Knowspace
AI-Powered Senior Care Monitoring System
"futureproof took a complicated technical problem and crafted a layperson's solution. They are the only technical team we've worked with that was able to truly listen and understand the nature of our business, along with the technical ability to develop an off the shelf solution. And it didn't require a steep learning curve for my team or our customers to implement."
— Jack Burden, Founder and CEO, Knowspace
THE CHALLENGE
Knowspace needed to navigate the complex technical landscape of developing their real-time monitoring platform that processes millions of data points from IoT devices.
They faced challenges in selecting appropriate technologies for their data pipeline, including MQTT brokers, stream processing frameworks, and indoor positioning algorithms.
Additionally, they needed guidance on hardware options, system architecture optimization, and implementing practical machine learning approaches for behavior recognition and fall detection.
OUR SOLUTION
futureproof provided structured guidance on selecting appropriate technologies for Knowspace's data pipeline, including MQTT brokers, stream processing frameworks, and indoor positioning algorithms.
We helped them evaluate hardware options, optimize their system architecture, and implement practical machine learning approaches for behavior recognition and fall detection.
Our advisory services included technical architecture reviews, vendor selection for IoT components, and implementation planning for their AI analytics pipeline.
During a 60-day pilot in late 2024, seniors were able to choose one or more wearable devices from a broad catalog. This included wristwatches and pendants among other stylish, lightweight options.
Each device was automatically provisioned in seconds at the front desk by ALF staff using a custom, secure mobile app. 30 million data points were collected at a rate of 1M per device per week with an operating cost of under $300/mo and capacity for 1000 devices.
SUMMARY
Knowspace monitors and protects seniors with cognitive impairments.
Their technology, deployed at Assisted Living Facilities (ALFs), combines portable Bluetooth beacons, wall-plug gateways, and AI analytics to provide real-time location tracking and privacy-preserving behavioral insights without the use of invasive cameras.
The system alerts staff to potential falls or emergencies with 3 second latency from event to alert, and provides detailed reports for facility management.
RESULTS
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1M data points per device per week
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3-second latency from event to alert
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Data pipeline costs reduced by 90%
TECHNOLOGIES
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BLE (Bluetooth Low Energy)
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MQTT (Message Queuing Telemetry Transport)
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Kafka (Stream Processing) using Quix.io
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Data Cleaning and Device Positioning
SERVICES
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Opportunity Assessment
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Vendor Selection
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Implementation Roadmap
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Pilot Execution
GALLERY
Main landing page and device onboarding instructions
Selection of wearable devices available to seniors in the Knowspace system
Alert system providing staff with real-time notifications of potential emergencies
System performance dashboard showing data collection rates and latency metrics
Interactive facility map showing real-time resident locations and movement patterns
Visualization of the alert processing pipeline from sensor data to staff notification
Simplified architecture visualization showing key components and data flow
High-level architecture diagram showing the complete system infrastructure
Time-series database visualization of resident movement data
Correlation analysis of multiple data streams for pattern identification
Detailed view of sensor data patterns used for behavior analysis
Signal strength analysis used for precise indoor positioning of residents
Stream processing pipeline using Quix.io for real-time data analysis
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