One in three adults over the age of 65 fall each year, making falls the leading cause of death due to injury for older adults. For the growing $222 billion long-term care (LTC) industry, facility operators are struggling to provide quality care and residences while managing increasing resident acuity and increasing fall rates. In the U.S. alone, these falls cost operators $1.8 billion annually, and contribute to lasting indirect revenue loss from damaged reputations. To help solve this problem, Luvozo developed the Automated Fall Assessment System (AFAS) in NSF SBIR Phase I award #1548784, to address the 31% of preventable falls that are attributed to environmental hazards such as floor clutter, rugs, poor lighting, and low transition contrast. The system consists of an inexpensive 3D sensor, computer vision algorithms, and assessment models to detect and evaluate hazards that commonly cause a fall. We tested the system against a panel of physical and occupational therapists and found that AFAS identified more hazards than the average of the experts.