AI MARS: Enhancing Security for Mass Events

AI MARS (Intelligence system for monitoring, alert and response for security in events) is a four-year project funded by the CDTI (Centro para el Desarrollo Tecnológico e Industrial) within the Strategic Program of Industrial Consortiums for Research (CIEN Program). The AI MARS consortium leaded by RETEVISIÓN (CELNEX group), includes five other companies (TELEVES, EMERGYA, SNGULAR, SHS, and HERTA), and is supported by four public research organizations (Universidad de Granada, Instituto Tecnológico de Castilla y León, Universidad Carlos III de Madrid, and Universidad Politécnica de Madrid).

The main objective of the project is to develop technological solutions capable of providing useful information in real time to public security forces and private security companies, as well as to managers of large public spaces (shopping centers, sports venues, etc.) to prevent attacks, agglomerations, disturbances and other incidents in large concentrations of people and other elements with high security requirements.

AI MARS contemplates the use of different technologies for the identification of objects (weapons, vehicles, etc.) and people, including advanced video processing techniques, recognition of biometric patterns (iris, facial, vascular), device detection mobile (WiFi, Bluetooth, cellular networks), and the use of sensors and IoT (Internet of Things) devices. Likewise, it raises the use of advanced data analytics solutions using Big Data, Machine Learning and Artificial Intelligence techniques. The need to facilitate on-site deployments, specifically oriented to each application case, as well as the convenience of carrying out the local processing of the data to minimize the response time, make the 5G technology and some of its key functionalities, such as the Network Slicing and the Mobile Edge Computing (MEC), especially indicated for the project. In addition, AI MARS considers essential to provide advanced visualization interfaces, including virtual and augmented reality techniques.

Within AI MARS, the RSTI group will carry out research on new sensors to detect the presence and activity of devices in areas of high concentration of people and things. These sensors will be integrated into the global identification and tracking platform, for their analysis and correlation with other data sources of the system. In this sense, the RSTI group brings its experience in WiFi Tracking technology and the pilot service of analysis of people flows in the Smart CEI Moncloa platform.

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