Grant: Alliance Grants

As safety threats continue to evolve and become increasingly complex, there is a need for new sensor architectures that can deliver persistent area protection. The main challenge addressed in this collaboration is establishing and sustaining continuous safeguarding of a particular area and conducting pre-emptive safety inspections of the surrounding region through automated, accurate, and efficient means. Currently, sensor systems for area protection mainly rely on humans who carry out monitoring activities and decision-making, which can result in information overload, delayed response times, and potential errors in identifying threat activities. To create a well-functioning monitoring system, designing autonomous sensing systems that can improve situational awareness, detect potential threats, and enhance response capabilities is crucial. Autonomous sensor architectures can help manage the increasing amount of data generated by these technologies, making optimizing modularity and scalability easier. The partnership aims to develop an advanced Scalable Cooperative Inspection Network (SCIN+) based on the SAPIENT platform for asset protection. The planned research will generate innovative techniques and algorithms to enable the timely identification of potential faults or limitations in securing infrastructure before they lead to safety concerns. The outcomes of this project include state-of-the-art edge-computing based image analysis, data fusion techniques for human activity recognition, predictive strategies for data anomaly detection and adaptive sampling strategies.