Development of Vision-based Load and Configuration Safety Monitoring System for Mast-Climbing Work Platforms

The Centers for Disease Control and Prevention is proceeding with a sole source firm fixed price contract award to Stony Brook University to develop a lightweight machine learning system designed to monitor the safety of mast climbing work platforms through vision-based load and configuration analysis. Stony Brook University is the only entity capable of fulfilling this requirement due to its exclusive possession of a proprietary dataset generated from prior research, along with the specialized institutional knowledge of the original study design, data collection methods, and machine learning modeling techniques critical to the project’s success. No other vendor has access to this dataset or the requisite expertise to ensure the system’s quality, accuracy, reliability, and timely delivery. This acquisition is authorized under FAR Part 6.103-1 for other than full and open competition, given the unique and irreplaceable nature of Stony Brook University’s capabilities. The solicitation number is 75D30126Q7915, and while the contract is intended for sole source award, the government is inviting any firm that believes it can meet the requirement to submit a written capability statement by August 13, 2026. Responses must demonstrate equivalent experience, assets, and technical proficiency without compromising performance standards or schedule. The work will be performed in Georgia, and inquiries should be directed to the designated point of contact, Jariya Taylor, through the CDC Office of Acquisition Services under the Department of Health and Human Services.