This research focuses on the design and development of a prototype Artificial Intelligence of Things (AIoT) system for monitoring and controlling irrigation using weather information. The system consists of four main components: 1) Weather Station – This component includes various sensors such as air temperature, relative humidity, wind speed, and sunlight duration, among others, to collect real-time weather data. 2) Controller Unit – This unit is equipped with machine learning algorithms or models to estimate the reference evapotranspiration (ETo) and calculate the plant’s water requirement by integrating the crop coefficient (Kc) with other plant-related data. This enables the system to determine the optimal irrigation amount based on plant needs automatically. 3) User Interface (UI) and Display – This section allows farmers or users to input relevant information, such as plant type, soil type, irrigation system type, number of water emitters, planting distance, and growth stages. It also provides a display for monitoring and interaction with the system. 4) Irrigation Unit – This component is responsible for controlling the water supply and managing the irrigation emitters to ensure efficient water distribution based on the calculated requirements.
การเปลี่ยนแปลงสภาพอากาศของโลกทวีความรุนแรงขึ้นอย่างต่อเนื่อง สถานการณ์ดังกล่าวส่งผลกระทบ โดยตรงต่อภาคการเกษตร โดยเฉพาะในประเทศไทยที่มีแนวโน้มเผชิญกับปัญหาการขาดแคลนน้ำและความ ผันผวนของปริมาณน้ำฝน ซึ่งส่งผลต่อทั้งปริมาณและคุณภาพของผลผลิตทางการเกษตรโดยตรง ทั้งนี้ การบริหารจัดการน้ำในภาคเกษตรกรรมของประเทศไทยยังคงเผชิญกับข้อจำกัดหลายประการ เกษตรกรส่วนใหญ่ยังคงพึ่งพาประสบการณ์ส่วนตัวในการให้น้ำพืช ซึ่งอาจนำไปสู่การใช้น้ำที่ไม่มีประสิทธิภาพ เช่น การให้น้ำมากเกินความจำเป็นหรือน้อยเกินไปจนส่งผลกระทบต่อผลผลิต หรืออาจนำไปสู่ปัญหา เช่น การแตกใบอ่อน การร่วงของดอก และมีผลผลิตที่ไม่ได้คุณภาพ (Togneri et al., 2023) ในขณะที่ข้อมูลทาง วิชาการที่สามารถช่วยให้การบริหารจัดการน้ำมีความแม่นยำขึ้น เช่น ค่าอัตราการใช้น้ำของพืชอ้างอิง (Evapotranspiration: ETo) และค่าสัมประสิทธิ์พืช (Kc) กลับเข้าถึงได้ยาก เนื่องจากมีความซับซ้อนในการ คำนวณ อีกทั้งข้อมูลที่มีอยู่มักเป็นข้อมูลเฉลี่ยรายจังหวัดซึ่งไม่สามารถนำไปใช้ได้อย่างมีประสิทธิภาพในระดับ ฟาร์ม โครงการนี้จึงมุ่งเน้นไปที่การพัฒนาระบบปัญญาประดิษฐ์สำหรับการติดตามและควบคุมการให้น้ำพืชอัจฉริยะ โดยอิงข้อมูลสภาพอากาศซึ่งจะช่วยแก้ไขข้อจำกัดของเกษตรกรไทยในการเข้าถึงข้อมูลที่ ถูกต้องและการบริหารจัดการน้ำที่แม่นยำ
คณะอุตสาหกรรมอาหาร
The growing interest in antioxidant-rich foods is driven by their potential to reduce the risk of chronic diseases such as cancer, cardiovascular conditions, and cellular degeneration. Ginger (Zingiber officinale), banana inflorescence (Musa paradisiaca L.), and roselle (Hibiscus sabdariffa L.) are herbal plants known for their high phenolic content, a crucial component in antioxidant activity. However, the bioactive compounds in these plants are often unstable when exposed to light, temperature, and oxygen, leading to a reduction in their efficacy. This study aims to investigate the optimal ratio of ginger, banana inflorescence, and roselle for encapsulation in liposomes—a technique designed to enhance the stability of bioactive compounds and improve their delivery efficacy. The research evaluates the antioxidant activity of the extracts using DPPH, ABTS, and FRAP methods, alongside total phenolic content (TPC) measurement. The most effective ratio for antioxidant activity will be selected for liposomal encapsulation, employing phospholipids as key structural components. The encapsulation efficiency (EE%) will be calculated to assess the effectiveness of the liposomal delivery system. The findings are expected to identify the optimal combination of ginger, banana inflorescence, and roselle that maximizes antioxidant potency and enhances the stability of bioactive compounds through liposomal encapsulation. This approach offers a promising strategy for developing herbal health supplements that maintain their biological properties over time.
คณะเทคโนโลยีสารสนเทศ
The project of game development to educate about Egyptian civilization This is intended to be a game to promote learning about ancient Egyptian civilization. The original learning may feel boring. Do not attract the attention of learners Therefore saw the presentation in the form of a game on virtual reality technology that inserts knowledge history With the aim of making learning more interesting The organizers can choose to use Unreal Engine 5.1 (Unreal Engine 5.1) and Oculus Quest II (Oculus Quest2) to develop. Within the game, players must find a way to escape from this room within the specified period of solving puzzles in various forms such as statues, traps, etc. In order to solve puzzles and leave this room, players must collect all the information inside the room. In addition, the game shows the life of the player and when the player cannot solve the puzzle correctly.
คณะครุศาสตร์อุตสาหกรรมและเทคโนโลยี
This aimed to 1) develop an effective augmented reality (AR) media integrated with the metaverse to enhance English phonics and communication skills. 2) To evaluate English pronunciation skills using augmented reality media integrated with the metaverse, and 3) To assess English communication skills through interactions within the metaverse. The sample group comprised 120 Grade 4 students from two classrooms in the first semester of the 2024 academic year, selected through cluster random sampling and divided into experimental and control groups. The research instruments included AR media sets, media quality assessment forms, phonics tests, and English communication skills assessment forms, administered before and after the learning intervention. Data analysis employed mean (x ̅), standard deviation (S), t-tests for independent samples, and one-way analysis of variance (Multivariate Analysis of Variance: One-Way MANOVA) to compare mean score differences between the experimental and control groups. Results indicated that the overall quality of the AR media kit with the metaverse was rated at a very high level (x ̅= 4.80, S.D. = 0.12). Evaluating specific aspects showed that the content quality was at the highest level (x ̅= 4.92, S.D. = 0.07), while the media production technique also rated highly (x ̅ = 4.70, S.D. = 0.17). Furthermore, the English pronunciation and communication skills of the Grade 4 students using the AR media with the metaverse were significantly higher after the intervention compared to before, the overall quality of the AR media integrated with the metaverse was rated at the highest level (x ̅= 4.80, S.D. = 0.12). For individual aspects, content quality was rated at the highest level (x ̅= 4.92, S.D. = 0.07), and media production techniques were also rated at the highest level (x ̅ = 4.70, S.D. = 0.17). Comparing the mean scores of English pronunciation and communication skills between the two groups, it was found that the experimental group using AR media integrated with the metaverse demonstrated significantly higher English pronunciation skills than the control group (F(1, 89) = 3261.422, p = 0.001, Partial η² = 0.98). Additionally, the experimental group exhibited significantly higher English communication skills than the control group (F(1, 89) = 4239.365, p = 0.001, Partial η² = 0.98). These results aligned with the research hypothesis that "Grade 4 students’ English pronunciation and communication skills post-learning with AR media integrated with the metaverse would significantly improve compared to their pre-learning levels at the .05 level of significance.