Detect and Locate Stranger Intrusion
The DeepLens device OS is not stable. The software automatically upgraded and it introduced regression on the device. Synced with AWS DeepLens support team. Eddie and the team helped solve the issue with support overnight. Finally I'm able to test out the project on the device. Appreciate the professional online support from AWS team!
Accomplishments that we're proud of
It's unbelievable we were able to accomplish a deep learning project within a couple of weeks! With limited knowledge of deep learning, we were able to achieve using it to solve the real life problem in such a short time. Moreover, we were inspired by the DeepLens, and we came up with many interesting ideas when we brainstormed in the beginning.
Even my 11 year old daughter showed interest in DeepLens. She came up with ideas such as using DeepLens to detect an elderly person's fall off the bed or in coma state on the floor (we are planning to achieve this idea in the next creation project). I'm so proud she presented DeepLens and the idea to her middle school science class. It attracts a lot of attention and questions from her fellow middle schoolers.
What we learned
DeepLens and AWS AI ecosystem are very powerful to build solutions to help human better life. Amazon is on the right path of leading the industry to achieve the AI evolution. We are inspired and we are glad to have the opportunity of experiencing such an amazing product.
Actually, the use case we solved in this project can be generalized as below: an intelligent system to detect the event, capture the image of the event, send real-time notification with accurate location for immediate response.
The next of our creation, we want to build a system to help seniors living alone. We want to use Sagemaker to train a deep learning model to detect person fall on the floor event and deploy this model to DeepLens -- to automatically detect elder person fall on floor or in coma state, and send real-time notification with accurate location of the fall event to urgent care team or relatives for fast reaction of rescue or assistant.