Developing a Smart Farming Simulation Utilizing LoRa Communication and Presenting Knowledge on LoRa Communication System Components
เทคโนโลยี LoRa (Long Range) เป็นเทคโนโลยีที่สามารถสื่อสารข้อมูลได้ระยะไกลที่สุดในหลักกิโลเมตร ใช้พลังงานต่ำและไม่มีค่าบริการรายเดือน จึงเหมาะกับการพัฒนาการเกษตรซึ่งมีพื้นที่กว้างและWifiเข้าไม่ถึง ในรูปแบบของการทำเกษตรอัจฉริยะด้วยระบบการสื่อสารแบบLoRa
คณะสถาปัตยกรรม ศิลปะและการออกแบบ
A Photographic series that expresses the abstract states of myself, towards the question of existence that results from being surrounded by expectations of both surrender and freedom of expression, this series focuses on my own subjectivities in order to bring back memories of almost forgotten feelings and make them clear once more.
คณะเทคโนโลยีการเกษตร
Capsicum chinense is a high-potential economic crop in the food and pharmaceutical industries due to its role as a primary source of capsaicin, a bioactive compound with significant physiological effects. However, capsaicin levels and fruit quality will be influenced by genetic factors, environmental conditions, and genetic-by-environment (G×E) interactions, leading to variability in capsaicin biosynthesis. This study will aim to analyze the impact of different environmental conditions on the growth, fruit quality, and capsaicin content of C. chinense ‘Scotch Bonnet’. The field experiments will be conducted at the demonstration plots of the Faculty of Agricultural Technology, King Mongkut’s Institute of Technology Ladkrabang, during two growing seasons: July–October (rainy season) and December–April (dry season). Four condition environments will be evaluated, and environmental parameters such as temperature, relative humidity, and light quality will be monitored to assess their effects on plant physiology and capsaicin biosynthesis. Additionally, an F1 hybrid breeding program will be established using six parental lines through a Half-diallel mating design, generating 15 hybrid combinations. The general combining ability (GCA) and specific combining ability (SCA) will be assessed to identify promising hybrid combinations with high and stable capsaicin content and yield. The findings from this study will be expected to provide valuable insights into optimizing cultivation conditions for high-pungency chili production and supporting the development of F1 hybrid seeds with commercial viability and consistent capsaicin levels.
คณะวิทยาศาสตร์
Currently, climate change and human activities are causing rapid deterioration of coral reefs worldwide. Monitoring coral health is essential for marine ecosystem conservation. This project focuses on developing an Artificial Intelligence (AI) model to classify coral health into four categories: Healthy, Bleached, Pale, and Dead using Deep Learning techniques. With pre-trained convolutional neural network (CNN) for image classification. To improve accuracy and mitigate overfitting, 5-fold Cross-Validation is employed during training, and the best-performing model is saved. The results of this project can be applied to monitor coral reef conditions and assist marine scientists in analyzing coral health more efficiently and accurately. This contributes to better conservation planning for marine ecosystems in the future.