Sensor technologies such as infrared sensors and hyperspectral imaging, video camera surveillance are proven to be viable in port security. Drawing from sources such as infrared sensor data, digital camera images and processed hyperspectral images, this article explores the implementation of a real-time data delivery system. In an effort to improve the manner in which anomaly detection data is delivered to interested parties in port security, this system explores how a client-server architecture can provide protected access to data, reports, and device status. Sensor data and hyperspectral image data will be kept in a monitored directory, where the system will link it to existing users in the database. Since this system will render processed hyperspectral images that are dynamically added to the server - which often occupy a large amount of space - the resolution of these images is trimmed down to around 1024×768 pixels. Changes that occur in any image or data modification that originates from any sensor will trigger a message to all users that have a relation with the aforementioned. These messages will be sent to the corresponding users through automatic email generation and through a push notification using Google Cloud Messaging for Android. Moreover, this paper presents the complete architecture for data reception from the sensors, processing, storage and discusses how users of this system such as port security personnel can use benefit from the use of this service to receive secure real-time notifications if their designated sensors have detected anomalies and/or have remote access to results from processed hyperspectral imagery relevant to their assigned posts.
Applying hyperspectral imaging technology in port security is crucial for the detection of possible threats or illegal
activities. One of the most common problems that cargo suffers is tampering. This represents a danger to society because
it creates a channel to smuggle illegal and hazardous products. If a cargo is altered, security inspections on that cargo
should contain anomalies that reveal the nature of the tampering. Hyperspectral images can detect anomalies by
gathering information through multiple electromagnetic bands. The spectrums extracted from these bands can be used to
detect surface anomalies from different materials. Based on this technology, a scenario was built in which a
hyperspectral camera was used to inspect the cargo for any surface anomalies and a user interface shows the results. The
spectrum of items, altered by different materials that can be used to conceal illegal products, is analyzed and classified in
order to provide information about the tampered cargo. The image is analyzed with a variety of techniques such as
multiple features extracting algorithms, autonomous anomaly detection, and target spectrum detection. The results will
be exported to a workstation or mobile device in order to show them in an easy -to-use interface. This process could
enhance the current capabilities of security systems that are already implemented, providing a more complete approach
to detect threats and illegal cargo.