ABS Safety and Security campus (SSC)
Project description
The main research question is as follows:
How can an analysis-tool be designed and implemented to analyze diverse sources for predicting potential conflicts, disasters, or other incidents, informing the partners of the safety and security campus (SSC)?
An analysis tool for the Safety and Security Campus (SSC) should collect and process data from various sources, like sensors, social media, and weather reports, to predict potential conflicts or disasters. Using machine learning, it can identify patterns and risks, helping the SSC act proactively.
A user-friendly dashboard would show clear visualizations, such as heat maps and alerts, to highlight key insights. The tool should securely share information with partners and adapt to include new data sources. With automated reports and notifications, the SSC can quickly respond to threats and improve safety effectively.
Context
InnoLabs is collaborating with the Safety and Security Campus (SSC), an innovative hub located at the army base in Oirschot, which is dedicated to enhancing safety and security solutions for the region. SSC serves as a collaborative platform that unites various stakeholders, including Brainport Eindhoven, local fire brigades, the 13 Lichte Brigade, customs authorities, police departments, and the municipality of Oirschot. This unique consortium fosters innovation by leveraging the diverse expertise of its partners to develop comprehensive solutions that address pressing safety challenges faced by the community.
The SSC's approach emphasizes the importance of collaboration with the surrounding ecosystem of companies, research institutions, and knowledge centers, both within the Brainport region and beyond. By pooling resources and knowledge, SSC aims to ensure the safety and security of its citizens while promoting technological advancements that can be applied operationally in real-world scenarios. Their mission is to “jointly tackle shared challenges within the safety domain,” and this collaborative ethos is at the core of all initiatives undertaken at the campus.
The specific assignment at hand focuses on the development of an analytics tool designed to enhance public safety through the monitoring of open-source data. Given the increasing reliance on digital platforms and social media for communication and information dissemination, the need for effective data analysis has become more pressing. Local authorities require a systematic way to identify and respond to potential threats, such as riots, natural disasters, and illegal gatherings. By utilizing open-source data, the analytics tool will empower these authorities to receive timely insights, thereby improving their capacity for proactive risk management.
Results
The finished products will include an analysis tool capable of scanning open-source media to identify relevant information regarding potential threats to the Brainport community. The tool will process data and automatically generate reports twice daily—at 08:00 and 17:00—summarizing potential events or gatherings that may pose risks to public safety.
In addition to the tool, thorough documentation will be provided detailing how the system works, allowing for further development and improvements. All research conducted during the project will be documented, and the findings will be summarized in a comprehensive research report. This report will include recommendations for future actions and a conclusion based on the project’s outcomes.