Project List
01219335 Data Acquisition and Integration
Second Semester, 2023. Section 450
Project Overview
Our project aims to understand the trends regarding whether to go outside or not based on the level of PM2.5 pollution. Users interested in exploring decisions and data can do so through APIs and visualizations.
Members
- Chayakarn Hengsuwan (ID: 6510545322)
- Suparak Aryasit (ID: 6510545756)
Key Features
- Users can access a list of APIs providing information about pollution levels and decisions based on their location.
- Users can visualize:
- Mean AQI based on decisions to go outside.
- Relationship between PM2.5 level concerns and decision-making.
- Word clouds representing other factors influencing decisions.
- Percentage of reconsideration to go outside based on PM2.5 levels.
- Trends of AQI over time by district.
- Trends of AQI and decision-making.
Overview
The Soil Moisture Predictor project aims to visualize data collected from primary and secondary sources, including soil moisture, PM2.5, air humidity, temperature, and wind speed. The application also provides a soil moisture prediction feature using other environmental variables as predictors.
Members
6410546122 Jiratchaya Thongsuthum 6510545713 Worawalan Chatlatanagulchai
Overview
Allergic Rhinitis and Environmental Factors investigates how environmental factors influence allergy symptoms. We focus collecting on environmental factors such as data on dust levels, temperature, and humidity, as these elements could affect allergic rhinitis. We will also survey individuals with allergic rhinitis to determine whether they experience symptoms in the morning.
Members
- 6510545764 Setthapon Thadisakun
- 6510545420 Tantikon Phasanphaengsi
Github repository
Features
- API endpoint for statistic values such as mean, max, and min of enrironmental factors when allergic rhinitis happened in the morning.
- API endpoint for statistic values such as mean, max, and min of enrironmental factors and does allergic rhinitis happned from our samples.
- Visualization site for looking at pattern, trends, and statistic values during data collecting period
ComfyWear: A project that detects clothing styles in images and predicts the comfort level (1-5) of people based on their clothes, local temperature, and local humidity. It also provides data-driven advice to help people dress comfortably. Plus, it can also integrate the data from user feedback to enhance future predictions as well.
Overview
Flare Watchers is a smart system that uses different sensors and cameras to watch for fires. It has a special model that can look at the data from the sensors and images from the cameras to figure out if there is a fire happening. If Flare Watchers think there is a fire, they will take pictures with the camera and send an alert.
Project's GitHub
Due to the project file size being too big you can view and download our project on GitHub link
Trafica - 2024 Year Project
Abstract
This project is a part of the year project of Data Acquisition and Integration, Data Analytics, and Software Testing course Kasetsart University.
Our project aims to collect data to study the possible effects of traffic around Kasetsart University (Computer Department) that potentially cause air/noise pollution.
Our goal is to study the correlations between the acquired data using the knowledge on data acquisition and analytics.
Members
Nanthawat Duang-ead 6510545551
Phumrapee Chaowanapricha 6510545683
You can visit our GitHub Repo: https://github.com/D7NAMITE/trafica_year_project_2024
WeatherSense
See more information: Github Repository
Team members
- Wissarut Kanasub 6510545721 Software and Knowledge Engineering student
- Sukprachoke Leelapisuth 6510545748 Software and Knowledge Engineering student
Overview
WeatherSense is a weather tracking website that updates weather data and classification every 10 minutes. Leveraging our trained random forest classification model, WeatherSense provides accurate classification and historical weather information.
The system corrects data using the Ky-015 sensor and integrates with the OpenWeatherMap API to ensure reliability. Node-RED assists in data correction.
Features
- Display latest weather data every 10 minutes
- Display type of waether that classcification by Our model
- Display old weather data
- Weather data visualization
WateringMe
Overview
WateringMe is home plant monitoring application designed to promote the way gardener water by analyzing past and current data of soil moisture and weather condition. Through data visualization, it presents historical and real-time data trends. Using multiple linear regression, it forecasts soil moisture for the next hour from many factors such as humidity, temperature and precipitation , while also computing Potential Evapotranspiration (PET) to estimate water loss from soil, mm/day.
Member
- Natthapol Sermsaran 6510545527 Software and Knowledge Engineering, Kasetsart University
- Natthadit Lertpisanwut 6510545403 Software and Knowledge Engineering, Kasetsart University
Our project's Github repository
See more information:Github Repository
DustNWeatherAPI collects data on air quality using a dust sensor PMS7003 and weather information from the WeatherAPI. Then, it visualizes and integrates this data.
For visualization, the application displays PM1, PM2.5, and PM10 data collected between April 20, 2024, and May 10, 2024, along with the average temperature, wind speed, humidity, and cloud cover during that period.
For the API, the application offers endpoints to retrieve information on dust and weather, with filtering options provided using Django Rest Framework.
Explores the connection between sleep and environmental variables, focusing on how factors like noise, temperature, humidity, and weather conditions influence sleep quality. By analyzing data on sleep patterns alongside environmental data, the project aims to visualize how our surroundings impact the quality and duration of sleep.
Keep Yourself Healthy Project
GitHub: https://github.com/nicharr-nn/KeepYourselfHealthy_project
Description
Sitting for too long at the computer can lead to stress and physical strain, so we should go exercise. But before heading out, there are several factors to consider, such as the AQI (Air Quality Index) in your area and the temperature, to avoid heat stroke and danger from dust. Our project will help you decide whether to exercise indoors or outdoors based on the AQI and temperature in your area.
Features
- Visualize the average AQI and temperature in this week for each day
API
- Get the AQI and temperature in the area (minimum, maximum, average, average for each day)
- Get the Heat Stroke Level (Low, Moderate, High)
- Get the AQI Level (Good, Moderate, Unhealthy for Sensitive Groups, Unhealthy, Very Unhealthy, Hazardous)
Libraries and Tools
- FastAPI
- Python
Primary Data
- Temperature Sensor from KidBright
Secondary Data
- AQI from AQICN
Reference
Will the cloth dry, bro?
Team Members
- Chirapat Chanmit 6510545306, Software And Knowledge Engineering
- Thanutham Chonsongkram 6510545365, Software And Knowledge Engineering
Project Overview
We'll use the clothes covering our sensor, which is connected to the kidbright board, to collect data into our database, then spray the water and check the fabric and surrounding humidity every 3 hours to determine the ideal drying time.
Github Repository
Our project addresses the critical issue of air pollution in Bangkok by focusing on indoor air quality. Given the escalating concerns about pollution's impact on health, we aim to assess and improve the air inside homes and buildings. Through our research, we seek to empower individuals to take proactive steps towards creating healthier indoor environments, contributing to overall well-being and sustainability. More about our project: Ezdust
Waste Watcher
Team Members
Software and Knowledge Engineering, Kasetsart University
- Jullaphong Jiamwatthanaloet 6510545314
- Phimnada Chirachotsuphaphat 6510545641
Project Overview
- WasteWatcher is an API platform and data visualization web application.
- WasteWatcher serves as a platform for waste management analysis to help address the global warming issue.
Features
- Real-time Waste Monitoring: Retrieve bins and waste records along with weather conditions via API in real-time.
- Data Visualization: Visualize waste records along with weather conditions using interactive charts.
- API Exploration with Swagger UI: Explore the API endpoints easily and intuitively using Swagger UI.
Waste Watcher Repository
Weather-Steam-API
This project is about creating API from Temperature, Humidity, and Pm2.5 and Stream_games. We collect data from the primary source and secondary sources. To see the pattern and trend of the data.
Team members
Software and Knowledge Engineering, Kasetsart University
- Pichayoot Tanasinanan 6510545632
- Achirawich Phongpanich 6510545781
Project Overview
We use the temperature and humidity sensor, which is connected to the kidbright board, every hour as a primary source data, and then we collect game name and player count from SteamDB manually as a secondary source data.
Related Document
API-Pathfinder
Contributors
- Chanun Suntrapiwat 6510545357
- Jirapat Chutimantapong 6510545292
Project Overview
We try to investigate the relation between traffic and weather by collecting the data on traffic like linearX, linearY, LinearZ, Latitude, Longitude ,and Timestamp in realtime and change into acceleration and time spent for each time we travel to University.
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We used 2 devices(from each member) to collect the traffic data.
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We collected data from traffic on Ngamwongwan Road to the Kasetsart Intersection which only includes the section that’s around the campus area due to difficulties on data collecting.
Features
- Visualization Web Application.
- Display statistical number of the data acquired.
The API would provide: Statistical Endpoints of the acquired data included
Github: Pathfinder-API
📄 Project Overview:
Measure the rate of ice melting. For example, if the temperature and humidity are at certain levels, how long will it take for the ice to melt?
To conduct experiments, we will place the ice on various surfaces such as metal, soil, plastic, and wood.
🛠️ Features:
Overview: The main page of the project see weather forecast, visualized data and the statistical data of the ice melting.Tables: The table view of the ice melting data use by ApexChart.- Ice Experiment: The ice melting data.
- Material: The material data.
- Weather Condition: The weather condition data.
API Query: The documentation of the API used by the Django REST API framework.
👾 Github Repository: IcyMelt
Thanabordee BUNDITSAKUL
Sirin PHUNGKUN
A system to watch over people living alone. It uses an ESP32 with sensors to track indoor environments such as temperature and light + IP Camera with an action model to keep track of action status. Combines this information with other online sources, like weather data, to give advice and notify us when bad events happen.
Github: https://github.com/Sosokker/HomieCare
Functionality
- Predict Indoor Environment
- Recommend action to do according to data
- Real-time IP camera stream with snapshot
- Detect Fall down and notify with Line
Water absorption in different soil type
About the project
The project aims to investigate the relationship between soil moisture levels and water absorption capacities across different soil compositions. By collecting data on parameters like moisture, temperature, and water drainage rates.
Members
- 6510545578 Buravit Yenjit (software and knowledge engineering)
- 6510545799 Atikarn Kruaykriangkrai (software and knowledge engineering)
Project overview and features
- Custom tools were built to measure soil moisture content and water drainage rates simultaneously.
- Sensors enabled continuous data collection every 5 seconds during experiments.
The purpose of this project is to measure light intensity and temperature in various learning environments, both indoors and outdoors, by using Kidbright's sensor. Also, data from the API is used to collect humidity and PM2.5 levels. We collect the data from 10.30 a.m. to 4.00 p.m. to determine the best timing and learning spaces for studying. We collect the light and temperature at: * Co-working space on the third floor of the computer engineering building. * Engineering library. * KU main library. * Economics Library.
Cat Impact
We collect cat appearance in local ecosystem via security camera to predict cat population in area to calculate extinction rate of local wild life; but for now we can only estimate the amount of cat's prey in local area.
We are only enrolled in DAQ, thus we make this project to fit just DAQ subject's requirements.
Team members:
- Nantawan Paramapooti 6510545535 Department of Software and Knowledge Faculty of Engineering Kasetsart University
- Tanakorn Kullapatchawarit 6310546325 Department of Software and Knowledge Faculty of Engineering Kasetsart University
Project overview and features
- First, we observe and count cat appearances on our camera to predict the cat population in local area
- Then, we calculate amount of cat’s prey based on our secondary dataset
- And provide API and data visualization of cat's prey
preview:
WeatherFootfall
Overview:
Weather Footfall analyzes weather's impact on campus activity by correlating data from a using PIR Sensor and Temperature and Humidity Sensor It offers concise insights through statistical analyses and visualizations, aiding in resource optimization and event planning.
Members
- 6510545276 Kantapon Hemmadhun
- 6510545497 Tanapoom Srikaewkheaw
Github repository
https://github.com/TSpoomM/Weather_FootFall.git
Related to the course:
Data Acquisition and Integration
Overview
This project involves creating an API that provides information about Thai movies and their details. We collect data through a questionnaire asking people of various ages and genders about their favorite Thai movies. After obtaining the movie titles, we use web scraping to find out when they were released and where they can be watched. These applications include Prime Video, Apple TV, Netflix, VIU, YouTube, and 3CHPlus, which are popular among Thai audiences for watching Thai movies.
Team Member
6510545250 Kongkawee Chayarat
6510545624 Pichayanon Toojinda
Project documents
