In raising crickets for meat consumption, the growth rate and growth period of crickets are important data used to identify the number of crickets per breeding area at each age. Therefore, the researcher has an idea to create a system for monitoring the growth rate of crickets in a closed system using an infrared camera combined with computer image processing to study the growth and identify the growth period of crickets at each age in order to obtain knowledge that can be disseminated to farmers to improve the breeding process for maximum efficiency.
ปัจจุบันจิ้งหรีดถือได้ว่าเป็นสัตว์เศรษฐกิจชนิดใหม่ของประเทศไทยซึ่งทางภาครัฐโดยเฉพาะกรมปศุสัตว์ได้เริ่มมีการส่งเสริมให้ภาคการเกษตรได้เพาะเลี้ยงจิ้งหรีดเพื่อการบริโภคสำหรับการส่งออก และเป็นการตอบรับกับเทรนด์อุตสาหกรรมอาหารใหม่ (Novel food) ตามแนวทางขององค์การอาหาร และเกษตรแห่งสหประชาชาติ (FAO : Food and Agriculture Organization) ซึ่งคาดการณ์เอาไว้ว่าจำนวนประชากรโลกจะเพิ่มขึ้นอย่างต่อเนื่องทำให้ความต้องการแหล่งโปรตีนมีมากขึ้นตามไปด้วย คณะผู้วิจัยจึงมีแนวความคิดที่จะหาสร้างระบบเลี้ยงจิ้งหรีดที่มีประสิทธิภาพ
คณะศิลปศาสตร์
Layla, the hotel robot, is responsible for carrying guests’ luggage and guiding them to their accommodations. It is equipped with an internal map of the hotel, allowing it to navigate various locations efficiently. Additionally, it features an AI-powered system that enables interactive conversations in three major languages: Thai, English, and Chinese.
คณะวิศวกรรมศาสตร์
The Thai Sign Language Generation System aims to create a comprehensive 3D modeling and animation platform that translates Thai sentences into dynamic and accurate representations of Thai Sign Language (TSL) gestures. This project enhances communication for the Thai deaf community by leveraging a landmark-based approach using a Vector Quantized Variational Autoencoder (VQVAE) and a Large Language Model (LLM) for sign language generation. The system first trains a VQVAE encoder using landmark data extracted from sign videos, allowing it to learn compact latent representations of TSL gestures. These encoded representations are then used to generate additional landmark-based sign sequences, effectively expanding the training dataset using the BigSign ThaiPBS dataset. Once the dataset is augmented, an LLM is trained to output accurate landmark sequences from Thai text inputs, which are then used to animate a 3D model in Blender, ensuring fluid and natural TSL gestures. The project is implemented using Python, incorporating MediaPipe for landmark extraction, OpenCV for real-time image processing, and Blender’s Python API for 3D animation. By integrating AI, VQVAE-based encoding, and LLM-driven landmark generation, this system aspires to bridge the communication gap between written Thai text and expressive TSL gestures, providing the Thai deaf community with an interactive, real-time sign language animation platform.
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.