Good Software Design

Strategies to achieve it

Even the best software has flaws. Don't assume that the technology will handle the situation 100% fault-free. Don't forget that applications are developed by humans. Humans make mistakes every day.

Failures will be reduced to the maximum, ensuring the success of your project, if the correct design team carries out a deep analysis of the situation to be handled.

In the design phase, consider from the most insignificant to the most relevant aspect that the system will handle. Avoid thinking, this or that will never happen. Rest assured that someday it will happen, the difference will be that you foresaw that event. The end user must be involved in this phase, or be the main source of information.

Consider "Scalability", a word in English that means that modifications can be easily made to the software without altering its flow, or that modules can be added to the software without altering it, and it is very important that the database has a good design. This will be very useful after you put the software into production, since the end user always requires something extra, such as generating this report or another data capture module that helps me relate this information with this other one, which by some reason was overlooked at the time of design.

Make an optimal database design and above all choose the correct database that meets the requirements of your project. Choosing an object-oriented programming language like Jakarta (Java EE), to develop your application would be a very smart idea, since Java handles "Scalability" very efficiently and works on multiple platforms, which makes it transportable, important for web applications.

Very important. Remember that technology is managed by humans. Sometimes humans tend to commit acts outside the law. It would be appropriate to establish and follow Internal Controls to guarantee the quality of the information and avoid fraud. Audit the information that the new system is reporting to you for a couple of years, to avoid legal action against you for erroneous information and of course to monitor possible failures and make the appropriate corrections quickly.

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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.

Strategies to achieve it

A digital world.

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