The BorderForce BM-SAF (Border Management Situation Awareness Framework), is a comprehensive framework that combines functionalities with methodological blueprints to support border management operations and specifically identification of situations of interest in border regions under survailance. It offers a systematic approach for consuming and interpreting sensor data, including Open-Source Intelligence (OSINT), to deliver timely, consistent information on identified potential threats (incidents), along with associated risk evaluations. The framework integrates the following core components to enable the efficient ingestion, tracking, and monitoring of sensor observations:
- OSINT Component,
- Multimodal Data Fusion Component,
- Risk Assessment Component.
These technologies process data from the available sensors that detect physical environmental changes such as the movement of entities and auxiliary data services that provide contextual insights through weather data, and terrain information. The BorderForce envisions to provide innovation traits by integrating OSINT capabilities that gather publicly available information to enhance situational awareness and procedures to formulate and apply CIRAM-compatible risk assessment enabling the evaluation of potential threats and the categorisation of risks to support informed, operational decision-making.
OSINT
The OSINT component enables automated acquisition and analysis of open-source data relevant to border security operations. It collects publicly available information and utilizes machine learning models to understand textual dependencies and extract meaningful intelligence from diverse and seemingly unrelated content. The system specifically targets information related to sensitive locations and includes both pre- and post-processing tools to ensure data integrity and the quality of extracted intelligence. These features are formatted for direct integration with the Data Fusion subsystem, enhancing situational awareness. Additionally, the OSINT module supports multilingual analysis through integrated translation tools and operates in full compliance with ethics and privacy regulations, ensuring responsible and lawful use of data.
Multimodal Data Fusion
The Multimodal Data Fusion component integrates and analyses data from diverse sources to produce tracks of sensors’ observations (observations over time regarding the same object/target). It performs sensor fusion across all inputs, including cameras, radars, satellites and RPAS/UAVs, ensuring a unified operational picture. Moreover, the component it combines sensor data with features extracted from Open-Source Intelligence (OSINT). The platform applies predictive analytics to classify potential risks by type and severity. It also tracks unfolding incidents in real time and employs explainable AI to identify and highlight the key contributing features, enhancing transparency and operational decision-making.
Risk Assessment
The Risk Assessment component will be implemented on the BorderForce Risk assessment Framework that envisions to leverage FRONTEX’s Common Integrated Risk Analysis Model (CIRAM) to ensure a consistent and standardised evaluation of threats across the system. It will generate georeferenced Risk Indicators by integrating fused sensor data with potential features derived from Open-Source Intelligence (OSINT), maintaining geolocation metadata from the original sources to preserve spatial relevance and traceability.