Crowd sensing utilizes a large group of users with devices capable of sensing to collect data for analysis. The motive of crowd sensing is to generate inferences from collected data. Examples of these applications include measuring traffic congestion, bike route quality, parking spot availability, and pollution levels. Since these applications are not necessarily the job of software developers, one of the challenges for crowd sensing is the effort required for task initiators to create and deploy a task, especially when they lack technical expertise. We are developing a framework to ease the development of crowd sensing tasks for non-experts by enabling them to create crowd sensing tasks and analysis using automated GUI-based tools for many common cases. These tasks are then pushed to a marketplace to make it easier for users to discover tasks that they want to participate in (or that have incentives that are appealing to them). We will demonstrate this system and allow participants of the demo session to create their own tasks and Percom attendees can participate in collecting data for those tasks throughout the week of Percom.