Raweeroj Sangsit

Agricultural Engineer specializing in automation and precision agriculture. Skilled in IoT-based smart farming and AI-driven analytics to optimize productivity. Proficient in automated irrigation, remote sensing, and farm management systems. Passionate about leveraging automation for sustainable and efficient farming.

Development of a Precision Agriculture System for Wolffia Cultivation

11/2023-03/2024

Tasks

• Implemented PLC technology for automated control of environmental factors such as water quality and temperature.
• Integrated Haiwell Cloud for remote monitoring, enabling real-time data analysis and system adjustments.
• Designed the system to improve cultivation efficiency, reduce resource usage, and ensure sustainable farming practices.

Mango Fruit Detection and 3D Localization

07/2024-12/2024

This project received an award.

Tasks

• Utilized the YOLO (You Only Look Once) deep learning model for real-time mango fruit detection from images.
• Applied triangulation techniques to estimate the 3D positions of detected mango fruits.
• Integrated various tools for preprocessing images and refining detection accuracy, ensuring reliable 3D localization for efficient mango harvesting.

IoT Plant Factory

04/2024-06/2024

Internship at Smart AI Solutions Co., Ltd.

Tasks

• Integrated IoT sensors to monitor key environmental factors, including temperature, humidity, light, and soil moisture.
• Used Arduino-ESP32 for processing sensor data and automatically controlling the environment to optimize plant growth.
• Applied machine learning algorithms to predict and adjust for optimal growth conditions in a controlled environment.
• Enabled real-time remote monitoring and control through the Blynk platform.
• Designed the system layout and visualized the plant factory setup in 3D using SketchUp.

Smart IoT Plant Irrigation System for Efficient Water Management

11/2023-03/2024

Tasks

• Utilized soil moisture, temperature, and light sensors to collect data for efficient irrigation.
• Used ESP32/Arduino to process sensor data and control water pumps and valves.
• Automated irrigation processes to conserve water and ensure optimal plant growth.

Insect Detection

10/2022-11/2022

Tasks

• Applied CNN models such as YOLO and EfficientNet for insect detection and classification.
• Collected and preprocessed image/video data for training and testing deep learning models.
• Trained models using TensorFlow to achieve accurate insect recognition.

• Second Runner-up, National Agricultural Engineering Project Competition – Presented a project on a 3D Fruit Detection and Localization System at the 31st National Agricultural Engineering Conference (Feb 6-7, 2025) at Rajamangala University of Technology Thanyaburi.

• Inspire for Tomorrow Contest – Recognized for successfully participating in the Inspire for Tomorrow Contest, organized by Univentures, Grand Unity, Forward System, AheadAll, and Senses Property Management.

• Esports-Engineering Competition, KMITL – Participated in the event as an extracurricular activity.
• AIE 2022 Industrial Camp, Chumphon – Participated in a factory seminar camp to gain hands-on industry experience.
• T7000 Training, KMITL – Completed training by CNH Industrial on advanced agricultural machinery.