AI assistant in the job of home security
Protecting your home is not longer only the job of the police or a good dog. In the new social era we are living, we need smarter solutions, smarter assistants, that can recognize and identify easily our friends, from intruders or unwanted presence. Such solutions should adapt to the home specifics, such as homes with noisy environments, random schedules, large variety of sounds, variety in the types of visual visitors - and use complementary cues from the home context or person’s preferences, for yielding better predictions. With Flare, our product, we are analyzing both audio (dog barking, glass breaking, steps, speech, alarm, etc.), video analysis (humans, dogs, cats, faces, fire, etc.) and user’s preferences history in a parallel manner, to predict and classify events happening at home, and learn patterns from them in time. Using the complementary sources of truth from the system or real-world knowledge in a parallel fashion is a daunting task at first, but on the longer run it gives more reliable and responsible results as a whole, which I believe is the next step in improving our virtual assistants. We are proud to be among the first pioneers to have such a large deployment of machine learning on a small custom-made IoT hardware device.
George is a full-stack engineer, with a great passion for new technologies, hardware and machine learning. During the years, he was working in different positions, such as web/firmware developer, mobile developer, team leader, branch manager and lately entrepreneur. He enjoys getting the best learnings from all the positions he has been through and the people he met. Currently, George is CTO of BuddyGuard, a home security product that disrupts the smart home market through special features powered by artificial intelligence (face recognition, voice analysis, pet detection, etc.). At BuddyGuard, he is managing the technical side, which involves many challenges on data security, audio and video machine learning algorithms, distributed cloud systems scalability, mobile phones integrations and hardware electronics integrations.