Solving Space Utilization Challenges

Sunnybrook’s medical staff expressed concerns about limited space availability, particularly for bookable exam rooms. However, casual observations indicated that some rooms appeared to remain empty. Sunnybrook needed a reliable solution to measure actual room usage accurately while addressing two significant concerns:

Privacy: Ensuring patient privacy was paramount, particularly in sensitive clinical settings.

Accurate Detection: Existing solutions struggled to detect minimal motion, such as during procedures like blood transfusions, where patients may remain largely still.

HH Angus was engaged to design and implement a solution capable of addressing these challenges while delivering actionable insights.

Solution | Smart Sensors and AWS Integration

Our Digital Services team developed an innovative solution leveraging cutting-edge sensors and AWS services:

Sensor Deployment:

• • mmWave Sensors: Initial deployment involved mmWave sensors capable of detecting micro-motions, such as breathing, to confirm room occupancy. These sensors were equipped with cellular SIM cards to operate independently of Sunnybrook’s network.
  • 3D Stereoptic Sensors: To further expand the data gathered from the various clinics, the move to 3D-stereoptic sensors was used to provide not just occupancy status of exam rooms, but also the near real-time occupancy count data. Enhancing scalability, these sensors could monitor multiple rooms simultaneously, offering greater hardware efficiency.

Security and Connectivity:

• • mmWave sensors utilized mTLS (mutual Transport Layer Security) for secure data transmission.
  • Custom authorization for 3D-stereoptic sensors was implemented using AWS Lambda.

Data Aggregation and Storage:

• • Data was streamed via Amazon Data Firehose and AWS IoT Core, stored in AWS S3, and processed through AWS Lambda.
  • A centralized S3 data lake provided a secure, scalable repository for all processed data.

Visualization and Insights:

• • Data queries were conducted using AWS Athena, while AWS QuickSight offered intuitive 2D dashboards for near-real-time analysis with minimal latency.

This comprehensive approach ensured seamless integration, robust data security, and actionable insights for Sunnybrook.

Outcome | Actionable Insights and Future Expansion

The solution provided Sunnybrook with detailed, data-driven insights into space utilization:

Initial Findings: The installation was completed in December 2024, and data collection began in January 2025. Analysis of the 11 monitored exam rooms in Sunnybrook’s M-Wing, conducted from January to March 2025, revealed a surprising utilization rate of only 33%. This insight challenged initial staff assumptions and highlighted opportunities for more efficient space planning.

Future Outlook: New medical clinics, which opened in January 2025, will contribute additional data to further refine Sunnybrook’s understanding of space usage and inform future expansion strategies.

Through this project, Sunnybrook is well-positioned to optimize its clinical spaces, ensuring that resources are allocated effectively to enhance both staff workflows and patient care delivery.

Key Outcomes Summary

Accurate Space Utilization Data: Revealed underutilization of monitored exam rooms, providing actionable insights.

Efficient Resource Allocation: Enabled informed decisions about space planning and allocation.

Scalability: Designed for expansion, with sensors deployed to additional clinics.

Improved Patient Care: Enhanced operational efficiency supports better patient care delivery.

Predictive Analytics: Tool for staff to forecast resourcing needs based on the day of the week using historical trends

Privacy Assurance: Leveraged secure sensor technologies to maintain patient confidentiality.

AWS Services Used

AWS S3 (Simple Storage Service): Acted as the central repository for storing and
retrieving large datasets, facilitating data analysis and accessibility.

AWS IoT Core: Enabled secure, scalable connectivity for IoT devices, allowing for efficient data collection and integration into the cloud.

AWS Athena: Offered an interactive query service to analyze data in Amazon S3 using SQL, simplifying the extraction of actionable insights from complex datasets.

AWS QuickSight: Provided visualization tools and dashboards for business intelligence, enabling Manulife to derive and act upon insights from their data effectively.AWS Lambda: Supported serverless computing, automating data processing and transformation tasks without the need for server management.

Amazon Data Firehose: Streamlined the capture, transformation, and loading of streaming data, ensuring efficient data flow from IoT devices to storage and analysis tools.

AWS IoT Events: Monitored sensor data for specific conditions, facilitating real-time alerting and response mechanisms to optimize building operations.

AWS Step Functions: Orchestrated complex data processing workflows, coordinating the various components of the ETL pipeline for streamlined operation and maintenance.