการพัฒนาเทคโนโลยีแบตเตอรี่และระบบบริหารจัดการพลังงานภายในประเทศ ลดการพึ่งพาเทคโนโลยีจากต่างประเทศ และเพิ่มขีดความสามารถในการแข่งขันด้านพลังงาน
คณะอุตสาหกรรมอาหาร
Fish gelatin is increasingly recognized as an alternative source of gelatin, but its use has been limited due to weak gelling properties. To address these issues, the effect of furcellaran, a gelling agent, was examined at various levels (25-100% FG substitution) on the structural and physicochemical properties of FG gels. As the amount of FUR increased to 25%, the FG/FUR gel showed improved hardness and gel strength (P<0.05). Additionally, increasing FUR levels led to higher gelling and melting points, showing a dose-dependent relationship. Microstructural analysis revealed that adding FUR created a denser gel network with smaller gaps. SAXS scattering intensities also increased as FUR concentration rose. Overall, adding FUR improved the gelling properties of FG without negatively affecting springiness and syneresis, enhancing gel strength and gelling temperature.
วิทยาเขตชุมพรเขตรอุดมศักดิ์
This project aims to design and develop an eye-tracking system to facilitate communication for paralyzed immobile patients. The system is designed to enable patients to convey their needs to caregivers or family members by detecting and tracking eye movements using the Tobii Eye Tracker 5 device. This approach serves as an alternative communication method, replacing the physical movement or speech of paralyzed patients. The system effectively detects and tracks eye movements at a distance of 55 to 85 centimeters and is designed for installation on a computer to ensure ease of use. The program interface consists of three main sections: (1) a set of emotions, (2) a set of needs, and (3) a set of additional needs. It supports input from a virtual keyboard in both Thai and English and allows users to specify additional needs through eye-tracking-enabled typing. Furthermore, the system can generate synthetic speech for text that is difficult to pronounce aloud, send notification messages via the Line application, and store usage data in a database presented in a dashboard format. System testing revealed that the optimal detection distance ranges from 65 to 75 centimeters, as this range yields an error rate of no more than 1 percent. The system accurately responds to eye movements for communication through sound within 3 seconds when interacting with various function buttons. This eye-tracking system effectively enables paralyzed immobile patients to communicate their emotions and needs, facilitating better understanding and interaction between patients and their caregivers or family members.
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.