AI Lab projects
Learn about breakthrough AI innovation with hands-on labs, code resources, and deep dives.
Clean Water AI
Clean Water AI uses a deep learning neural network to detect dangerous bacteria and harmful particles in water. Drinking water can be seen at a microscopic level with real-time detection.Go to CleanWater AI
Water safety can be difficult to maintain across the vast distribution of a municipal water system. Contamination by bacteria or dangerous particles is often difficult to detect before health issues occur.
AI detects water contamination issues, using trained models to recognize harmful particles and bacteria. Distributing devices that monitor water for problems will help cities detect contamination as quickly as possible.
Clean Water AI trains a neural network model, then deploys it to edge devices that classify and detect harmful bacteria and particles. Cities can install IoT devices across water sources to monitor quality in real time.
Monitoring water safety in real time
Clean Water AI uses AI and high definition cameras to detect bacteria and particles in a water source.
Technical details for Clean Water AI
Clean Water AI trains the convolutional neural network model on the cloud, then deploys it to edge devices. We used Caffe, a deep learning framework, which allows a higher frame rate when running with Intel Movidius Neural Computing Stick.
An IoT device can then classify and detect dangerous bacteria and harmful particles. The system can run continuously in real time. The cities can install IoT devices across different water sources to monitor water quality as well as contamination in real time.
Currently, Clean Water AI has been built as a proof of concept using a microscope and Up2 board. The entire prototype costs less than $500, and they’re plans to scale up production to help reduce unit costs.
Gen Studio is a prototype created with collaborators from The Metropolitan Museum of Art, Microsoft, and MIT. Gen Studio uses AI to visually navigate The Met’s art collection.
Angel Eyes is an IOT device that monitors a baby’s sleeping position and environment. Caregivers can view a live stream from anywhere and receive notifications if the device detects any issues.
PoseTracker uses deep learning to track the position and orientation of objects. This solution will use your phone camera to measure and track the angle, orientation, and distance of an item in real time.
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