SeeChange Technologies has been announced as the winner of the Most Innovative ML Solution in the AI & Machine Learning Awards. Their ground-breaking Machine Learning solution to practical, real-world issues in Health and Safety is delivered from their core mission—to help humanity thrive through the power of visual AI Technology.
The award recognises SeeChange Technologies Liquid Spill Hazard Detection in Real Time, designed to automatically recognise hazardous physical world scenarios and identify the relevant actions to take.
SeeChange’s state-of-the-art Machine Learning model has been trained on over 1 million spill images. It’s ability to detect different floor surface types and any kind of liquid spill, including water on a shiny floor, makes this solution the most advanced and effective method of ensuring your environment is as safe as it can be. Fifty percent of claims made against retailers are from trips and falls, with 70% of these being avoidable – SeeChange Spill detects and notifies in real-time allowing a fast response to potential liabilities, and helps maintain HSE and OSHA compliance.
The AI & Machine Learning Awards, organised by Computing.co.uk (The Channel Company), recognises the organisations, products and people who bring AI to life and apply it to solve real problems. Other winners in the 2022 awards include Deloitte and Lloyds Banking Group.
SeeChange Technologies: A Message From The CEO
“SeeChange are delighted to receive such high praise for the work we are doing to apply AI to meaningful real-world problems. Using AI to solve fundamental health and safety problems such as slips, trips and falls, perfectly demonstrates SeeChange’s ethos and approach to the use of such advanced technology. Huge congratulations to the entire team, and thank you to the AI Excellence Awards for recognising our contribution to health and safety technology and to the AI sector”
Jason Souloglou, Founder & CEO of SeeChange Technologies
The judges shared this statement regarding SeeChange’s award “An innovative solution to a high impact practical problem. It’s impressive to see the modelling framework with respect to the semantic segmentation model to identify multiple objects in an image, and collaboration with third parties to get more training data. Good work.”.
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