Smooth and faster reporting of forest fires

Developers: Smruti Ranjan Behera, Suvankit Prusti, Siddhartha Satyakam, Tusharkant Sahu

Web scraping refers to the extraction of data from a website. This information is collected and then exported into a format that is more useful for the user. Be it a spreadsheet or an API.In general, web data extraction is used by people and businesses who want to make use of the vast amount of publicly available web data to make smarter decisions.

A sensor is a device that detects and responds to some type of input from the physical environment. The specific input could be light, heat, motion, moisture, pressure, or any one of a great number of other environmental phenomena. The output is generally a signal that is converted to human-readable display at the sensor location or transmitted electronically over a network.

The system proposed takes various meteorological parameters like wind speed, pressure , temp, humidity etc. into account from an open source yet scientifically trusted meteorological web site by the method of web scraping. Based on the data received from the web site , the machine learning model deployed in the web app predicts a pattern.

By comparing them with certain parameters , a probabilistic result can be obtained. But to have a deterministic result , after getting a higher probability of forest fire, the sensors can remotely switched on to get the real time data. This will enable us to get a very accurate result while conserving the energy of the batteries for further use.