IOT BASED FOREST SAFTEY ALERT SYSTEM ON DISASTERS WITH INTRUDER DETECTION
Author(s):
Guruprasanna J K , Dr.Bhagya H.K.
Keywords:
LCD,GPS, IoT,WIFI, Cloud, transfer learning, YOLO algorithm
Abstract
The most frequent danger in forests, forest fires seriously devastate the forest's richness, biodiversity, and natural environment. To safeguard forests from fires, early identification and preventive actions are required. There are two conventional ways of human surveillance that are most frequently utilised to accomplish early identification of these issues. Direct human monitoring is one method, while remote video surveillance is another. When doing distant observation, one can implement detection automation to achieve surveillance. This project's primary goal is to develop a real-time monitoring and warning system for fire detection, animal movement detection, and human infiltration detection in forest regions and along borders. The Raspberry Pi Pico microcontroller board, the ESP8266 WiFi module, and other components are used in this system. A 16x2 LCD display with an LCD I2C module, an infrared flame sensor, a MQ2 smoke sensor, a microphone sound sensor, a DHT11 temperature and humidity sensor, a NEO-6M GPS module, and a 5V mini buzzer.
Article Details
Unique Paper ID: 160350
Publication Volume & Issue: Volume 10, Issue 1
Page(s): 213 - 220
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