Sustainable water quality data are important for understanding historical variability and trends in river regimes, as well as the impact of industrial waste on the health of aquatic ecosystems. Sustainable water management practices heavily depend on reliable and comprehensive data, prompting the need for accurate monitoring and assessment of water quality parameters. This research describes a reconstructed daily water quality dataset that complements rare historical observations for six station points along the Chao Phraya River in Thailand. Internet of Things technology and a Eureka water probe sensor is used to collect and reconstruct the water quality dataset for the period from June 2022–February 2023, with Turbidity, Optical Dissolved Oxygen, Dissolved Oxygen Saturation, Spatial Conductivity, Acidity/Basicity, Total Dissolved Solids, Salinity, Temperature, Chlorophyll, and Depth as the recorded parameters from six different stations. The presented dataset comprises a total of 211,322 data points, which are separated into six CSV files. The dataset is then evaluated using the Long Short-Term Memory (LSTM) algorithm with a Mean Squared Error (MSE) of 0.0012256, and Root Mean Squared Error (RMSE) of 0.0350080. The proposed dataset provides valuable insights for researchers studying river ecosystems, supporting informed decision-making and sustainable water management practices.

Energy consumption especially electricity is considered one of the most serious problems in households these days. It is because the amount of electricity consumed is more than the amount that people actually need. This means that there is an overusing which resulted from the inconvenience of moving to the switch to turn off the light or any appliances and it is often that closing the light is forgettable, for instance; in addition, there are no tools for monitoring how much energy that is consumed in residents. From this, it can be easily seen that people are having a problem in energy usage monitor and control. There are two main objectives of this study including 1) creating the communication framework among server, clients and devices, and 2) developing the prototype system that try to solve the mentioned problems which gives the user an opportunity to know the amount of electricity they have used in their houses and also the ability to turn appliances on and off through the Internet on smart devices such as smart phones and tablets that support Android platform or any web browser. Raspberry Pi is used as a microcontroller and the data is transferred to the smart device by WebSocket protocol which is strongly recommended for real-time communication. The example features on the device's screen are user management, controlling and monitoring of appliances. The result expresses that the system is very effective and not difficult to use from users' satisfaction. However, current sensors may be used for a more accurate electricity measurement and Wi-Fi module for more appliances to calculate its power in the future.

For over two decades, scholars and practitioners have emphasized the importance of digital literacy, yet the existing datasets are insufficient for establishing learning analytics in Thailand. Learning analytics focuses on gathering and analyzing student data to optimize learning tools and activities to improve students’ learning experiences. The main problem is that the ICT skill levels of the youth are rather low in Thailand. To facilitate research in this field, this study has compiled a dataset containing information from the IC3 digital literacy certification delivered at the Rajamangala University of Technology Thanyaburi (RMUTT) in Thailand between 2016 and 2023. This dataset is unique since it includes demographic and academic records about undergraduate students. The dataset was collected and underwent a preparation process, including data cleansing, anonymization, and release. This data enables the examination of student learning outcomes, represented by a dataset containing information about 45,603 records with students’ certification assessment scores. This compiled dataset provides a rich resource for researchers studying digital literacy and learning analytics. It offers researchers the opportunity to gain valuable insights, inform evidence-based educational practices, and contribute to the ongoing efforts to improve digital literacy education in Thailand and beyond.

Obtaining more accurate and complete real-time data when luminaire measurement of street and public lamps is the most concerning thing for Provincial Electricity Authority of Thailand, especially for navigation of inspection and controlling the energy economization. So this paper proposed a resolution which construct database system design using PostGIS with PostgreSQL. Based on Linux platform, adapting the modern technology of Web application framework, PHP, Javascript, CSS, and HTML, an mobile application of monitoring and verification the energy measuring was implemented. Using the policy of database server so users at the different accessible levels can conveniently retrieve proper information for working according to their responsibility.