This research aims to study the guidelines and develop a prototype of an application for public transport users to plan their journey and increase safety in using different types of public transport to travel to King Mongkut's Institute of Technology Ladkrabang. The objectives are as follows: 1) To study the factors of user experience (UX) and user interface (UI) design that affect the users of the application for using public transport. 2) To study the needs of users of public transport applications who must travel to King Mongkut's Institute of Technology Ladkrabang. 3) To present the guidelines for designing the user experience (UX) and user interface (UI) and to produce a prototype of the application for using public transport to travel to King Mongkut's Institute of Technology Ladkrabang. The research includes a review of the literature on User Experience (UX) and User Interface (UI) design, as well as a look at examples of public transportation applications and pick-up sites near King Mongkut's Institute of Technology Ladkrabang. This study is based on qualitative research. There are examples of employing relevant applications during the interview. The target audience is students aged 18 to 35 who will give prototypes for application development to satisfy their requirements. Provide information that is actually useful to users. The research results found that the public transport vehicles that the target group used the most were the Songthaew (the pick-up truck), train, airport rail link, motorcycle taxi, taxi, and bus, respectively. Users were concerned about various safety issues and wanted to design features to increase safety and confidence in using public transport vehicles for students, such as sending locations to relevant officials in the event of an emergency or when assistance was needed, and important information about public transport vehicles that students needed, such as calculating prices, calculating travel times, bus schedules, official and clear pick-up and drop-off points, bus routes, driver registration, suggestions or route recommendations, and the time of public transport vehicles arriving at the point where users were waiting, etc. The guidelines for designing the User Experience (UX) were presented from the analysis of the target group's data, which was a prioritization of the features of the menu for recording frequently used routes, a menu showing nearby pick-up points, a menu for searching for routes and selecting using various user constraints, such as calculating travel prices or travel times, and a menu that could set fonts and color modes to support a variety of users. This was because the study of user needs for fonts found an equal demand for Thai fonts with looped (Looped font) and without looped (Loopless font), as well as a study of the application's color requirements, which required both light and dark colors to be displayed in approximately equal amounts. This includes the design of the user interface (User Interface) by designing symbols that allow users to access the desired information quickly without confusion.
1. ยังไม่มีแอปพลิเคชันสำหรับรถโดยสารสาธารณะเพื่อการเดินทางมาสจล.โดยตรง (www.condonewb.com ,2564) 2. จากการสำรวจบางแอปพลิเคชันนั้นไม่ ได้รับการเพิ่มเติมข้อมูลที่เป็ นปั จจุบันและไม่ ได้รับการพัฒนา อย่างต่อเนื่องนั้นก่อให้เกิดความสับสนในผู ้ใช้งานแอปพลิเคชัน (เว็บไซต์ rottuthai.com อัปเดทปี ล่าสุด 2562) 3. กลุ่มผู้โดยสารมีทัศนคติที่ ไม่ปลอดภัยในการโดยสารรถตู้สาธารณะ (ณิชา สุขวัฒนากรณ์ ,2562)
คณะเทคโนโลยีสารสนเทศ
This report is part of applying the knowledge gained from studying machine learning models and methods for developing a predictive model to identify customers likely to cancel their credit card services with a bank. The project was carried out during an internship at a financial institution, where the creator developed a model to predict customers likely to churn from their credit card services using real customer data through the organization's system. The focus was on building a model that can accurately predict customer churn by selecting features that are appropriate for the prediction model and the unique characteristics of the credit card industry data to ensure the highest possible accuracy and efficiency. This report also covers the integration of the model into the development of a website, which allows related departments to conveniently use the prediction model. Users can upload data for prediction and receive model results instantly. In addition, a dashboard has been created to present insights from the model's predictions, such as identifying high-risk customers likely to cancel services, as well as other important analytical information for strategic decision-making. This will help support more efficient marketing planning and customer retention efforts within the organization.
คณะวิศวกรรมศาสตร์
One of the most important aspects of responding to a medical case is the response time. In general, most fatalities are due to the patient not being able to reach the hands of the doctor in time. This also includes the arrival of medical equipment to the scene. The human brain will start to degrade in function after 3 minutes of oxygen starvation which conventional road transportation method first responders presently use is usually unable to reach the site in this golden 3 minutes, resulting in fatalities during transport or before the arrival of first responders at the scene. Therefore, medical equipment transport by fully autonomous aircraft is explored. This is done through drone deliveries which is much quicker than road methods as the equipment could be flown straight to the site as it is not affected by traffic, road conditions, and navigation. In this project, we will explore an aerial delivery system for medical equipment such as Automatic External Defibrillators (AEDs), First aid equipment, and other small requested medical devices. This will be done through a DJI drone platform and their SDK application. The main goal for this project is to decrease the response time by using an autonomous aerial drone to deliver medical equipment.
คณะวิศวกรรมศาสตร์
This project aims to develop an AI-powered system for detecting and classifying wall cracks using image processing. It identifies different crack types, assesses severity, and ensures accuracy across various image conditions. The goal is to support preventive maintenance by enabling early detection of structural issues, reducing repair costs, and improving safety.