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Fire Detection - background

Wildfires cause catastrophic damage worldwide, accounting for 20% of global carbon emissions. The problem, exacerbated by climate change, is deteriorating. Unusually severe fires in USA, Australia, Spain etc, have claimed hundreds of lives, causing damage worth Billions. Wildfires are breaking out in countries unaccustomed to the problem. Northern European countries experienced a 200x increase in area burned in 2018. 

Airplane Drops Fire Retardant on Wildfir
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Power grids

In collaboration with Pyreos, Imperial College London and King's College London, Tethir is developing a new solution for early detection of the most predictable fires: those occurring due to power line failure.  These fires are more damaging than most because they often occur in high winds. In California over 6 years, 1,500 wildfires started in the power line corridors of one utility company, some of the most devastating on record. In Spain, 3,185 fires were started by power lines between 1985-2010. Power line operators worldwide now face severe financial liabilities (In the billions of dollars), creating a large market for reliable and effective detection systems.


Very few power grids have any wildfire detection and those that do have sparse coverage. Current solutions have not been adopted at scale because they are too expensive and often only detect fires once they have grown to an unstoppable size. Companies need technologies that can detect fires in the first minutes after ignition, while they still occupy <1 acre and when firefighters have a chance of extinguishing the fire before it causes extensive damage. This is challenging. Many wildfires occur in remote areas far from electricity and telecommunications infrastructure.  Low power consumption, reliability and power/comms-autonomy are key.

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Early Detection

Tethir's innovative system increases the detection range of typical flame detectors from <85m to 1-2km. 

Multiple wavelength detection and advanced algorithms are being deployed to achieve market-leading false alarm rates.