Let’s take a practical and very intuitive example. In supermarkets, a retail sector that has always remained open, even during the toughest lockdowns, cameras combined with sales analysis based on artificial intelligence can help managers to have a clear and real-time picture of the choices of the customer but also on age groups and time preferences, in order to be able to prepare truly “targeted” commercial strategies.

AioT

But truly, the IoT, the artificial intelligence applied to the Internet of Things, is entering an ever wider range of applications that need better data management to achieve maximum efficiency and optimization. Today, through these applications, it is possible, for example, to see where, even in a very large building, there is a water leak or a door that is not closed correctly. It is sufficient that the sensors are calibrated in order not only to detect the alarm but to transmit the data immediately so that it is displayed, perhaps even in 3D, by the management staff within the operating system. It is intuitive how powerful this solution is for data centers, airports, or industries.

Against Covid

Artificial intelligence applied to the IoT can also help companies and institutions to manage that social distancing which, amid the pandemic, has, in many cases, also become a legal obligation. Intelligent cameras with corporate AI can report attendance data on a single platform. Therefore, access to shopping centers, stations, or workplaces is only allowed when it can be done in real safety. Indeed, before the situation becomes critical, it is possible to set alert thresholds and also examine the flow histories to alert customers and prevent them from accessing the shop or supermarket. Particularly not secondary, intelligence makes it possible to make the data provided by the cameras completely anonymous, ensuring that people’s privacy is always protected.

Deep learning

Going well beyond this pandemic, which sooner or later, we all hope, will end, the intelligent analysis of deep learning, to stay with video surveillance, as regards object detection, offer security officers greater awareness of the situation and better possibility of verification, thus allowing immediate response to any threats. It is said, and it is true, that metadata lowers detection times from hours to minutes, if not seconds. 

Beyond Covid

Even specialized and tailor-made solutions for virus containment, such as thermal imaging cameras or mask detection, if they fully exploit artificial intelligence, will be able, in a very near future, to be used in other less “emergency” areas. . Sensors, cameras, network infrastructure, big data, cloud, all the components of artificial intelligence technology, once in the field, can easily be directed towards other functions: the whole heating unit, for example, for fire prevention or for access control of a person in a building. Also because the development of 5G, experts tell us, will allow the IoT to extend from smart home or commercial applications to those at an industrial level. 

Industrial IoT

Industrial IoT, in fact, makes processes efficient, productive, and innovative by enabling an architecture that provides real-time information on operating and business systems. The data is converted into instructions allowing machines to perform specific tasks. The AI-based system takes less time and can run continuously without errors. As a result, production efficiency improves and takes much less time. Of course, the key will always be the flexibility of the devices.  

An interesting market

In essence, it is a market in which it is worth investing. Recent research by Markets and Markets started from the very basics, the chips. The size of the global artificial intelligence market in this sector was $ 7.6 billion in 2020 and is expected to reach $ 57.8 billion by 2026, with a CAGR of 40.1%. The main drivers for the market are increasingly large and complex data, the improvement in computing power, and the growing adoption of deep learning and neural networks. These are those networks that, as the name implies, are modeled based on the functioning of our brain, certainly the most intelligent system that has ever been conceived. One cannot fail to focus on these data and technologies.

Also Read : Safety Installation: Tricks And Basic Principles

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Getting an accurate reading at home can sometimes be challenging. We’ve put together a few tips to help you get the most accurate reading possible when you’re taking your own blood pressure at home.

Avoid Measuring Under Stress/Duress

Stress is something that can cause your blood pressure to rise quickly. Whether you’re angry and irritated or perhaps something stressful has you a bit worked up, it’s best not to test when you’re feeling stressed or under duress as this probably won’t be an accurate reading.

In these cases, you’re sure to have a higher level than your typical numbers.
If you find that you can never find a good time that you aren’t worked up or stressed, it might be time to consider retiring. We hear Florida is quite nice! Ha

Take More Than Once a Day

It’s a good idea to take your blood pressure more than once a day to get accurate readings. This can help to determine if there is something in your day that perhaps triggers a change or whether it’s particularly high at a certain point in your daily routine.

We recommend using a morning approach for the first time. Don’t measure right after you wake up but be sure to measure before you take any medications. Then, you can use the evening time for your next readings. Don’t be afraid to read it 2-3 times at each of these timeframes for an accurate reading.

Quality Equipment

It is important to be sure that you have quality equipment for reading your blood pressure. If your equipment is not reliably accurate, then your readings won’t be either. Medical sites like sensoronics.com have medically-approved equipment for this purpose and many other things as well.

You can have your device checked for accuracy as well. Maybe take it to your doctor with you and check your equipment against their medical equipment to see if they are close and be sure you are using it properly.

Positioning

There are many small things that can add to your blood pressure. Even sitting wrong can make a difference. Here are some vital points for positioning that will help you get an accurate reading of your blood pressure as well.

• Do not take your blood pressure with a full bladder
• Try to avoid caffeine, alcohol, food, and tobacco within 30 minutes of taking a reading
• Don’t chat right before or during taking your blood pressure
• Use the same arm every time. Try to elevate that arm to a level that is similar in height to your heart at the time of the reading
• Always place a blood pressure cuff on your bare skin or only over light clothing layers

These are simple things you can do and each of them will make a difference in your reading to help you get a more accurate blood pressure reading at home.

Also read : How The Google Smart Speakers Compare To Each Other

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Have promoted a frame of predictive learning, which is a prediction based on data (experience) that integrates sensation and behavior and correction in real-time. He gave a lecture on the concept of “experience-based robotics” based on work and research cases with companies.

A System That Learns And Adapts In The Real World

The results obtained by deep learning have come to be seen in various forms. Many of them are capable of smoothly generating and recognizing images, videos, and sounds. The result leads to recognition of natural language and is being utilized in the dialogue between machines and humans.

However, most of the satisfactory performance is achieved by connecting a computer such as a PC or a cloud to a network. In fact, there are few cases where robots utilize deep learning in a stand-alone state. Still, it is quite difficult for robots to achieve the same intelligence as humans. “It’s not so easy to connect and transfer between the cyber and physical worlds. I’ve always been aware of where those gaps are,” Ogata said. He points out that “thinking about a system that learns and adapts in the real world, not just deep learning, may be an opportunity to think about the next AI (artificial intelligence).”

Currently, image recognition is becoming widely used as a function of robots that utilize deep learning. Image recognition technology is used for the degree of damage to objects and quality inspection. However, the difficulty in further evolving robot development is to incorporate the measurement results of sensors in the physical world into the model.

Therefore, a method of interpreting the sensor value and directly connecting it to the action without using a model was considered. A reward value is prepared for the difference between the robot’s sense (sensor value) and the action taken based on it. 

Reinforcement learning to learn higher strategies that give higher rewards by giving higher rewards to well-resulting sensory and behavioral combinations is currently the focus of attention in the robot industry. There is. However, it is quite difficult to create a reward function that is the basis for judging “good” or “bad”, and the number of learnings is tens of thousands to hundreds of thousands, which is quite large.

Since it is difficult to perform this enormous number of learnings on an actual machine, simulations will be used, but evaluation of the analytical model created from this simulation is also an issue. For Go and Shogi, optimization can be done by setting the reward function, but for robots that work in the real world, it is difficult. Basically, when trying to predict, it fails, so it is necessary to first learn the result of the failed action and then change the internal state that generates the action.

Also Read : 6 ways To Take Screenshots Of Your Windows 10 Computer

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Powerful Internet access and computer algorithms have enabled machines to make a leap of progress in understanding the human voice and video information, and are gradually moving towards true artificial intelligence. AI (Artificial Intelligence), is artificial intelligence products that can realize automatic responses far away from us? How to keep them constantly updating and upgrading themselves but still keeping them within the controllable range of human beings?

This problem brings general worries and anxiety to people. “I think the development of artificial intelligence will eventually lead to the extinction of the human race,” physicist Stephen Hawking gave this view in an interview with the BBC. Elon Musk, the founder of Tesla, called AI “the biggest potential threat to mankind.” Bill Gates, former president of Microsoft, expressed similar concerns.

How much worry is necessary? How urgent is the problem? We have gathered a number of experts in the fields of industry, scientific research, and policy decision-making to assess the development risks of artificial intelligence. Participating in this topic discussion included one of the founders of Skype and a think tank member of the Institute of Potential Risks for Human Future Development-Jaan Tallinn, and Guruduth S. Banavar, an expert in charge of computer cognition research at IBM’s Watson Institute for Supercomputers. Professor of the Department of Computer Science at the University of Padua, the Radcliffe Institute for Advanced Study of Harvard University, and the president of the International Association for Artificial Intelligence Research-Francesca Ross.

The following is the edited content of the expert’s conversation.

What Is The Danger?

What Threats Does Artificial Intelligence Pose To Mankind?

Influenced by science fiction and movies, the threat posed by artificial intelligence is mainly the conflict between humans and machines. This view is actually wrong. Artificial intelligence can solve problems better than humans in certain areas, such as big data screening. However, in some areas where humans are good at, machines perform very badly. Such as common sense reasoning, asking wonderful questions, and “jumping out” to think about questions. The combination of humans and machines is the foundation of our computer cognitive ability and a revolutionary idea for solving complex problems in various fields.

Artificial intelligence-based systems have provided convenience to our lives in many ways: stock automatic trading systems, automatic flight control systems, industrial flow robots, error detection, and search engines. In the past 5-10 years, Computer algorithms and advanced computer architecture have allowed us to develop many new applications.

However, it is necessary to realize that computer algorithms have been applied to the extreme. To achieve greater progress, you need to introduce more complex symbol systems-this is a very high requirement. Today, our neuroscience and cognitive science researches have only scratched the surface for the study of human intelligence.

My personal opinion is that artificial intelligence machines that can reach the human level and realize general perception and speculation are just a topic of entertainment.

Today’s artificial intelligence is unlikely to pose a threat to mankind. If we want to discuss the long-term impact of artificial intelligence, (that is, when artificial intelligence can perform strategy, science, and artificial intelligence research better than humans), we must involve the issue of controlling super intelligence.

What Is The Problem Of Super-Intelligent control?

The most advanced robots now also have an “off button” that allows humans to achieve complete control. However, the prerequisite for the “shutdown button” to work is that it is outside the robot’s work area. For example, a computer that can play chess is limited to playing games with people, and it does not perceive that its human opponent can unplug its power to terminate the game.

However, super-intelligent machines, through intentional or unintentional programming, can fully understand the surrounding world and predict the consequences of someone who can press their “shutdown button”, and it is difficult for humans to control it.

How Serious Is This Problem?

At the moment this is only theoretical speculation. But it needs to be carefully recognized that super-intelligent machines may only be controlled by the laws of physics and programs set by people for early intelligent robots.

The early programs were designed based on our very limited knowledge of physics. Imagine that if we are faced with an intelligent robot and the instruction we give is to “create a greater future for mankind”, we had better be very sure of how it will react.

In many specific fields, the performance of artificial intelligence has surpassed that of humans, including some fields involving precise judgment. At present, artificial intelligence does not threaten humans, but humans have been affected by machine judgments, such as online automated trading systems, health check systems, and unmanned vehicles, and unmanned weapons that will soon be popularized.

We need to clearly understand and analyze the potential threats of artificial intelligence in specific fields, not only to make them work, but also to ensure that they can be safe, friendly, and operate in accordance with human values. This is not a simple subject, because even humans cannot act in accordance with the principles set by themselves most of the time.

Impact on daily life

What kind Of Threats Will Artificial Intelligence Bring To Mankind In Specific Fields?

For example, in automated trading systems, a wrong decision made by a machine will cause economic losses to many people. The mistakes of driver less cars will also threaten the safety of human life.

How Should We Treat These Risks?

Any risk has two sides: the risk of doing it and the risk of not doing it. We have already made many wrong decisions based on incomplete information and unprofessional professionals, resulting in thousands of deaths, millions of dollars in losses, and slow development in core areas such as medical care. Based on the application experience of IBM Watson supercomputers in many fields, I believe that in specific fields, artificial intelligence can effectively reduce risks.

However, I have a cautious view of the field of comprehensive artificial intelligence. I think we have always underestimated the complexity of this issue. We have too many unknowns.

What Measures Does IBM Take To Reduce The Risks Of Artificial Intelligence Technology?

IBM’s computer cognition system, like other modern computer systems, is based on cloud computing structure, algorithms, and large amounts of data. In order to prevent violations, the operation of these systems can be recorded, tracked, and reviewed. These cognitive systems do not operate autonomously, so their instructions, data, and structure require us to take certain protective measures to prevent man-made external attacks. Anyone who accesses and updates the system is controllable.

We mainly protect data through complex encryption and digital signatures, protect computing code through vulnerability scanning and other technical means and protect computer structures through isolation and other means.

These policies to support the safe operation of artificial intelligence are designed based on an in-depth analysis of risks. These policies need to be appointed by security and transaction, and the committees that manage sales and public safety (SEC), the Food and Drug Administration (FDA), and the National Institute of Standards and Technology (NIST) are the institutions responsible for setting safety standards in their respective fields. Review.

The Watson Supercomputer Is Helping Doctors Solve Medical Problems.

Can it be responsible for the medical injuries caused by its own mistakes?

The Watson supercomputer will not give a diagnostic opinion. It provides a variety of treatment suggestions to doctors by processing large amounts of patient medical data. The doctor will consider Watson’s recommendations and comprehensively analyze other factors to make a final treatment judgment.

Doctors are also making mistakes all the time, mainly because they cannot fully grasp all the information about a certain disease. A system like Watson Computer can help them reduce mistakes.

There was a study comparing doctors and medical automatic diagnosis systems. The conclusion is that most doctors lost to computers.

I think it is very beneficial for Watson Computer to provide more comprehensive medical advice. I very much hope that it will have the opportunity to diagnose me.

Impact On Humans 

Some Experts Believe That Artificial Intelligence Has Robbed Some Of Human Jobs. Do You Agree?

Technological progress does make some jobs disappear. An Uber driver once excitedly explained to me how he entered the destination on the tablet to get the itinerary. I told him that in a few years, it might be these small technological objects that brought me to my destination. The driver said happily that he would be more trouble-free, just sit in the driver’s seat and enjoy it. Sitting in the back row, I couldn’t help shaking my head. In my opinion, the biggest impact of driver less cars on mankind is not convenience, but lost jobs.

In the long run, in addition to work, we should also imagine what else our society can revolve around.

Throughout history, we have been building tools to help us accomplish things we couldn’t do. Each generation of tools will trigger our thinking about nature and working methods. Productivity increased, jobs were redefined, new occupations were born, and some occupations disappeared. The computer cognition system has expanded human thinking ability and has a stronger potential for substitution.

The key to the problem is that an organization should be established to quickly train professionals so that they can develop computer cognitive systems as assistants to assist them in their respective work. These skills can enhance human professionalism and set a new standard for “experts”.

How Should We Prepare For The Artificial Intelligence Society?

There is a lot of uncertainty about when full artificial intelligence will be realized or even if it can be realized. (Although as a physicist, I think everything is possible!) But uncertainty is not an excuse for not thinking about control issues. For the issue of how to control, targeted research has just begun, and it may take decades to produce results.

I believe that we can completely minimize the adverse effects of artificial intelligence applied in specific fields on humans. We need to set human value standards for machines, set work principles and priorities, such as conflict resolution capabilities consistent with humans. The completion of the artificial intelligence design work in a specific field can prepare for the design of a comprehensive artificial intelligence that does not harm humans.

In the early 1990s, when computers entered the medical field, social activists in many countries called for the protection of patients’ rights. Ten years later, the medical information confidentiality agreement was born. Similarly, artificial intelligence in specific fields is also facing a serious problem, which rights should not be violated, and what responsibilities should be borne after infringement?

Selling ordinary cars now has to pass a series of safety tests, and selling driver less cars in the future will also require new safety test standards. What needs to be carefully tested is not only the car operating procedures but also the emergency judgment procedures designed on the basis of human ethics and moral principles.

What are the rights of drivers, passengers, and pedestrians in the world of driver less cars? Can consumers not provide all the information to investment advisors and smart assistants? Who should be responsible for investment advice? Is it an investment consultant, an investment service organizer, an intelligent assistant designer, or a data custodian? There are still many problems that human society with intelligent machines will face and solve in the future.

Also Read : The Future Of Customer Experience With Artificial Intelligence

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Much has happened since then, and throughout the last decade, we have seen interesting advances in this world of wireless networks. One of them, perhaps the most striking, is the LiFi (Light Fidelity), a technology with which light can be much more than light. In this text, we are going to know the origins of LiFi, how it works, its current state, advantages and limitations.

What Is LiFi?

Simply put, LiFi is visible light or VLC (Visible Light Communication) data transmission system. We first heard of it in July 2011 when Harald Hass, a professor at the University of Edinburgh, coined the term during a TED talk.

The principles of this technology are based on altering the frequency of visible light between 400 and 800 THz. LED bulbs are used that flicker at such a speed that it is imperceptible to the human eye, but yes to a photoreceptor that must be connected to the device. It is the equivalent of connecting a WiFi antenna to a desktop computer, and only instead of interpreting the WiFi signal, it interprets a light bulb on or off, ones and zeros.

A LiFi system uses an LED bulb that turns on and off at such a speed that it is not noticeable to the human eye.

An encoder is attached to the luminaire. The Internet signal reaches the encoder, and the light bulb turns on or off to transmit the data. The photoreceptor is placed in an area where the light reaches, interprets this data and allows the connection. It has also been tested with infrared rays, which allowed a download speed of 42.8 Gbps to be achieved, and 224 Gbps has been achieved in laboratories. 

Advantages Of LiFi

The advantages of LiFi are not few, but we can summarize them in three: speed, interference and security. It is not without disadvantages either, but we will address them in the next section. Let’s start with speed.

We have already seen that the speed that LiFi systems can achieve is not low. The first test showed 10 Mbps, and it was expected that the maximum speed to be achieved with this technology would be 500 Mbps. It is obvious that it is not. After leaving the laboratories (where a speed of 224 Gbps was achieved), the LiFi achieved a speed of 1 Gbps. Now we have fibres of 600 Mbps and up to 1 Gbps, but at that time we were talking about 100 times the average speed of WiFi.

Later, Joanne Oh, from the University of Eindhoven, placed a series of antennas transmitting infrared rays in a laboratory, which allowed her to achieve 42.8 Gbps at a distance of 2.5 meters. The waves were 1,500 nanometers long, making them imperceptible to the human eye. In addition, several antennas with different wavelengths and angles could be placed to avoid possible interference.

The electromagnetic spectrum is very wide, which works in favour of LiFi technology when it comes to reducing interference.

Advantages of LiFi is that it takes a back seat to the point of being almost superfluous. LiFi technology can use the entire spectrum of visible light. WiFi uses the 2.4 GHz and 5 GHz bands, so all connections are crowded into a reduced bandwidth (that’s why you may notice connection problems when using the 2.4 GHz band on a block of buildings, for example).

LiFi systems have zero radio frequency interference with other devices, so they are solutions to consider for aeroplanes or hospitals.

By using the visible light spectrum, LiFi technology can emit in very many wavelengths, preventing different lights from overlapping each other. As long as the receiver is ready to detect a particular wavelength, there will be no problems with other lights. This can be useful to offer a network connection in offices and cities.

Finally, One of the weaknesses of the LiFi is that the light does not penetrate the walls, and this, in turn, is a great argument. With WiFi technology, someone with bad intentions can intercept the network and violate it, but with LiFi the attacker has to have access to light, he has to be illuminated by the same light as those he wants to violate. It doesn’t seem viable.

Disadvantages Of LiFi

To take advantage of the LiFi network, you must have a photoreceptor connected. If you cover it, you stay offline.

You may have guessed the downsides of the LiFi as you read the pros. They are, mainly, two: you have to be illuminated, and it would take many bulbs to cover an area such as an office or a house. If there is no light, there is no connection.

We said before that the luminaire turns on and off at such speeds that the eye does not perceive it, but the photoreceptor does. But the photoreceptor, of course, has to have direct access to the light. It is enough to cover the photoreceptor with any object to leave it in the dark and, therefore, cut the connection. In a demo, we could see that just bypassing your hand over the sensor the speed drops.

In the area marked with red, a drop in connection speed can be seen, the result of momentarily passing your hand over the photoreceptor.

And that’s just talking about the home, but we have to bear in mind that we also connect from mobile phones. The LiFi connection in mobile phones presents a major problem, and that is that the pockets of the pants are opaque. If you put the mobile in your pocket, backpack, bag or any container that is not transparent, you can still have WiFi, but if you use a LiFi system, the photoreceptor of the mobile will not see the light and, therefore, would not have a connection.

On the other hand, when we hire WiFi at home, we want it to reach all rooms, and this is possible thanks to the fact that the signal penetrates walls (although it implies a reduction in power and speed). The light does not. This means that getting a LiFi connection in a home or office would mean putting several bulbs with their respective encoders in all rooms and keeping them on.

One of the main problems of LiFi systems is that if there is no light, there is no connection.

Everything is said, both Hass and several experts believe that by dimming the light a lot to the point that it does not disturb or using infrared, this situation could be solved. That, however, does not mean that what for WiFi is a salvageable obstacle (such as walls), for light is an element that supposes staying connected.

What state Is The LiFi In Right Now?

Beyond laboratory testing, LiFi technology is still far from reaching users’ homes. For the moment, LiFi stays in certain use cases, mainly companies and professional markets. This is the case of the new Signify Trulifi bulbs, presented a few weeks ago. They are capable of reaching 250 Mbps, but they are designed for places such as hospitals or airports.

Since LiFi technology does not have radio frequency interference, some airlines such as Air France have shown interest and presented at Le Bourget a mock-up of the cabin with LiFi power, their program to offer such connectivity in flight. Among the advantages mentioned, the increase in speed and the reduction of onboard wiring stand out.

The same occurs in the AAL X AAL project, of the VDA Group in collaboration with Solari Spa and the University of Udine. The idea of ​​this project is to bring the LiFi connection to the health sector, since “it does not produce electromagnetic pollution, which has great problematic implications in machinery such as IMR scanners.” This project is underway at the Oncological Reference Center (CRO) in Aviano, Italy.

At the moment, LiFi technology is intended for business and professional projects, not for the end consumer.

It has also been tested in a simulated attack on the metro network. It was starred by Verizon, Nokia and Aegex Technologies, which used LiFi technology to maintain two-way communication with a control centre. BT Defense, a UK intelligence and military customer infrastructure provider, also deployed LiFi at its Adastral Park facility to connect 3,700 employees.

Pure LiFi, one of the pioneering companies in this field, has developed the LiFi OFE, a LiFi sensor for mobiles with which speeds of up to 1 Gbps can be achieved. However, it still has the same problem as photoreceptors for computers and luminaires: if there is no light, there is no network.

As we can see, they are all niche programs for professional sectors or projects in development. LiFi technology still has a long way to go to reach the end consumer, although it is advancing slowly but surely.

Also Read : Artificial Intelligence And Autonomous Cars. A real Threat To Humans?

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Although the use of artificial intelligence has grown by leaps and bounds in the financial sector, there is still a long way to go. One of the robotics solutions with the highest potential in the industry is the use of robots in process automation, also known as Robotic Process Automation (RPA).

Unlike other banking technologies, RPA is not artificial intelligence but relies on it for the automation of business processes, mainly transactional, based on specific rules. It is, in a nutshell, software that learns from a user and helps him perform simple tasks.

Characteristics Of Robotic Process Automation

According to the Robotics Process Automation Advisory Financial Sector report published by PwC Mexico, these are the characteristics of RPA:

• It is a technology that allows you to configure “Robots Software” to automate manual or semi-automatic tasks in an integrated way, with the current systems of the organization.
• It is a virtual workforce, which complements the human team of the entities through the simulation of the activities that employees carry out day by day.
• It is a technology that improves productivity through the reallocation of high-value activities to employees.
• It is a workflow-enabled for the interaction between systems and platforms.
• It is a solution for cost reduction and reduction of human or manual errors.

RPA In The Banking Sector

According to the PwC report, “70% of financial institutions have already analyzed, or are analyzing, the implementation of RPA and the impact on their organization. 16% are already in the process of implementation ”.

For market-leading financial institutions, efficiency and effectiveness are a priority. The application of robotics in processes is a way to optimize activities such as payment processing or billing, report creation, data validation and update, data migration between bank applications, and financial claims processing.

“It is probable that in the next 15 years 45%, and maybe up to 75% of the outsourced work existing within the financial services sector will be carried out by robots, or to be more precise, by a Robotic Process Automation (ARP ) ”

Cliff Justice, Advisory Director of KPMG LLP.

Success Stories Of Robotic Process Automation

1. Bancolombia: Financial Advice

Through “Invesbot,” the bank offers its clients the opportunity to manage their investment portfolios better. The robot provides real-time information about the portfolio’s performance and can advise on making changes to it, taking into account market conditions.

For Bancolombia, the implementation of this roboadviser represents the great potential to expand its customer base and offer added value to its digital customers. “The idea is that the client does not have a higher cost for advisory services,” said Juan Felipe Giraldo, president of Bancolombia Securities. “We see this more as a path to growth, rather than something that allows us to reduce the number of financial advisors,” he added.

2.Kryon Systems: Claims Processing

The use of the most widespread robotics in banking is related to customer service processes, particularly in the handling of claims. A successful example of the implementation of RPA solutions in this area is Kryon Systems, an RPA solution provider based in Tel Aviv, which has worked with different financial institutions in the region.

Francine Haliva, senior vice president of the company, said in an interview with Finance TNT, that the automation of claims payments allowed a reduction in response time and a decrease in human errors. “Once they automated the process with the RPA platform, this process began to be carried out in less than two hours, automatically, instead of the four days that workers normally took,” he said.

3.Bank Of New York Mellon: Fraud Prevention

One of the most common problems faced by users in the digital age is identity theft. Cybercrime is increasingly sophisticated, which requires banks to implement more effective cybersecurity solutions.

Financial institutions such as Bank of New York Mellon have already bet on the automation of robotic processes to identify fraudulent transactions without generating friction in the user experience.

Through RPA solutions, the bank monitors the use of credit cards, storing profiles and usage patterns that include changes for seasons such as Christmas or holidays. Subsequently, through machine learning algorithms, it performs real-time analysis to identify anomalies in the use of credit cards and avoid unauthorized transactions.

4.KeyBank: Invoices And Accounts Payable

This bank, based in Cleveland, United States, has incorporated the RPA principles to offer a comprehensive solution that optimizes electronic billing based on payment cycle management. RPA technology has eliminated the need for employees to perform repetitive manual tasks and, thanks to machine learning capabilities, they have improved the user experience from start to finish.

“Banks have traditionally focused on payment execution,” Matt Miller, head of products and innovation at KeyBank for commercial business payments, told Finance TNT. According to Miller, thanks to the RPA, the bank no longer needs to transform the information into a standard format for consolidation. Additionally, they have added advanced controls, such as the online payment cycle report, to ensure that no payment date is passed.

The transformative potential of PRA and cognitive automation is unprecedented. It is no longer about whether or not financial institutions should adopt these technologies, but when they will. Those who resist or take a long time to implement them may become irrelevant in an increasingly competitive market

Also Read : Robot plays “Super Mario Bros.” With a Controller

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# 1 Smart Home Devices Will Skyrocket In Popularity

Even those who ruled out smart home technology as unrealistic toys for lazy young people find it increasingly difficult to resist the charms of smart home devices with IoT.

These devices will be top-rated in 2019 and the coming years, as they become highly intuitive and innovative and extend not only to the comfort of home automation but also to the safety of the home and the safety of your family.

Dryers that warn you when lint buildup is too high can prevent a fire. That is the kind of smart home functionality that will see a great adoption in 2019 and in the coming years.

Another great driver of the intelligent adoption of IoT development is the need to save energy. Smart thermostats and smart lighting help conserve energy and reduce bills, which will be another great reason why more and more people turn to IoT devices in 2019 and beyond.

# 2 Edge Computing Will Be Necessary For Cloud Computing

This will be a change to be careful. For a long time, IoT devices have relied on the cloud to store their data. However, IoT development and developers and manufacturers are beginning to realize the utility of storing, calculating, and analyzing data to the limit.

This means that, instead of sending all the data from the IoT device to the cloud, the data is first transferred to a local device located closer to the IoT device or at the edge of the network.

This local storage device can sort, filter, and calculate the data and then send all or only part of the data to the cloud, reducing traffic to the network.

Known as “edge computing,” this approach has several advantages. First, it helps to manage better the large amount of data that each device sends. Reduced dependence on the cloud allows applications to run faster and reduce latency.

By being able to collect and process data locally, the IoT application consumes less bandwidth and works even when cloud connectivity is affected. Due to these positive aspects, cutting-edge computing will see innovation and wide adoption in IoT, both consumer and industrial. Reduced participation in the cloud facilitates better security practices and reduces connectivity costs. 2020 will see more use of next-generation IT in IoT.

# 3 Medical Care Will See Greater Adoption Of IoT

One of the most important applications of IoT is undoubtedly in the field of medical care, and next year we will see how medical care really adopts IoT skills.

According to Frost and Sullivan, the Internet of medical supplies could be expected to grow at a compound annual growth rate of 26.2% and reach $ 72 billion by 2021.

Devices such as sensors, portable devices, medical equipment, health monitors, and a variety of other medical devices are configured to connect to IoT.

From health service providers to the general population, everyone knows IoT development better than before, and this is intended to increase the adoption of IoT in the world of medicine forever.

Mobile health applications and virtual assistants to monitor the health of the patient at home, portable devices and intelligent implants that communicate the parameters of the patient, smart cars that follow the vital signs of the patient in transit and a series of other connected smart devices configure the remodeling of the medical world.

# 4. IoT Security Will Be A Higher Priority

As adoption increases, more and more devices connect to the Internet of things. The network expands, data volumes increase, and there is more information at risk.

A bigger boost to IoT security should accompany the increased use of IoT. With vital data floating in the cloud, patient health and home security are at risk, and the development of mobile applications based on IoT will have to be safer than ever.

As of now, not all IoT devices are equipped with the type of security features that laptops and computers are equipped with. In the next year, that will have to change.

Machine-to-machine authentication will overlap, biometric logins will become the norm, and artificial intelligence, machine learning, and big data techniques will be used to identify and frustrate data breaches.

# 5. AI And Big Data

With billions of consumer and industrial devices connected to IoT and data transmission, the amount of data that must be processed and analyzed will grow exponentially.

The idea is not only to collect data but also to extract actionable information from this data and that some artificial engineering and big data techniques will be needed to process all that information.

A convergence of AI, IoT, and Big Data will lead to a wave of new generation applications and advances. In fact, it can be challenging to see any of these in isolation.

# 6. Blockchain For IoT Security

Many financial and government institutions, entrepreneurs, consumers, and industrialists will be decentralized, autonomous, and quite intelligent. Some of the new companies are seen building their tangled territory in IOTA (IOTA is a distributed ledger specially designed to register and execute transactions between devices in the IoT ecosystem) to develop modules and other components for companies without the cost of SaaS & Cloud.

You should prepare to see the centralized and monolithic computer models that are separated in the jobs and microservices that will be distributed to the decentralized machines and devices. Someday, IoT will penetrate the health, government, transactions, finance, and other disciplines that people these days cannot think about. This type of IoT technology trend will create significant effective differences.

# 7. Better Data Analysis

The next few years will surprise us with the most significant trend that will occur between the IoT and the connected world. Now, how the world and IoT combine with AI to become a decision-making assistant for all people and businesses, and that’s all we expect.

AI is a machine learning system that can quickly identify trends. IoT Trends will bring better data analysis and make it easier to protect them. In addition to this, it collects information from essential data to make better decisions for our lives. It seems that the integration of IoT is less reflexive, intelligent, and is also self-learning.

# 8. Smart Cities To Become The Mainstream

In the past, we have seen that states implemented more technologies and sensors to take advantage of accessible data collection tools. Soon, we will see the IoT Trends, where cities with a vision of the future will invest in pioneering exchanges of data that will allow access and fusion of data between public and private organizations together with citizens.

We will have the opportunity to see the conversion of the thought of several smarter cities soon. The integration of IoT with receptive cities will unlock sustainable development, decrease traffic congestion, and improve security.

# 9. Customization Of Retail Experience

IoT makes retail supply chain management even more efficient today. With the help of sensors and other smart beacon techniques, adapting the shopping experience has become much more comfortable, and people can do it more accurately.

According to the new changes, IoT Trends of the following years will personalize your commercial presence. You can imagine receiving a discount notification on a product generally purchased at your favorite store, but can you also imagine an internal map of your favorite store that takes you to the exact product you want?

This latest technological trend of IoT will ensure better integration of the personalized retail experience that can ultimately bring a new era of shopping.

# 10. Predictive Maintenance Powered By IoT

In 2009 and beyond, the home will inform homeowners about plumbing leaks, appliance failures, electrical problems so that homeowners can avoid the home maintenance disaster. More of the characteristics of the sensors in factories, airplanes, and automobiles that can be achieved today will soon enter your home with the help of all these IoT Trends.

In response to these predictive IoT skills, we will see home care offers as a contractor service. No matter if you are at home or not, they will take action immediately when a problem is perceived.

Currently, several home insurance companies already know the changing nature of smart sensors and other connected devices that significantly affect the Internet of things trends. Sensors found in cars, such as national insurers, will be able to reduce risk and other payments during the supply of lower rates to consumers who will install proactive monitoring systems to avoid damage.

# 11. Software As A Service Becomes The Norm

If we talk about the technological trends of IoT, software as a service is considered one of the hot topics for the estimated markets. With the help of the low cost of entry, SaaS is quickly reaching the list of the best for being also the favorite firm in the IT gaming sector, and soon we will have the opportunity to see an excellent defense of the company. Software as a service among all these technological trends of IoT will improve people’s lives better than ever.

# 12. Creating A Unified Framework For Integration

The lack of a unified IoT framework is something that the Internet of things has faced as a challenge in cooperating with industries. Several companies do not have a shared central platform. All the Internet of the things trends I mentioned before, including a unified framework, since this is the only way to keep industries safe.

Blockchain will help accelerate the adoption process with the help of improving and developing mobile or web applications. These are the applications that have high-performance thresholds, and this process will also help maintain the intensive data process that is generally required.

# 13. Energy And Resource Management

Energy management depends mostly on the acquisition of a better understanding of consumption. Most of the time, the products that can fit in the electrical panels reach the market, and these can monitor very well the energy consumption of the home. All these technological trends of IoT can be easily integrated into resource management, which will make people’s lives easier and more comfortable.

Automatic notifications can also be added to send information with smartphones when the power threshold is exceeded. Other features such as sprinkler control, indoor temperature management, etc. can also be added.

# 14. Greater Consumer Adoption

In the next ten years or so, you will see a significant change in the Internet of things when the consumer-based IoT change occurs, as well as Lily Robotics market failures. The growth of the consumer-based Internet of things financing will decrease, and the future will be the year for the industrial IoT platform and infrastructure. These Internet of things trends will require time to evolve.

Companies like BetterView, Veniam, and Swift Navigation are based on Industrial-IoT will see the construction of the Internet of Things architecture, solve difficulties in insurance, agriculture, transport, or telecommunications, and will see a vivid reduction in capital expenditures.

In Conclusion:

These are some of the trends that will dominate the IoT application development ecosystem in the new year. Both consumer and industrial IoT will see significant advances and a series of connected devices, but the whims of some people know about technology will become standard.

Of course, new technologies will emerge that will make IoT more intuitive and easy to use. Still, to a large extent, manufacturers will have to work harder to protect their connected devices, since the risk to the data will also increase. Amid all these trends and predictions, the future is definitely promising and certainly worth waiting for.

If you have any IoT application development requirements, do not hesitate to contact us. We are a leading application development company in Dubai that offers a mobile application based on IoT full of functions according to your choices.

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