counting sea containers

SecurePort's primary objective is to create a proof of concept AI model capable of analyzing drone images to identify containers with hazardous contents in close proximity. By collecting a comprehensive dataset of drone images and annotating them with hazardous material labels, the project lays the groundwork for developing a convolutional neural network (CNN) model trained to recognize patterns indicative of dangerous substances.

The ideation phase of SecurePort encompasses the development of key stages: Data Collection: A diverse dataset of drone images capturing various angles and perspectives within the Port of Antwerp is meticulously gathered, containing crucial information about containers and their contents. Data Annotation: Domain experts meticulously label the dataset, identifying containers carrying hazardous materials such as flammable, explosive, toxic, or corrosive substances. AI Model Development: A sophisticated CNN model is crafted to analyze drone imagery and identify containers with hazardous contents, leveraging the annotated dataset to recognize pertinent patterns. Alert Generation: Upon processing drone imagery, the AI model generates alerts listing containers and their hazardous contents, enabling prompt corrective actions by port authorities. Decision Support: In addition to alerts, SecurePort provides visualizations to assist port personnel in making informed decisions, effectively mitigating risks associated with hazardous container placements.