Legacy Systems

Organizations may have compelling reasons to maintain an old system, such as:

The system works satisfactorily, and the owner sees no reason to change it.
The costs of remodeling or replacing the system are prohibitive because it is large, monolithic, and/or complex.
Training on a new system would be very costly in time and money lost, compared to the appreciable anticipated benefits of replacing it (which may be zero).
The system requires close to 100 percent availability, so it cannot be taken out of service, and the cost of designing a new system with a similar level of availability is high. Examples include systems for managing customer accounts in banks, computerized reservation systems, air traffic control, power distribution (electrical grids), nuclear power plants, military defense facilities.
The way the system works is not well understood. This situation can occur when the system designers have left the organization, and the system has either not been fully documented or documentation has been lost.
The user expects that the system can be easily replaced when necessary.

Legacy systems often run on outdated (and usually slow) hardware. Spare parts for this equipment may become increasingly difficult to obtain.

If legacy software runs only on aging hardware, the cost of maintaining the system may outweigh the cost of replacing the software and hardware unless some form of emulation support allows the software to run on new hardware.

These systems can be difficult to maintain, improve, and expand because there is a general lack of knowledge of the system, personnel who are experts in it have retired or forgotten what they knew about it, and personnel who entered the field after who was "bequeathed" never found out about it. This can be exacerbated by lack or loss of documentation.

Integrating with newer systems can also be difficult because new software may use completely different technologies. The type of bridging hardware and software that remains available for different technologies that are popular at the same time are often not developed for different technologies at different times, due to the lack of high demand for it and the associated lack of reward from a large economy of market scale, although some of these "technologies" are assumed to be developed by vendors and enthusiasts of particular legacy technologies (often called "retro computing" by communities).

Enhancements to legacy software systems

If it is not possible to replace legacy systems through the practice of retirement implementation, it is still possible to improve them. The majority of development is often spent on adding new interfaces to a legacy system. The most important technique is to provide a Web-based interface to a terminal-based mainframe application. This can reduce staff productivity due to slower response times and slower action from a mouse-based operator, however, it is often seen as an "upgrade" because the interface style is familiar to users. non-specialized and find it easy to use.

Printing enhancements are problematic because legacy software systems often do not add formatting instructions, or they use protocols that are not usable on modern PCs. A print server can be used to intercept the data and translate it into more modern code. Rich Text Format (RTF) or PostScript documents can be created using inheritance and then interpreted to a PC before being printed.

Biometric security measures are difficult to implement in legacy systems. A viable solution is to use a telnet or http proxy server to sit between mainframe users to implement secure access to legacy applications.

The change is taking place in some organizations to switch to automated business processes, which generate complete systems. These systems can then connect to the organizations legacy systems and use them as data repositories. This approach can provide a number of significant advantages: users are insulated from the inefficiencies of their legacy systems, and changes can be quickly and easily incorporated into animal byproduct software.

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Projects in analysis and design

We help agricultural companies maintain the traceability of their products, through semi-autonomous cloud and mobile applications.

When doing the engineering of the project, I realized that I can manage the traceability of any agricultural product, as well as its subsequent transformation processes, using machine learning.

In an agricultural process and its distribution chain, the application will be used mostly by agricultural workers and processing plant operators, as well as by financial and commercial executives.

A large part of traceability is learning about the control of processes and tasks that must be executed and controlled at each point of production in a farm field and commercial sector.

Large exporters must ensure food safety when exporting to regulated markets such as the European economic community.

Traceability is risk management to minimize and control food safety hazards. Each operator in the production chain is responsible for their traceability system.

According to European and American food control laws, they declare that traceability and self-control constitute one of the basic principles of food safety, and define the responsibilities of economic operators and the competent authorities in this area.

The Alimentarius Codex states that the controls (self-controls) that food companies must apply to guarantee the healthiness of the products they produce or market must be based on the hazard analysis and critical control points (HACCP) system. This HACCP system allows the identification, evaluation and control of significant food safety hazards.

The codex alimentarius classifies traceability as a prerequisite.

A digital world.

According to the World Economic Forum (WEF), the 4th industrial revolution is a digital revolution that merges technologies between the physical, digital and biological spheres.

Augmented reality (AR, VR), artificial intelligence (AI_), and the internet of things (IOT) accelerate the path towards digitalization.

The Internet of Things (IOT) is a system of computational, mechanical, digital devices, objects, animals or people. interrelated, with the ability to transfer information over the network without human intervention.

AI, also called machine intelligence, is intelligence demonstrated by machines, in contrast to human intelligence.

Machines (any type of computer) learn from information.

Machine Learning (ML) is the scientific study of algorithms and statistical models that computer systems used progressively to improve their performance on a specific task. These algorithms build mathematical models of information to predict or make decisions, without being explicitly programmed to perform said task.

These algorithms are used to filter email, detect network intruders, understand images and videos, among many other applications.

Augmented Reality the real world with different eyes. Augmented Reality (AR) is a technology that allows us to superimpose virtual elements on our vision of reality.

Augmented reality (AR) is the term used to describe the set of technologies that allow a user to visualize part of the real world through a technological device with graphic information added by this device. This device or set of devices adds virtual information to the existing physical information; that is, a virtual synthetic part to the real one. In this way, tangible physical elements are combined with elements virtual ones, thus creating an augmented reality in real time.

Legacy Systems

Legacy Systems

Enhancements to legacy software systems

A digital world.

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