Introduction to Current Projects
NuEra-ID's current projects span a range of activities focussed either directly on the development of a unique system of identification or the development of tools that will help customers adopt this technology. As such, some are inventive developments, others are software projects being undertaken for clients. All involve, wherever possible, the use of Open Source Software and applied science.
A summary of the current projects as follows:
- Numerically Unique Encrypted Redundant Array (NU-ERA). A technology suite that makes possible the cost-affordable individual identification of every object of interest (ranging from people to individual pieces of paper) within any organisation.
- Job Tasking and Reporting System(JTaR). JTaR is a software solution that demonstrates how companies providing contracted services can safely and securely utilise a customer's computer network and resources to report their work to their own computer system which is external and separate to the network of their customer.
- Item Tracking and Stocktaking System(ITAS). ITAS is a software application, installed at the Defence National Supply and Distribution Centre, that utilises and demonstrates the value of the NU-ERA tecnology Suite.
- Low Cost, Metropolitan Area Network(LC-MAN). LC-MAN is the means by which is it possible to set up a low cost, high performance WiFi network in any area, be it an industrial complex, suburbia or a rural village in a developing country. LC-MAN is deliberately designed to require minimal electrical power to operate and so is suitable for deployment in countries and situations where electrical power is not easily accessible.
- Common Application Front End(CAFE). CAFE is a format standard for input and output forms that makes it possible for software applications, created by numerous different contractors, to have the same look and feel. CAFE greatly reduces the need for operator training, minimises the clerical effort associated with data input and application operation and prevents, as much as possible, accidental erroneous data input.