
The Public Park Project: Bubbledel Park is a new-style public park located at Suan Phra Nakhon in Lat Krabang District, Bangkok. Designed to be modern and entertaining, the park incorporates the concept of using bubbles to add vibrancy and create a unique connection with nature, unlike any other place.
สวนสาธารณะที่เกิดด้วยจินตนาการที่เต็มไปด้วยความมหัศจรรย์และความสุข สวนแห่งนี้โดดเด่นด้วยพื้นที่สีเขียวเข้ามาประดับประดาไปด้วยฟองอากาศที่เปรียบเสมือนลอยขึ้นสู่ท้องฟ้า ให้เห็นสีสันที่สวยงาม แต่ยังสามารถสัมผัสได้และให้ความรู้สึกเหมือนอยู่ในโลกแห่งความฝัน ถูกออกแบบมาเพื่อให้ผู้คนได้ผ่อนคลาย สนุกสนาน และเชื่อมต่อกับธรรมชาติในแบบที่ไม่เหมือนที่ใด แบ่งโซนได้อย่างชัดเจน นอกจากนี้ ยังมีกิจกรรมที่น่าสนใจ เช่น การเล่นกีฬากลางแจ้ง เวที และลานอเนกประสงค์ในการชมการแสดงต่างๆ ทำให้ที่นี่เป็นสถานที่ในอุดมคติสำหรับทุกเพศ ทุกวัย

คณะวิทยาศาสตร์
This work presents the fabrication of the handheld meter for potentiometric detection of Hg (II). The meter was constructed based on using an ion-sensitive field-effect transistor (ISFET) platform. The developed meter provides high accuracy and precision (%Recovery was in the range of 92.55 - 109.32 and %RSD was 2.38). It was applied to the analysis of cosmetic samples. The results by the developed electrode were not significantly different at a 95% confidence level compared to the results by using ICP-OES.

คณะวิทยาศาสตร์
This project presents the development of an automatic recycling machine for plastic bottles and cans, utilizing Machine Learning for packaging classification through image processing, integrated with smart sensor systems for quality inspection and operation control. The system connects to a Web Application for real-time monitoring and control. Once the packaging type is verified, the system automatically calculates the refund value and processes payment through e-wallet or issues cash vouchers. The system can be installed in public spaces to promote waste segregation at source, reduce contamination, and increase recycling efficiency. It also provides financial incentives to encourage public participation in waste management. This project demonstrates the potential of combining Machine Learning and smart sensor systems in developing accurate, convenient, and sustainable waste management solutions.

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.