1. A dynamic risk assessment methodology was developed for the protection of crowds during mass gatherings, centered on human factors to effectively produce policies and deploy adequate solutions.
2. A policymaking toolkit was created for the long-term and strategic decision-making of security policymakers, including a database of empirical data, statistics, and an analytical tool for security policy modeling.
3. A set of human-centered tools was designed for Law Enforcement Agencies (LEAs), including real-time crowd behavior forecasting, innovative communication procedures, semantic intelligence applied to social networks and the internet, and novel computer vision techniques.

Throughout its duration, LETS-CROWD fostered communication and cooperation among LEAs, first responders, civil protection agencies, and citizens to enhance security during mass gatherings. The project placed a strong emphasis on citizen-centered research, assessing the impact of security measures on the public and their perception of them while ensuring compliance with EU fundamental rights.

The effectiveness and impact of the project were demonstrated through practical trials involving seven LEAs and relevant emergency services units. To evaluate performance, transferability, scalability, and large-scale deployment, these demonstrations were conducted across eleven use cases.