This project presents the development of a "Smart Cat House" using Internet of Things (IoT) and image processing technology to facilitate and enhance the safety of cat care for owners. The infrastructure of the smart cat house consists of an ESP8266 board connected to an ESP32 CAM camera for cat monitoring, and an Arduino board that controls various sensors such as a motion sensor in the litter box, a DHT22 temperature and humidity sensor, an ultrasonic water and food level sensor, including a water supply system for cats, an automatic feeding system, and a ventilation system controlled by a DC FAN that adjusts its operation according to the measured temperature to maintain a suitable environment. There is also an IR sensor to detect the cat's entry into the litter box and an automatic sand changing system with a SERVO MOTOR. All systems are connected and controlled through the Blynk application, which can be used on mobile phones, allowing owners to monitor and care for their pets remotely. Cat detection and identification uses image processing technology from the ESP32 CAM camera in conjunction with YOLO (You Only Look Once), a high-performance object detection algorithm, to detect and distinguish between cats and people. Data from various sensors are sent to the Arduino board to control the operation of various devices in the smart cat house, such as turning lights on and off, automatically changing sand, adjusting temperature and humidity, feeding food and water at scheduled times, or ventilation. The use of a connection system via ESP8266 and the Blynk application makes it easy and convenient to control various devices. Owners can monitor and control the operation of the entire system from anywhere with internet access.
ในปัจจุบัน ผู้คนจำนวนมากเลือกเลี้ยงแมวเป็นเพื่อนคลายเหงา แต่ด้วยภาระหน้าที่การงาน การเรียน หรือธุระส่วนตัว ทำให้หลายครั้งเจ้าของไม่สามารถดูแลแมวได้อย่างใกล้ชิดตลอดเวลา ก่อให้เกิดความกังวลใจและเป็นห่วงสัตว์เลี้ยงที่บ้าน ปัญหาเหล่านี้เป็นแรงบันดาลใจให้เกิดแนวคิดในการพัฒนาบ้านแมวอัจฉริยะ (Smart Cat House) เพื่ออำนวยความสะดวกและตอบโจทย์ความต้องการของผู้เลี้ยงแมวในยุคปัจจุบัน บ้านแมวอัจฉริยะเป็นระบบที่ถูกออกแบบมาเพื่อช่วยให้เจ้าของสามารถติดตามและดูแลแมวได้จากระยะไกลผ่านแอปพลิเคชันบนมือถือ โดยภายในบ้านแมวอัจฉริยะจะมีระบบต่างๆ ที่ช่วยอำนวยความสะดวกสบายให้กับทั้งเจ้าของและแมว อาทิ ระบบควบคุมการให้อาหารและน้ำ ระบบจัดการกระบะทราย ระบบควบคุมอุณหภูมิ และระบบกล้องวงจรปิด เป็นต้น ทำให้บ้านแมวอัจฉริยะเป็นทางออกที่ตอบโจทย์สำหรับผู้เลี้ยงแมวที่ไม่ค่อยมีเวลา แต่ยังคงต้องการดูแลสัตว์เลี้ยงของตนให้มีความสุขและมีสุขภาพแข็งแรง
คณะวิศวกรรมศาสตร์
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.
คณะเทคโนโลยีสารสนเทศ
This research presents a deep learning method for generating automatic captions from the segmentation of car part damage. It analyzes car images using a Unified Framework to accurately and quickly identify and describe the damage. The development is based on the research "GRiT: A Generative Region-to-text Transformer for Object Understanding," which has been adapted for car image analysis. The improvement aims to make the model generate precise descriptions for different areas of the car, from damaged parts to identifying various components. The researchers focuses on developing deep learning techniques for automatic caption generation and damage segmentation in car damage analysis. The aim is to enable precise identification and description of damages on vehicles, there by increasing speed and reducing the work load of experts in damage assessment. Traditionally, damage assessment relies solely on expert evaluations, which are costly and time-consuming. To address this issue, we propose utilizing data generation for training, automatic caption creation, and damage segmentation using an integrated framework. The researchers created a new dataset from CarDD, which is specifically designed for cardamage detection. This dataset includes labeled damages on vehicles, and the researchers have used it to feed into models for segmenting car parts and accurately labeling each part and damage category. Preliminary results from the model demonstrate its capability in automatic caption generation and damage segmentation for car damage analysis to be satisfactory. With these results, the model serves as an essential foundation for future development. This advancement aims not only to enhance performance in damage segmentation and caption generation but also to improve the model’s adaptability to a diversity of damages occurring on various surfaces and parts of vehicles. This will allow the system to be applied more broadly to different vehicle types and conditions of damage inthe future
คณะบริหารธุรกิจ
This research aimed to develop the mixed tea from longan peels and seeds. Population studied were longan farmers who planted longan and preserved the longan product in Ampur Wang Nam Yen, Sa Kaeo Province. From the results, it was found that from By-product in the production of dehydrated longan, longan peels and seeds, which can be processed into ready-to-drink powdered tea. This not only helps reduce waste from the production process but also contributes to generating additional income from these by-products.