Forest Fire Detection and Prediction using IoT and Node MCU


IoT Integrated Forest Fire Detection and Prediction using NodeMCU


This paper presents a fire detection and alert system based on IoT. Here a specific environment is monitored 24×7 and the user is alerted in case of any fatal situation. This can be implemented using a nodemcu and a number of sensors for detecting different physical parameters that can go high during a fire-related accident. Nodemcu is an IOT based controller board with an onboard WIFI module called ESP8266. Here two parameters are being monitored continuously temperature and the presence of smoke. For sensing temperature, the LM35 temperature sensor is used. For sensing the presence of smoke a gas sensor called MQ6 is used, this sensor can detect and measure any carbon-based gas smoke that produces CO2 this makes it possible to detect smoke using MQ6. Also, a PIR sensor is used for detecting the presence of any human. Both gas and temperature sensor is analog so cannot be connected to a digital pin but to an analog pin that is input to an ADC (analog to digital converter). Nodemcu has a one-channel ADC which presents a problem since there are two analog sensors. This can be solved by adding an ADC module called MCP3008. MCP3008 is a sixteen-pin IC with an eight-channel ADC. Also, forest areas can be monitored through a camera using this camera fire can be detected using image processing. For this we can run a python program from a PC and using the OpenCV library fire can be detected. This can be used as a contingency system if the sensors malfunction. If any fire is detected then a water sprinkler will be turned on to prevent fire also an alert is sent to the concerned person for further action.


Fire accidents are common incidents all around the world most of the time this ends up in human life loss. This accident can happen in any environment such as home, industries, cinemas, etc. If an accident occurs in an industrial environment the fatality of the situation is very high. This can be solved by designing a general system to monitor any type of environment remotely or locally. This system is realized in this paper.


  • Fire alarm systems with a buzzer?
  • Fire alert systems with no continuous monitoring system
  • Highly expensive monitoring systems?


Current systems are local hence the alert is not conveyed to authorities far away. Also, the local system could be damaged in the fire


  • Nodemcu based fire monitoring system
  • IoT based alerting system
  • Sensor-based monitoring?
  • Can be monitored continuously from anywhere in the world
  • Connected to the internet all the time


  • both local and global fire alert is provided
  • internet is used for global alerts?
  • concerned personal can monitor from anywhere in the world
  • very low-cost implementation?
  • also, camera-based detection is provided as a failsafe in case sensors malfunction

Humidity and Temperaturedata

Forest Fire Detection and Prediction using IoT and Node MCU


Node Fire


  • Nodemcu is the central part of the whole system
  • Every other component is connected to it as shown in the above diagram
  • LM35 and MQ6 are connected to nodemcu through MCP3008
  • That is not shown in the diagram but can be seen in the circuit diagram
  • PIR sensor is connected to a digital pin?
  • It will go high if any human is present
  • Nodemcu is connected to thingspeak through a WIFI network
  • Also, forest areas can be monitored through a camera using this camera fire can be detected using image processing


  • Nodemcu
  • MQ6
  • LM35
  • PIR sensor
  • Water pump


  • C programming?
  • Python 3 IDLE


  • remote forest fire detection
  • remote forest fire prevention?
  • a man less fire fighting
  • automated fire department????

Forest Fire Detection and Prediction using IoT and Node MCU


[1] A. Aksamovic, M. Hebibovic, and D. Boskovic, “Forest fire early detection system design utilizing the WSN simulator,” in 2017 XXVI International Conference on Information, Communication and Automation Technologies (ICAT), 2017, pp. 1-5.

[2] Y. Liu, Y. Liu, H. Xu, and K. L. Teo, “Forest fire monitoring, detection and decision making systems by a wireless sensor network,” in 2018 Chinese Control And Decision Conference (CCDC), 2018, pp. 5482- 5486.

[3] D. Pant, S. Verma, and P. Dhuliya, “A study on disaster detection and management using WSN in Himalayan region of Uttarakhand,” in 2017 3rd International Conference on Advances in Computing, Communication & Automation (ACCA) (Fall), 2017, pp. 1-6.

[4] C. Aranzazu-Suescun and M. Cardi, “Distributed algorithms for event reporting in mobile-sink WSNs for Internet of Things,” Tsinghua Science and Technology, vol. 22, no. 4, pp. 413-426, 2017.

[5] V. P. Illiano and E. C. Lupu, “Detecting Malicious Data Injections in Event Detection Wireless Sensor Networks,” IEEE Transactions on Network and Service Management, vol. 12, no. 3, pp. 496-510, 2015.

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