Unmet Need: Sensor Data Recognition and Analysis
In today’s connected world, businesses and individuals are more interested in capturing and understanding the data our smart phones, smart speakers, even smart refrigerators transmit. This data-mining craze has created a proliferation of sensor data and we are finding it difficult to track all of these smart devices in a given environment. There is an increasing likelihood that data is available from smart home technologies within our everyday environments but we are not effectively using that data. Many of these technologies are brittle and do not adapt to users' explicit or implicit wishes.
The Technology: Adaptive Smart Environment Activity Tracking System
This smart home artificial intelligence technology is from the WSU Center for Advanced Studies in Adaptive Systems (CASAS). The invention enables machine learning of activities and behavior profiles of smart home residents activities in an instrumented smart home. The CASAS smart home uses the learned information to analyze resident behavior, predict and identify activities, perform automated assessment of resident functional independence, and assist by automation activities in smart homes. The CASAS smart home discovers patterns in user behavior and generates automation polices that mimic these patterns, while keeping residents in control of the automation. Users can provide feedback on proposed automation activities, can modify the automation policies, and can introduce new requests. In addition, CASAS continuously updates its models to reflect changes in resident behavior.
• Adult Care Facilities/Remote Care givers
• Retail stores
• Smart Home Consumers
• Uses machine learning technologies to monitor daily activities, identify critical situations, and perform automated assessment of functional performance
• Predicts events and uses the learned information to provide health monitoring
• Widely tested in a physical smart environment
U.S. Patent: US 8,417,481