This project aims to create the model of fire protection system for the kitchen. The model installed of protection and notification systems was created by using the Google SketchUp program with a ratio of 1:10 from the real kitchen scale. According to the literature it was found that more than 50 % of the fire within the shelter occurred in a kitchen. The main causes are flame heat sparks and electrical equipment. The system was developed to detect flame gas and smoke by using infrared sensor (IR FLAME) and gas detection device (MQ-2). Arduino MEGA2560 is a central processor to control the device of the protection system. Node MCU is a data receiver with Arduino to display the average amount of gas flame through the Blynk application in real time and send notification via the Line application when the amount of either flame gas or smoke is greater than or equal to the specified quantity. Fire protection system is divided into 3 conditions: fire gas and smoke. In case of fire the sprinkler will be activated with class K extinguishers to extinguish fire. In gas leakage conditions ventilator will be activated to ventilate the gas leaks and the gas supply is cut off. For smoke condition the ventilator will be activated to ventilate the smoke out of the kitchen. The results of the experiment by using the method of dividing into 13 simulations in total. The system can detect the flame with 12 points 92% from 13 points. In case of gas a can of gas was used in all tests. Nine points of gas can detect with 69% of the total 13 points. The smoke detector can capture smoke with a large amount of smoke. There are a total of 13 tests that can capture 11 smoke points representing 84% of all 13 points.

This research was the application of Unmanned Arial Vehicle (drones) in conjunction with remote sensing technology to monitor the occurrence of the waste dump site fire. The research began with designing and developing prototype tools to collect data from the field site. After the tools were tested they were used to measure gases from the dumping sites. After that the field observation was performed in Nonthaburi Province Pathum Thani Province and Pha Nakhon Si Ayuthaya Province. The final step of the research was to collect the data of active fire hot spot and image from MODIS system satellite covered the area of Nonthaburi Province Pathum Thani Province Pha Nakhon Si Ayuthaya Province and Samut Prakan Province in the period of 1 November 2017 to 31 October 2018. The result showed that the developed drone and the prototype gas detection units worked as designed. The result of gases measurement by the tools were similar to the references equipment. The field observation showed that the dumping site mainly composted of plastic organic matter and cotton which up to 74.9 percent in total. This indicated the factor that influenced the dump site gas generation. Based on the combination technique in the research it could be concluded that Drone and Remote sensing technology were the compromised technology for monitoring fire from the municipal solid waste dump site area.