ISTT_Abacus_Xtreme | Spot That Fire!

The Challenge | Spot That Fire!

Build a crowdsourcing tool for citizens to contribute to early detection, verification, tracking, visualization, and notification of wildfires.

Agni - Rokkhi

"Agni - Rokkhi" , the system where citizens can contribute by providing an alert about fire occurrences around them. After verified through machine learning, peoples at risk will be alerted about the incident to be safe.

ISTT_Abacus_Xtreme

Over the past year, we have witnessed long and arduous battles against record-breaking wildfires across the world. A key to preventing harmful wildfire destruction and spread is early and effective detection. People’s contribution can be a game changer in this perspective, so we came with a crowdsourcing tool for citizens to contribute to early detection, verification, tracking, visualization and notification of wildfires.

Citizens can contribute to this by uploading pictures or videos or plain text about fire occurrences around them, the rest is on us. Our system will verify the fire through machine learning by processing these media files and help others nearby to be safe by-

sending notifications to its users, letting nearby fire fighters to know about the fire with proper location to reach as early as possible. To aware remote peoples about the incident to be safe the app will communicate with the regional authority to make an announcement.

Users can keep track with the fire incident by using the fire map option which shows real-time data. The fire fighters can get exact direction of air flow in that location with the weather update feature.

Over the past year, we have witnessed long and arduous battles against record-breaking wildfires across the world. A key to preventing harmful wildfire destruction and spread is early and effective detection. People’s contribution can be a game changer in this perspective, so we came with a crowdsourcing tool for citizens to contribute to early detection, verification, tracking, visualization and notification of wildfires.

Citizens can contribute to this by uploading pictures or videos or plain text about fire occurrences around them, the rest is on us. Our system will verify the fire through machine learning by processing these media files and help others nearby to be safe by-

sending notifications to its users, letting nearby fire fighters to know about the fire with proper location to reach as early as possible. To aware remote peoples about the incident to be safe the app will communicate with the regional authority to make an announcement.

Users can keep track with the fire incident by using the fire map option which shows real-time data. The fire fighters can get exact direction of air flow in that location with the weather update feature.

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