A senior care platform company using an innovative IoT hardware + software solution to continuously monitor and assess the well-being of older adults. Their technology uses composite environmental sensors to infer each senior’s daily activities—creating a real-time view of individual well-being.
To deliver on the promise of being “the next best thing to being there,” the client needed every device to behave like a personalized caregiver. That meant each device had to automatically learn and adapt to the unique habits of individual seniors—at scale, and with minimal manual setup.
The client partnered with thinkbridge to evaluate scalable solutions to personalize tens of thousands of devices across their platform.
thinkbridge engineers implemented a machine learning algorithm that automatically learns the daily habits of each senior and detects anomalies that may indicate changes in well-being. The algorithm improves continuously, using a feedback loop where caregiver corrections are fed back into the model—enhancing personalization over time.
The intelligence was embedded directly into each device, eliminating the need for new workflows or manual configuration. This resulted in an unprecedented level of personalization—allowing every device to adapt and respond to its user like a real caregiver would.
The solution is now in production and actively used across thousands of devices.
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