ABSTRACT While the U.S. has more nursing-home residents than any other country, families have become reluctant to send their elders to long term care facilities (LTCFs) due to fear of rampant infection. These facilities need to raise the confidence of their clients by revamping their approaches to cleanliness and providing reassuring proof to families that their elders will be safe. Effective cleaning in LTCFs involves monitoring the efficacy of the cleaning methods used. Cleaning procedures in LTCFs are increasingly moving towards more standardized methods, while monitoring of cleaning efficacy is generally based on visual assessment. Some facilities are beginning to adopt measures beyond visual assessment such as swab-based Adenosine Triphosphate (ATP) bioluminescence, but these costly and time-consuming swab tests are not widely adopted. Studies show most LTCFs would benefit from standardized tools such as checklists, more frequent staff education including specific product use training. The main objective of this project is to bring a new auditing system to long-term care facilities that provides instant contamination detection, rapid surface disinfection of invisible contamination (e.g. body fluids, saliva and respiratory droplets that can host pathogens) and documents proof of cleanliness. We believe our Contamination, Sanitization Inspection and Disinfection (CSI-D) technology will change cleanliness monitoring standards by allowing users to see contamination, in real time, for immediate remediation. The CSI-D system is not intended to be a primary disinfection or cleaning tool; instead, it acts as a post-cleaning audit solution complementary to other post-cleaning auditing tools (ATP, FT-IR, etc.), as well as providing documentation of cleanliness. The system’s disinfection capability is intended to provide spot disinfection only during audits or incident response and not employed as a large area disinfection method (e.g. fogging). This Phase I SBIR will validate the usability of the CSI-D as a post cleaning auditing system to detect, disinfect and document residual contamination, and apply risk-mapping algorithms to improve the current management of cleanliness in LTCFs. This project is a collaboration with AI and Machine learning researchers at the University of North Dakota and Valley Senior Living in Grand Forks, ND, and Edgewood Healthcare in Fargo, ND who will provide important input to the design process and access to long term care facilities for pilot studies. Aim 1 will include building the CSI-D software for long term care facilities, including developing the software specification, software for data management, and the contamination detection algorithm. Aim 2 will include the pilot test at LTCFs, including the development of the audit inspection procedure (task list), comparing efficacy of CSI-D with visual assessment and ATP bioluminescence detection, and development of the dynamic risk analysis algorithm. Future directions: ...