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Artifical intelligence for agriculture and enviroment

Abstract

Artificial intelligence for agriculture and environment is a collection of significant models for enviromental friendly Thailand development. The models create with machine learning and deep learning by Near infrared spectroscopy research center for agricultural and food products, including: Determining the nutrient needs (N P K) of durian trees by measuring durian leaves using a non-destructive technique using artificial intelligence, Identification of combustion properties of biomass from fast-growing trees and agricultural residues using non-destructive techniques combined with artificial intelligence, and Evaluation of global warming due to biomass combustion using non-destructive techniques using artificial intelligence. The basic technology used is Near infrared Fourier transform spectroscopy technology which measurement and output display can be done quickly without chemical, no requirement for special expert, and measurement price per sample is very low. But the instrument cannot be produced in Thailand.

Objective

ความเจริญก้าวหน้าทางวิชาการจะเป็นจริงเมื่อผลงานทางวิชาการถูกนำไปใช้ได้จริงในระบบการผลิตซึ่งมีนัยสำคัญทางเศรษฐกิจของประเทศ จึงได้นำผลงานของนักศึกษาและคณาจารย์ของศูนย์วิจัยเนียร์อินฟราเรดสเปกโทรสโกปีสำหรับผลิตผลเกษตรและอาหาร มานำเสนอในงานจัดแสดงนวัตกรรม KMITL Innovation Expo 2025 ในวันพฤหัสบดี 6 ถึง วันเสาร์ 8 มีนาคม 2568 ณ หอประชุมเจ้าพระยาสุรวงษ์ไวยวัฒน์ (วร บุนนาค) สจล. ซึ่งเป็นโอกาสดีของศูนย์วิจัยเนียร์อินฟราเรดสเปกโทรสโกปีสำหรับผลิตผลเกษตรและอาหารในการเปิดเผยผลงานทางวิชาการสำคัญซึ่งมีแนวโน้มสามารถนำไปใช้ได้จริงต่อสังคมเกษตรกรรมและสิ่งแวดล้อมเพื่อการพัฒนาประเทศ

Other Innovations

Spray System of Plant Essential Oil Emulsion for Reducing PM2.5

คณะเทคโนโลยีการเกษตร

Spray System of Plant Essential Oil Emulsion for Reducing PM2.5

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A Study of Sound Absorption Material Using Rubber Powder from Old Tires

คณะวิศวกรรมศาสตร์

A Study of Sound Absorption Material Using Rubber Powder from Old Tires

In Thailand, the quantity of old tires has been increasing annually, posing a significant environmental challenge due to their non-biodegradable material. However, old tires contain an internal porous structure, which suggests their potential application as sound-absorbing materials. Porosity is a key characteristic that enables materials to trap sound waves, making them effective for noise reduction. Therefore, this study aims to investigate and develop sound-absorbing materials from old tire rubber powder. The methodology involved mixing old tire powder with fresh latex at a ratio of 1:2, followed by drying at a temperature of 120°C for four hours. Subsequently, the physical properties influencing sound absorption, including density, porosity, and water absorption, were analyzed. The results indicated that the sound-absorbing material produced from old tire rubber powder showed a density of 0.96 g/cm³, a porosity value of 0.45, and a water absorption of 11.03%. Therefore, the findings suggest that old tire rubber powder has the potential to be effectively utilized as a sound-absorbing material.

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Automatic License Plate Recognition Service

คณะวิศวกรรมศาสตร์

Automatic License Plate Recognition Service

This project focuses on the development of an automatic license plate recognition system that supports both standard and special license plates in Thailand. By utilizing Machine Learning technology, the system enhances the efficiency of license plate reading. It can process data from both images and videos. Users can register and subscribe to the service, allowing them to send data for processing through RESTful API, WebSocket, and registered IP cameras.

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