The development of a fruit spoilage detection system originates from the need to reduce agricultural product losses, a global issue affecting both the agricultural and food distribution industries. Spoiled fruit can negatively impact product quality and result in significant economic losses. The primary goal of this system is to assist in screening and removing unsuitable fruit from the supply chain, thereby preserving product quality and meeting consumer demands for fresh produce. The system was designed to simulate the sorting process by utilizing images as a key factor in detecting spoiled fruit. Experimental results demonstrated high efficiency and rapid prediction capabilities, highlighting the system’s potential for practical applications.
ระบบตรวจจับผลไม้เน่ามีที่มาจากความต้องการในการลดการสูญเสียผลผลิตทางการเกษตร ซึ่งเป็นปัญหาที่เกิดขึ้นทั่วโลกโดยเฉพาะในอุตสาหกรรมการเกษตรและการจัดจําหน่ายอาหาร ผลไม้ที่เน่าเสียจะส่งผลกระทบต่อคุณภาพของผลิตภัณฑ์และสามารถก่อให้เกิดความสูญเสียทางเศรษฐกิจได้อย่างมาก การพัฒนาระบบตรวจจับผลไม้เน่าจึงมีเป้าหมายเพื่อช่วยในการคัดกรองและแยกผลไม้ที่ไม่เหมาะสมออกจากกระบวนการจัดส่ง เพื่อรักษาคุณภาพของสินค้าและตอบสนองต่อความต้องการของผู้บริโภคที่ต้องการผลไม้สดใหม่
คณะอุตสาหกรรมอาหาร
The "PRIVARY" product is an innovative herbal jelly beverage designed to support weight management and promote health through the benefits of four Thai herbs: roselle, safflower, chrysanthemum, and bitter melon. These herbs are rich in active compounds such as flavonoids, beta-carotene, and anthocyanins, which help reduce blood lipids, prevent inflammation, and exhibit antioxidant properties. The product emphasizes convenience and caters to health-conscious consumers using advanced production techniques like Inverse and External Gelation to create spheres encapsulating key bioactive compounds. Additionally, the product aligns with sustainability goals by enhancing the value of Thai herbs and supporting local communities.
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
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.