We envision a sensor-enabled mobile system to assist organizers and participants of public events in emergencies and evacuation situations using human computing principles. By autonomously detecting elements of emergent collective behavior (e.g. clogging, queuing, herding), efficient interaction and information sharing with specific groups in the crowd is enabled. We have previously shown the technological feasibility to infer collective behavior patterns from mobile sensor data. In this paper we report on key user aspects influencing further investigations: the perceived usefulness of this technology; the desired system deployment vector; and privacy considerations. Based on answers of 92 attendees at a city-wide public event we found that mobile phones were the preferred vector for mobile emergency assistants. We confirmed the acceptance of sharing privacy sensitive context information in this limited application purpose. Additionally, we report statistics on the desired feature sets of a mobile service to augment penetration of such emergency technology by adding value for non-emergency use.