Mr. Manuel R. Saldaña Profile

Manuel R. Saldaña

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Proceedings Article | 3 June 2014 Paper

A data-management system using sensor technology and wireless devices for port security

Manuel Saldaña, Javier Rivera, Jose Oyola, Vidya Manian

Proceedings Volume 9074, 90740J (2014) https://doi.org/10.1117/12.2051157

KEYWORDS: Sensors, Databases, Java, Computer security, Hyperspectral imaging, Image sensors, Image processing, Sensor technology, Data modeling, Network security

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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.

Proceedings Article | 18 May 2013 Paper

Security inspection in ports by anomaly detection using hyperspectral imaging technology

Javier Rivera, Fernando Valverde, Manuel Saldaña, Vidya Manian

Proceedings Volume 8743, 87430C (2013) https://doi.org/10.1117/12.2018067

KEYWORDS: Inspection, Hyperspectral imaging, Image processing, Detection and tracking algorithms, Information security, Target detection, Human-machine interfaces, Homeland security, Mobile devices, Cameras

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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.

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