MosChip®

Stranger Detection Using AWS ML Services and DeepLens

A case study of AI Engineering
The client is US based home automation solution provider having specialization into Smart Home Hubs, Smart Lighting, wireless sensors, interfaces, and valves. With new-age technology like Artificial Intelligence and Machine Learning penetrating the home automation market, the client wanted to add next-gen home automation solution in their portfolio to stay ahead of the competition. The client approached MosChip to design next-gen home automation systems with Machine Learning based face recognition to reduce the undesired/unwanted notifications of kids’/pet’s motion from home automation systems, thereby making the system smarter to identify actual stranger and send required notification to users. The home automation system allows users to control and monitor their home devices/electronics remotely via smartphones or tablets.
  • Improved quality of notification alerts sent to end-users
  • Delivered easy to deploy and configure face recognition applications for multiple faces

Stranger Detection Using AWS ML Services and DeepLens

A case study of AI Engineering

The client is US based home automation solution provider having specialization into Smart Home Hubs, Smart Lighting, wireless sensors, interfaces, and valves. With new-age technology like Artificial Intelligence and Machine Learning penetrating the home automation market, the client wanted to add next-gen home automation solution in their portfolio to stay ahead of the competition. The client approached MosChip to design next-gen home automation systems with Machine Learning based face recognition to reduce the undesired/unwanted notifications of kids’/pet’s motion from home automation systems, thereby making the system smarter to identify actual stranger and send required notification to users. The home automation system allows users to control and monitor their home devices/electronics remotely via smartphones or tablets.
  • Improved quality of notification alerts sent to end-users
  • Delivered easy to deploy and configure face recognition applications for multiple faces
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