The Sonalysts Human-Autonomy Interaction Laboratory (HAIL) conducts research, development, test, and evaluation of Human-Machine Interfaces (HMIs) for a variety of systems for the Navy, Space Force, Air Force, Army, and more. The UConn student team developed the Interface Crowdsourcing Environment (ICE) to digitize the crowdsourcing of HMIs and enable more rapid processing and analysis of design data from diverse groups of participants. The result is better HMIs for applications such as mission-critical Department of Defense systems.  A multitude of methods are used to design HMIs, including interviews, focus groups, surveys, and job observations. One additional method is to 1) provide end users a blank paper outline of the displays and a list of HMI components that must be included and 2) have users draw how they would ideally like the HMI to look. Analysts then manually recreated each paper drawing in PowerPoint and manually assigned colors to different components. Finally, they adjusted transparencies until heatmaps are generated showing where each HMI component should go. While this manual approach yielded valuable insights, it was labor intensive, error prone, and could not explore differences across demographic groups. ICE is a web-based platform that consolidates and automates the planning, collection, analysis, visualization, and exploration of this information crowdsourced from a large and diverse group of users. ICE enables simpler and more cost-effective data collection at greater scale, drastically increasing the quality of analytics and design of HMIs. ICE fully removes the need for paper/pen data collection, automatically processes and analyzes data based on common methods, and gleans insights through interactive visualizations, where analysts can rapidly toggle data on or off based on demographic features of users or other parameters. This application will greatly improve analyst workflows and empower analysts to design better HMIs.