Human space systems, such as the International Space Station (ISS) and future planned missions to the lunar surface and beyond, require the crew’s ability to locate and manage the physical resources that are required for use to achieve mission objectives. However, the large number of assets, ranging from expensive, specialized equipment, to food, water, and medical consumables for the crew is an overwhelming management problem. These assets are stored in numerous containers that are sometimes nested within other containers, frequently removed from one container and placed in another location, consumed, and/or used, and then discarded. Additionally, sometimes the containers themselves are moved. The challenge is to track and manage these assets so that the crew can readily locate items and ground controllers can identify when there is a need to provide sufficient resupply for the mission.
The current asset management approach for the ISS program is a bar-code-based system, coupled with a relational database. This system is referred to as the Inventory Management System (IMS) and is operated jointly by NASA and the Russian Space Agency (RSA). IMS is relatively accurate; however, it is extremely labor intensive. Individual items in orbit, as well as stowage items, are tagged with unique barcode identifiers. Every time an item is removed and placed in a new location, the transaction has to be manually logged. Astronauts are allocated 20 minutes per day for IMS updates and asset management; however, the actual time spent is often much longer. Additionally, if an item (e.g., a specialized tool for a certain maintenance procedure or a scientific experiment) cannot be found after several hours of searching (a single astronaut hour in space can be valued at about $180,000 at the time of this reporting), flight managers will have to decide whether to search longer or resupply a new item on the next flight, which could potentially displace other items from being sent. With IMS, the quality of the data is entirely dependent on the diligence of a large group of personnel (between Houston, TX, US; Moscow, Russia; and ISS) to manually input entries, batch updates daily, and coordinate these efforts.
To address the need for timely, accurate, cost-saving asset management both on the ground and in space, the Rule-based Analytic Asset Management for Space Exploration Systems (RAMSES) was developed. RAMSES is an integrated state-of-the-art asset tracking and information management system with relational database support that can automatically perform an inventory of the contents of one or more smart containers, track their location, report their inventory, track this information to a central information server, apply rule-based analytics to that inventory information, and finally present and provide that information through a Web-based interface.
RAMSES accomplishes this by incorporating the following key system components: (1) Smart Containers, (2) RDF-based Asset Information and Location Software (RAILS), rule-based conditioning and processing software, (3) network-accessible database, and (4) user interface via Web application.
The Smart Containers consist of a radio frequency (RF)-shielded structure or bag with about 1 inch (≈2.5 cm) of spacing material that runs along the walls of the container; this prevents the shielding material from interfacing with the ultra-high-frequency (UHF) RFID tags. Within the shielding material, the spacing material contains an RFID antenna. The RFID antenna connects to an RFID reader, which is connected to the host electronics board. The host electronics provide Bluetooth, and optionally Wi-Fi communications with an external computer or network. The lid or closure of the container consists of a magnetic switch that connects to the power board and host electronics. When the lid is opened, the system powers up the electronics. Once the lid is closed, the system performs an inventory of the RFID-tagged items within the container and starts a timer on the power board. It then sends inventory information to a remote server. Additionally, the system powers down the electronics when the timer expires, to preserve battery life.
RAILS is a state-of-the art information architecture and software implementation program that applies the rule sets. The RAILS software provides sensor data reception service applications that allow the remote Smart Containers and other devices to report their inventories, container location reports, and other data to the Web server through HTTP Post messages that include automated remote user notification.
To accomplish this, the server integrates information provided by the RAILS user interface into its database, and applies the rule-engine to trigger or clear any alarm or alert conditions or derive analytic information based on the physical or sensor data presented to the server. The server also provides a Web application view of the inventory, container and facility status, and the results of the analytic rule set to the system’s users. With these components, information from disparate data sources can be automatically shared and synchronized, and then combined with mathematical models and rule-based analysis to produce meaningful data for asset tracking managment and effective decision making.
RAMSES, based on RFID technology, utilizes a modular layered architecture to automate multi-level asset management and tracking for both space and ground applications. The main advantages RAMSES’ radio frequency identification (RFID)-enabled “smart” containers, hierarchical container tracking, and rule-based asset information system have over current bar-code-based asset tracking are: (1) significant time savings through automation, (2) real-time remote status monitoring through the Internet, and (3) rule-based analytics for proactive asset management and state-of-the art information architecture and software implementation. RAMSES addresses NASA’s needs for reliable, unified, autonomous, and low-cost asset management for Earth-based activities, robotic and human lunar exploration, and planning for expeditions to Mars and beyond.
This work was done by James Francis, Joseph Zapetis, and Joe Parrish of Aurora Flight Sciences (formerly Payload Systems Inc.); and Fabrice Granzotto, Olivier de Weck, Abraham Grindle, Matthew Silver, and Sarah Shull of the Massachusetts Institute of Technology for Stennis Space Center. For more information, contact James Francis at Aurora Flight Sciences, 617-500-4897. Refer to SSC-00358.