Caspar.AI’s proprietary sensing technology enables retirement communities to provide enhanced comfort and safety for their residents. Our technology powers features like wellness, resident inactivity and fall detection.
Caspar.AI runs at the edge — does not send sensitive data to the cloud, ensuring privacy.
Edge Computing ensures reliability. The AI modules are compiled on your devices for low-latency.
Caspar.AI’s API easily integrates with your buildings IoT platform to enhance their functionality.
Caspar.AI learns residents’ preferences and activities using CasparAdapt and CasparSense technology.
Our compiler produces local and computationally-efficient AI inference models for the building IoT platform to power intelligent applications – ensuring you can check in on your loved ones. It preserves privacy by design and keeps the users’ sensitive data within the home.
CasparSense uses multi-modal sensors within the home to predict user wellness, activities and intents – helping you ensure comfort for residents throughout your properties. Our technology is compatible with voice assistants like Amazon Alexa and Apple.
CasparAdapt is a library of Deep Co-Reinforcement Learning tools that are designed to intelligently adapt and personalize the home to residents. Our technology allows for a screenless UI and thus is easy-to-use for everyone.
import casparSense
import iotPlatform
platform = iotPlatform(room="bathroom”)
sensor = ["thermal", "sound", "vision"])
sense = casparSense(room="bathroom")
prob = sense.fall()
if prob > 0.5:
platform.alert(method="text")
import casparSense
import iotPlatform
platform = iotPlatform(room="bedroom”)
sensor = ["thermal", "sound", "vision"])
sense = casparSense(room="bedroom")
sense.run()
adapt = casparAdapt(room="bedroom")
@callback (userAction)
def userActionUpdate():
adapt.learnPrefs(sense.activity, userAction)
@callback (sense.activity)
def automatedBehavior():
platform.takeAction(adapt.getLearnedPrefs(sense.activity))
