How monitoring maximizes profits in the photovoltaic industry

The integration of renewable energy and storage generates additional monitoring and control needs, not only to ensure optimal performance, but also for the earliest possible return on investment.

Monitoring is necessary to understand energy production and use, detect problems early and take appropriate action.

To understand how electrical energy is being used and how it can be optimized, owners must:

  • Track how photovoltaic (PV) energy produced is consumed by loads, stored, or injected into the grid
  • Track and analyze photovoltaic energy production trends along with load consumption
  • Calculate the economic benefits associated with reducing energy consumption from the grid

Asset management functions should also be provided by a PV system monitoring system. This should include evaluating the performance of the PV system, detecting offsets or faults, and immediate notification of faults. In addition, since PV inverters can affect the power quality of an electrical installation, it is recommended to measure and monitor power quality disturbances, especially harmonics and imbalances.

When integrating local sources, such as a photovoltaic system, into a building’s electrical installation, control functions are often required. These functions mainly depend on the local sources available, the contract with the local energy supplier and the type of installation: grid-connected, microgrid or off-grid.For example, for an installation with grid-connected PV production, the necessary control functions may include:

  • Limiting photovoltaic power generation so that energy is not pumped into the grid
  • Control of the power factor at the point of connection to the grid to avoid penalties
  • Shifting the load over the period of PV production to maximize self-consumption
  • Participating in demand response, especially if storage units or generators are also part of the plant

Advanced cloud-based analytics optimize the use of local power sources, resulting in additional savings.
Considering additional criteria such as changes in electricity rates, weather forecasts and expected consumption, advanced analytics provide the optimal system configuration. The setpoint for each local source is then transmitted to the local control system.

To learn more about PV plant monitoring recommendations, contact us at [email protected].

User interface: the key factor in interacting with software and applications

The more complex technology becomes, so do our needs. Two of the essential needs we seek, especially when it comes to business processes, are speed and efficiency. While we meet the need for speed and efficiency, we have realized that there is also another need: entertainment. We want to be entertained, to have interaction during our engagements. The user interface fills that void since our lives have been inundated by digitization. We may not realize how common and crucial its functions are. One thing is for sure: user interfaces make our lives much easier. In this blog, we have discussed the topic of user interfaces with a very basic approach, as this topic can easily become very detailed and technical.

What is user interface?

The term is self-explanatory: user interface (UI) is a tool/object that helps people interact and operate more efficiently and easily. In other words, it enables human interactions to occur with computers, software, applications and websites. There are two aspects that occur when humans begin to interact with the user interface: the ability to command efficiently and easily and to receive instant feedback that aids the decision making process for the operating human.

User interfaces are created with multiple layers, with the goal of appealing to users’ senses, such as touch, sight and hearing. These layers help humans expend as little effort as possible to achieve the expected results when interacting with it. Layers are supported by various devices to increase and facilitate the level of interaction, such as keyboard, mouse, microphone, touch screen, camera and many more.

Why is it important to have user interfaces?

In addition to facilitating and increasing the efficiency of human interaction, user interfaces play a key role in terms of the functionality of computers, software, applications or websites. Functionality is often measured by the speed and responsiveness of the user interface. It is also important to consider the user experience when designing and focusing on the functionality of user interfaces.

Below, we highlight important components of user interfaces. These components provide valuable information about the goals of user interfaces. However, user interfaces, in most cases today, contain multiple components.

Information architecture: Its goal is to provide an easy process, bringing out the most important information with minimum effort for the user. Information architectures can be built in hierarchical, sequential or matrix form. They also include tooltips, icons, progress bar, notifications, message boxes and modal windows.

Visual design: When it comes to visual design, color, contrast, typeface and video play a crucial role in maximizing user appeal. While the goal is to create the attraction, it is also considered mission critical to make the user continue the interaction as much as possible.

Input design: These controls allow users to interact with computers, software, applications and websites to complete the desired action. They include check boxes, radio buttons, drop-down lists, list boxes, buttons, toggle buttons, text fields and date fields.

Navigation components: As you can understand, they are placed in order to provide easy and efficient navigation for the user to interact with. Breadcrumb, slider, search field, pagination, slider, labels and icons are common examples.

User interface on the IDboxRT platform:

The IDboxRT platform is based on state-of-the-art technology and the latest IT security implementations with the ultimate goal of bringing efficiency, security and ease to your production.

Our platform is the ideal place to view, control, compare and analyze everything related to your business processes. We provide all the necessary information with an in-depth view. Moreover, the in-depth view is applied for each component level.

IDboxRT is a platform in constant development and evolution. Depending on the specific needs of the company, the platform can be adapted to the configuration of the operation.

Please contact us for more information on the updates from the IDboxRT team of experts.

Web 3.0: What is it and how does it differ from Web 2.0?

What is Web 3.0?

Although Web 2.0 may seem like an advanced approach to the Internet, it still has many drawbacks. What about the security of your personal data? With Web 2.0, trusted institutions take control of user data, especially because of the need for trusted intermediaries. If two parties want to make a transaction but do not know and trust each other, they will have to resort to the services of trusted intermediaries. However, the intermediary has control over the storage and management of the data, thereby increasing its power over the users. In addition, centralized power has never led to success in times of crisis, which requires decentralization.

Web 3.0 is a promising improvement over Web 2.0, especially given the major transformations in terms of infrastructure. The third generation of the Web, also called the semantic Web, uses an improved metadata system. The metadata system helps structure and organize all types of data, making them readable for humans and machines. The main benefit associated with Web 3.0 is almost the best twist on the differences between Web 2.0 and Web 3.0. Web 3.0 eliminates the need for centralized intermediaries and introduces the universality of information.

How revolutionary is Web 3.0?


Understanding the comparison between Web 2.0 and Web 3.0 should also focus on the uniqueness of Web 3.0. The third iteration of the Web is a formidable response to Web 2.0’s shortcomings with an emphasis on innovative technology. Web 3.0 uses artificial intelligence to enable machine-to-machine interaction as well as advanced analytics. In addition, Web 3.0 uses a decentralized network to bring data under the control of the owners. As a result, users are able to own their data as well as determine how it is distributed. In addition, the differences between Web 2.0 and Web 3.0 are improvements in user privacy and security. Web 3.0 uses encryption and distributed ledger technology to address trust issues that were evident in Web 2.0.

Notable features of Web 3.0


You can build a stronger foundation for understanding “What’s the difference between Web 2.0 and Web 3.0?” by focusing on Web 3.0 features. Here are some of the most important features of Web 3.0 that will help distinguish it from Web 2.0.

  • Web 3.0 uses artificial intelligence to deliver the right results at a faster pace along with access to real-time information.
  • Web 3.0 also allows users to tap into the potential of 3D images and graphics.
  • Web 3.0 has a Semantic Web functionality. This means that Web 3.0 can support understanding the meaning of words. As a result, machines and people can easily find, share and analyze information on Web 3.0.
  • Web 3.0 also offers important features such as improved privacy and security.
  • Web 3.0 uses improved authorization mechanisms using distributed ledger technology and encryption to protect user identity and data.

If you want to learn all about how Web 3.0 and related technologies can improve your business processes, contact us and our top experts will inform you!

What is the best way to successfully define, scale and lead Digital Transformation?

DEFINE A CLEAR DIGITAL STRATEGY
Planning a company’s digital transformation from the outset involves being able to see the big picture. You also need to be clear about your desired outcomes. Define your objectives from the outset. Decide what you want to achieve and make sure you understand why the organization needs to transform. Depending on your current and planned methods of operation, the following may be decisive factors:

  • Reduced supply costs
  • Increased sales volume
  • Reducing waste or duplication
  • Increasing profits
  • Attracting new customers
  • Catching up with or surpassing competitors
  • Implement new technologies

In summary, start by assessing the current state of your business. Consider the requirements of your employees and systems, as well as potential areas for improvement.

CALCULATING ROI BEFORE STARTING IOT PROJECTS
A digital transformation should include an assessment of how much the proposed technology will drive revenue growth. A return on investment (ROI) calculation provides a feasibility check prior to

SELECTIVE TECHNOLOGY INVESTMENT
Choosing the right tools and technology is critical. There are many digital transformation trends being discussed in the marketplace, but technology must serve the business, not the other way around. Choosing the best strategy for the IoT journey remains a challenge. Before deciding on an expensive IoT implementation and choosing the direction of your journey, examine your options and seek advice on choosing the best technology and systems for your business.

IT/OT INTEGRATION FOR IOT SOLUTIONS
Integrating information technology (IT) and operational technology (OT) is no easy task, but with the right approach, it can deliver unprecedented growth. By implementing the right IoT solutions, you can successfully bridge the gap and create an intelligent, interconnected foundation to improve business processes and add value to your data. By integrating IT and OT systems, you can unlock the power of your data to generate accurate predictions and make informed decisions.

To ensure that your digital transformation efforts do not stall, it is important to have a trusted partner to guide you on your digital transformation journey. Each digital journey is individual and should be tailored to the client’s needs.

By checking off the different aspects of this list, you will be on your way to a successful digital transformation. If you would like to discuss digital transformation readiness in more detail, please contact us and we will put you in touch with our experts.

Cantabria in Digital Transformation

David Vilasack, IDboxRT manager at CIC, participated last month, September 28, in the conference “Cantabria in the Digital Transformation” organized by Ascentic and inaugurated by the president of Cantabria, Miguel Angel Revilla.

The manager’s intervention was aimed at talking about the experience of the IDboxRT monitoring platform in Industry 4.0, focusing on one of its main success stories: Bosch, whose project with the tool involves the monitoring of thousands of signals between its Spanish plants in Madrid, Barcelona and Aranjuez. Among the benefits obtained by this customer, we can highlight the creation of calculations and subsequent consumption reports to evaluate energy losses, or even the acquisition of data from CO2 sensors for personnel control (COVID-19) and reports for HR and Medical Service on the status of the different rooms of the plant for CO2 control (COVID-19).

In addition, Vilasack spoke about the key technological pillars in Industry 4.0, on which the strategy and operations of any company in its digital transformation process must be based. Among them, he highlighted augmented reality, cybersecurity, Big Data, the cloud, also known as cloud computing, an essential axis since 90% of companies will partially or totally migrate to cloud environments in the next three years.

Artificial intelligence was another of the elements analyzed, as business environments will become much more intelligent, forming a clear cohesion between machines and humans. They will be more efficient, effective and competitive spaces due to the automation of processes, so companies will increase their production and productivity.

What is the difference between Operational Intelligence (OI) and Business Intelligence (BI)?

Understanding the differences between operational intelligence (OI) and business intelligence (BI) is crucial to contextualizing and taking action on the information and insights provided by your analytics toolset. While both operational and business intelligence are used to drive action and inform decision making, there are key differences that distinguish these two areas of analysis.

Business intelligence maintains a relatively narrow focus with an emphasis on finding efficiencies that optimize revenue or profitability. BI typically means taking a snapshot of data over a defined period of time in the past and reviewing it to understand how the organization might achieve better success in the future.

In contrast, operational intelligence focuses on systems, rather than profits. OI uses real-time data collection and analysis to reveal trends or problems that could affect the operation of IT systems and to help front-line workers make the best decisions about how to address those problems.

The differences between operational intelligence and business intelligence can be summarized as follows:

Business intelligence focuses on finding efficiencies that increase or protect profits, while operational intelligence focuses on maintaining the health of IT systems.

Business intelligence leverages more historical data, while operational intelligence relies on real-time data collection and analysis. Operational intelligence has been described as immediate business intelligence gained from ongoing operational functions, a definition that speaks to the real-time nature of data collection and focuses on the operational functions that characterize operational intelligence in an enterprise environment. While business intelligence typically runs within a specific data silo, operational intelligence helps organizations break down data silos to uncover trends and patterns of activity within complex and disparate systems.

From colorizing old photos to becoming more efficient with Deep Learning

The technology key in improving the present future

The ability to synthesize sensory data, while preserving the desired statistical properties, is currently proving to be a great success in different industries.

Many examples are based on this concept and apply it to various industries using technology. One of the most prominent is the case of DeOldify, an artificial intelligence program that translates black and white images into color, or Nvidia, with its proposal to create realistic images of fake landscapes or non-existent people’s faces, from semantic sketches.

GANs: The most interesting idea in Machine Learning of the last decade

These systems are based on a very specific neural network architecture, called Generative Adversarial Network (GAN), an artificial intelligence algorithm based on the fact that synthesized data must maintain both statistical properties and be indistinguishable from real data, a process similar to a Touring test for data.

Such concepts have their origins in the past, where the comparison was made through simple visual inspection. Nowadays, classification models, called discriminators, are used to distinguish between synthesized data and real data. In a more intuitive way, this network can be understood as two competing networks: the first one is in charge of generating candidates, synthesized data, while the second one evaluates whether the data is real or synthesized. The goal of training is to increase the error rate of the discriminating network, i.e. to deceive the discriminator.

Monitoring, deep learning and its business benefits

The solutions described above are adapted to various sectors such as “Smart”, “Industry 4.0” and “Energy” among others. Real-time asset monitoring software is starting to use these technological advances to solve common problems, such as, for example, connection failures. It often happens that some sensors sending data are partially disconnected, which could have been avoided if a generator-discriminator model had entered the game, replacing the missing data with synthetic data. From here we could consider the possibility of replacing some sensors completely with synthetic parts, which would ensure the highest possible quality and reduce the hardware infrastructure required for effective monitoring.

Currently, Spanish companies such as CIC Consulting Informático, with its asset monitoring product IDboxRT Inteligencia Operacional, consider Deep Learning as a tool to make their customers’ lives easier.

Example of predictive visualization of the value that each variable will have in the next 15-minute period.
Example of predictive visualization of the value that each variable will have in the next 15-minute period.

The series of measures in the field of Deep Learning in monitoring, developed by CIC Consulting Informático, leads to significant positive results at several levels. First of all, it provides favorable economic conditions, allowing savings in the operation and maintenance of specific equipment, while avoiding serious losses of information. For this reason, there are advantages associated with energy efficiency, such as the reduction in energy consumption resulting from the reduction in the number of physical components.

Back to the future with deep learning

Deep Learning is expected to have a revolutionary effect on the way companies operate in the near future, making them more efficient in terms of consumption and profitability, optimizing all their processes and achieving tangible results on a global scale.

Industrial IoT: at the service of ideas

This is nothing new. We are not talking about a breakthrough technology that will appear with force in 2020. The IoT is something that has been on the minds of its precursors for many years, since the 1990s, simply waiting for communications and systems integration techniques to support their ideas.

And it is precisely this last word that is the key to understanding the reasons why its adoption in the industrial field has not been as rapid as predicted by the major global consulting firms. The truth is that we are not talking about a technology in itself, whose mere application is capable of solving a problem, but about a concept of application of several technologies in the service of a basic premise: an idea.

During the first years of the IoT boom, there have been situations in which medium-sized and large companies did not take steps, but real leaps towards the “application” of IoT in industrial environments. The problem is that these leaps were simply based on investing heavily in IoT devices, whose data turned out to be anecdotal or ancillary.

From the experience accumulated by our IDboxRT team, we subscribe to the maxim “What can’t be measured can’t be improved”. But the hype that IIoT is experiencing should not drag us into an unjustified eagerness to collect useless data, the counterpart to this maxim is that we should only and exclusively measure those parameters that allow us to achieve the expected ROI.

On this solid basis, a tide of device manufacturers, models, protocols, etc. appears before the leaders of these initiatives. In this sense, it is difficult to predict which of them will dominate the market in the medium term, so it is essential to have an open IoT platform that allows communication with a variety of devices in a simple way, as this greatly facilitates the choice of the right device for each use, without fear that certain data will remain isolated as the technology evolves.

At the level of communication protocols, we find a variety of lightweight protocols that allow communication with remote devices powered by batteries, whose duration can reach several years depending on the protocol used and the refresh rate. From the well-known MQTT, through CoAP, to other less recognizable protocols such as BACnet, we will find a multitude of protocols implemented by different devices, which may create doubts in those who have data processing platforms with low flexibility.

It is precisely this open nature what makes the Operational Intelligence tool that we developed at CIC Consulting Informático de Cantabria, IDboxRT, appear as one of the references in Gartner’s 2018 Competitve Landscape: IoT Platform Vendors. Without being able to be considered solely an IoT platform, the ability to ingest data from any device, regardless of the protocol, makes IDbox one of the safest bets in this regard, since whatever direction the industry takes, our customers will always be able to integrate their data, combining different protocols.

The possibility of combining data from our “IoT park” with process data directly collected from PLCs, SCADAs, databases or even third party WebServices allows IDboxRT customers to contextualize the information, implement mathematical models, combining all this data, and analyze the results to improve decision making in real time.

In short, from the IDboxRT team, we are sure that the implementation of IoT initiatives in the industrial field will undoubtedly bring substantial improvements both in terms of control and process optimization, as long as we focus on the value that each piece of data can bring to the heart of any initiative: an idea.

BIG DATA and OPERATIONAL INTELLIGENCE: a connection for life

The data generated by the machine makes Big Data analysis really interesting. Among other things, they allow you to improve the user experience, increase IT stability, detect security threats and even analyze customer behavior. But for that, the information must first be found and reviewed.

What is operational intelligence (OI)?

OI can be defined as a form of real-time business analysis that offers actionable visibility and an insight and management of all business operations.

The data produced by real-time operational intelligence enables operators to understand the performance of distributed infrastructure, make predictions, improve efficiency, and even prevent disasters. This gives a greater ability to make the right operational decisions and engage important stakeholders. Importantly, IO software learns from past actions through artificial intelligence (specifically, machine learning) and can therefore improve its own decision-making processes.

Operational intelligence, along with machine-generated data, provides the ability to understand exactly what is happening in individual systems in the IT infrastructure, in real time.

Therefore, modern Big Data platforms for operational intelligence are capable of processing more than 100 terabytes of machine data every day, which then serves as a prerequisite for making informed decisions in different business processes. Product managers can bring applications and services to market faster, managers improve the availability and performance of internal IT solutions, while sales teams have the ability to tailor services and products to customer behavior. The opportunities for business process optimization are endless.

How operational intelligence works

Operational intelligence plays directly with IT itself: A large amount of information is produced there from different IT segments to solve exact problems such as performance. This information generally includes web infrastructure logs, network data, application diagnostics, or cloud service information. Shortly after consolidating this data, it is possible to conduct a cause investigation and react to specific incidents, failures, and other problems. Monitoring mechanisms and alarms allow you to monitor your entire IT infrastructure, including applications, by identifying specific conditions, trends, and complex patterns. With this real-time report of an organization’s “machine rooms”, IT administrators will be able to develop a service-oriented view of their IT environment. This enables on-the-fly reports and data visualizations that provide an overview of events from different perspectives. This includes information about how applications, servers, or devices are connected to mission-critical IT services.

The main characteristics of an Operational Intelligence Software

  • Monitoring of all business processes in real time.
  • Detection of all kinds of situations throughout an operational process in real time.
  • Big Data control and analysis. Our Operational Intelligence Software continuously monitors and analyzes a variety of high-speed, high-volume Big Data sources.
  • Analysis of different situations, trends, the root of the problems.
  • Different users can view the data dashboards in real time.

Conclusion

Applications, sensors, servers and clients constantly generate data. This machine information can be used for user transactions, customer behavior, sensor activity, machine behavior, security threats, fraudulent activity, and other measures. For meaningful analysis and subsequent decision making, special operational intelligence platforms are suitable. They allow you to discover the value of hidden information by collecting, indexing, searching, analyzing and viewing the vast amount of information. It offers companies real-time information about the increasingly digitized business world that can be used for decision-making and corporate governance.