Sensor Augmented Factory Environment (SAFE)

This project aims to develop, test, and demonstrate an Internet of Things (IoT) architectural framework for integrating endpoint devices as sensor technologies that assess common worker safety risks in a manufacturing environment.


Sensing devices that assess variables such as worker posture; their physiological and fatigue states; exposure to chemicals; thermal, mechanical, and vibration hazards; and fall protection interlocks are commercially available and effectively monitor risk conditions. They also provide feedback to end-users and manufacturing managers. However, many of these technologies are platform specific and require linking to independent, third-party cloud environments to access analytics and data dashboards.

Proposed Solution

Building on the MxD 19-13 Human Workflow Digital Twin project, the team from Boeing, Northwestern University, and Modzy intends to produce a test bed to integrate safety endpoint devices with a scalable edge computing system. That system will interface with back-end analytics and follow business rules for feedback to users and manufacturing stakeholders. A substantial portion of the project will address barriers to adoption of endpoint sensor devices that measure/monitor safety conditions and worker health and environments.


This project could provide proactive ways to improve worker safety and health, cut costs, reduce injury-related delays, and ensure better working environments for manufacturing employees.