MUMBAI, India, Oct. 26 -- Intellectual Property India has published a patent application (202631123596 A) filed by Basant Kumar Sahu; Saubhagya Ranjan Nath; Bani Bhusan Praharaj; and Jaykrushna Mohanta on October 15, 2026, for Iot-Based Forest Fire Detection And Automated Suppression System Using Embedded Machine Learning.
Inventors include Basant Kumar Sahu; Saubhagya Ranjan Nath; Bani Bhusan Praharaj; and Jaykrushna Mohanta.
The application for the patent was published on October 23, 2026, under issue no. 43/2026.
Abstract: The present disclosure relates to the design and development of an integrated Internet of Things (IoT) based forest fire detection and automated suppression system. Wildfires present a major risk to natural ecosystems, wildlife, human life and overall climate balance, and early detection is essential for minimizing destruction and enabling rapid response. The system comprises a monitoring node 100 built around an ESP32 microcontroller unit 101, interfaced with a temperature and humidity sensor 102, a gas sensor module 103 for detecting carbon dioxide, ammonia, carbon monoxide and methane, a flame sensor with scanning servo 104, an embedded machine learning classification unit 105 trained using Logistic Regression, Support Vector Machine, Random Forest and XGBoost algorithms, a water nozzle with aiming servo 106, a relay-controlled water pump 107, a buzzer and LED alert unit 108, an OLED display unit 109, and a cloud connectivity module 110 for remote monitoring via ThingSpeak and Blynk platforms. Upon detecting a fire condition, the system automatically directs the nozzle toward the flame, activates the pump for suppression, and raises a local and remote alert. Experimental validation demonstrated classification accuracy exceeding 95%, with the Random Forest model achieving up to approximately 98.99% accuracy, confirming the system as an effective, low-cost, and scalable solution for early wildfire detection and automated response.
Disclaimer: Curated by HT Syndication.
