This research aims to 1) develop the project-based learning using discussion and lesson-learned methods via social media model (PBL-DLL SoMe Model) used for enhancing problem solving skills of undergraduate in education student, and 2) evaluate the PBL-DLL SoMe Model used for enhancing problem solving skills of undergraduate in education student. The samples groups are 9 specialists in education, enhancement of problem solving skills, educational technology, and computer and communication technology selected by purposive sampling. Thereafter, researcher analyses the data statistically by examining the mean ( x ) and the standard deviation (S.D.).The research result shows that (1) the PBL-DLL SoMe Model used for enhancing problem solving skills of undergraduate in education student, consists of 4 components which are 1) the analysis of the readiness of the input factors, 2) the process of the PBL-DLL SoMe Model, 3) the evaluation of the achievement of learning and problem solving skills (Output), and 4) the evaluation of the result between evaluating and feedback.

Abstract: This research purposed to design an automatic home-based fish farming using the internet of things and to evaluate its efficiency. There were 3 processes in this research: 1. creating a home-based fish farming environment (fish pond) 2. designing and developing home-based fish farming by using the internet of things and 3. experimenting and implementing the system.The fish pond (90 x 180 x 50 cm) was made up of 90 blocks. It was coated with waterproofed plastic in order to contain a maximum of 80 cm x 170 cm x 40 cm. or 0.544 m3 of water. The automatic home-based fish farming system using the internet of things consisted of 6 parts in the form of 1. A NodeMCU Microcontroller 2. An automatic fish feeder 3. A relay module 4. Home Wi-Fi 5. Web Application 6. Line Notify. The NodeMCU Microcontroller was the main module use to control the automatic working of the system.The experiment resulted in a number of findings. Firstly, Fish feeder experiment, Experiment for the fish feeder to release food for 30 grams, 5 times, average time 23 seconds, error rate + 8.70%, -7.25%; Experiment for the fish feeder to release food for 45 grams, 5 times, average time 35 seconds, error rate + 10.00%, -8.57%; Experiment for the fish feeder to release food for 60 grams, 5 times, average time 48 seconds, error rate + 2.08%, -5.27%; finally, 75g fish feeder, 5 times, average time 75 seconds, error rate +8.33%, -8.02%. As a result, the dispensing variation was no more than ±10%. Secondly, the timing of this machine was divided into 4 periods: during days 1 to 30, it dispensed food 30g. During days 31 to 60, it dispensed food 45g. During days 61 to 90, it dispensed food 60g. During days 91 to 142, it dispensed food 75g. It would feed 2 times: 7 am. and 6 pm. each day. Thirdly, the test was to turn on and off the water and oxygen pumps by just clicking a button on the web application. The system was used to feed 80 3-inch long catfish over a period of 142 days. At the end of the period, 43 catfish were left with 37 having died. The survival rate was 54%. These fish weighed 5,380 grams in total and their growth varied. There were 24 small fish which weighed 120-220 gram (61%), 10 medium sized fish which weighed 230-330 (23%) and 7 large fish which weighed 340-440 (16%).As a result, this system could be used for feeding fish, but it needs some improvements such as the introduction of a waste water monitoring system and an automatic water changing system which would enhance the automatic working of the system.

Cultivation <span lang="EN-US">of ornamental plants in the office is popular among office workers and the general public because it can create a good environment in the area, but the plant growers must pay attention to watering the plants, because it may cause the plant to die</span><em><span lang="TH">. </span></em><span lang="EN-US">With the advancement of internet of things </span><span lang="TH">(</span><span lang="EN-US">IoT</span><span lang="TH">)</span><span lang="EN-US"> technology, used to control devices wirelessly, this research developed the smart flowerpot system that works through mobile and web applications, using a microcontroller to control the system and connect to users via mobile and web application that can monitor the system, and control the operation both directly and automatically</span><em><span lang="TH">. </span></em><span lang="EN-US">When soil moisture is reduced to a predetermined value, the system will order the plants to be watered automatically, and when the water level is almost completely reduced, the ultrasonic sensor will send a notification to the mobile application to let the user know, after testing the system, it was found that the smart plant pot can work efficiently and can automatically water the plants</span><em><span lang="TH">.</span></em>