Energy Management

Energy management is a vital component of creating sustainable smart cities. IoT solutions allow city managers to monitor and control energy production, consumption, and distribution in real time. For instance, smart grids can balance supply and demand efficiently, while IoT-connected solar panels adapt to changing weather patterns to maximize energy production.

IoT: The Engine of Smart Cities

IoT technologies involve the interconnectivity of numerous devices and sensors, allowing them to communicate with each other and function collectively. These smart-systems seek to automate and optimize different aspects of a city, such as transportation, utilities, and public services, making it more efficient and responsive to citizens’ needs.

Smart Homes

In this era of developing smarter cities, ensuring optimal quality of life and levels of comfort for residents is given high importance. Smart living solutions like an adjustable mattress bring innovative technological advancements into our homes and bedrooms, making them more suited for the urban developed environment.

Public Safety and Security

When it comes to urban safety and security, IoT solutions can provide city officials with more effective tools for monitoring and responding to incidents. Examples include smart surveillance systems with facial recognition capabilities and IoT-connected emergency response systems that optimize response times during emergencies.

Waste and Water Management

IoT technology is revolutionizing urban waste and water management, one of the most pressing challenges facing cities today. Smart waste collection systems use sensors and data analysis to optimize collection routes and reduce fuel consumption. IoT-powered water management systems can monitor usage, predict demand surges, detect leaks, and minimize water waste at the city-wide level.

E-Government Services

IoT allows cities to offer seamless, connected e-government services to their residents. Citizens can access personalized services through their devices, enabling them to pay bills, access information, or file permits quickly and easily. This interconnected approach simplifies interactions between citizens and government, making services more accessible and efficient.

Smart Transportation

The combination of IoT and innovative transportation solutions is revolutionizing urban mobility. Data collected from IoT sensors can help improve traffic signal timings, reduce congestion, and optimize public transportation routes. In addition, real-time traffic monitoring can enable the deployment of autonomous vehicles and the development of smart parking systems that save time, energy, and emissions.

Smart Infrastructure

IoT-enabled infrastructure can detect maintenance needs and prioritize repairs, significantly reducing maintenance costs for cities. For example, smart streetlights can adjust brightness based on pedestrian and vehicular traffic, while connected bridges can monitor structural health to prevent potential accidents.

IoT in Healthcare

A key player in shaping the future of smart cities is the IoT’s integration within the healthcare sector. Smart healthcare systems can offer remote monitoring of patients, intelligent diagnostics, and efficient data management. This not only helps people receive personalized care and advice but also assists in making evidence-based decisions in public health and community planning.

Social Connectivity and Citizen Engagement

IoT technologies can foster greater social connectivity and encourage citizen engagement. For example, social networks can be used to gather data on citizen concerns and needs, which can inform proposals for the city’s future development. Furthermore, IoT sensors can measure air quality, noise pollution, and other environmental factors, allowing citizens to get real-time data about their surroundings and make informed decisions about their lifestyle choices.

Addressing Privacy Concerns

While the benefits of smart cities are vast, there are valid concerns about privacy and data security. The widespread collection of data by IoT devices should be carefully managed and monitored to ensure that citizens’ privacy is respected and protected. It is crucial to have clear data protection policies in place, which encompass both legal frameworks and technological solutions, to safeguard the personal information of residents.

Conclusion

The integration of IoT technologies into urban environments is unlocking the potential of smart cities, paving the way for sustainable, efficient, and connected urban life. As we continue exploring the benefits of IoT-powered solutions, the possibilities for transforming our cities and improving the quality of life for their residents seem boundless. As long as we ensure responsible use and proper management of the data collected, the future of smart cities is full of promise and potential.

The post The Potential of Smart Cities: IoT Solutions for Urban Life appeared first on TechReviewsCorner.

Hold Regular Meetings

In the day to day of a company, the most common thing is that we communicate with other colleagues or with our managers through written messages. However, this is not enough when seeking to strengthen internal communication since it is necessary to interact in person to get to know others. The objective of these assemblies is to share information jointly so that everyone can be updated and contribute their opinions, promote team cohesion and listen to the considerations of the staff.

Deliver a Welcome Manual

When a person joins to work in an organization, it is essential to transmit all relevant aspects of the company, such as, for example, what is the company’s mission, vision and values, its organization chart, its policy, the rules to follow and specific basic procedures. By carrying out this action, the new worker will obtain valuable information for their daily work. It will be easier for them to familiarize themselves with the environment, and they will feel more involved when they understand how they can add value.

If the company is going to prepare a welcome manual for the first time, it would be convenient if it were given to the recruits and the rest of the staff. In this way, your understanding of how the company works will increase.

Be Transparent

How those responsible for departments and projects communicate with their teams must be clear and direct. This will help speed up processes and increase the confidence that workers deposit with their superiors. In this sense, it is essential to communicate any news that may have arisen, whether negative or positive.

Send Newsletters And Internal Circulars.

An effective way of transmitting current news related to the company to the workforce is to send informative emails and documents that collect relevant information for workers.

The sending of internal newsletters is usually carried out every month, while, in general, the circulars are sent weekly. In the first case, the information shared usually includes content that is not related to the day-to-day running of the company, such as blog posts, success stories, employee interviews and events; In the second case, the usual thing is to incorporate those issues such as, for example, employee vacations, new hires and extraordinary situations that do influence daily operations. By making this type of mailing, workers will be able to have this news in writing, accessing it at any time.

Organize Events

An excellent way to encourage rapprochement and coexistence between the different employees of a company is by organizing parties, meals, celebrations or any other similar event. By meeting workers outside the work environment, they will feel freer to share and communicate in a relaxed way, which will help strengthen ties between staff members.

Also Read: Communication Strategies – Definition, Types And Real Examples

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Today when it comes time to contract the Internet for companies, the great unknown that still raises many headaches arises the differences between ADSL and Fiber Optic.

In this article, we will solve all your doubts about it so that you can make the best decision according to your needs: Fiber Optic or ADSL?

Differences Between ADSL And Fiber Optics

What advantages does Fiber Optics offer over ADSL? What are the differences and what advantages do they offer us? We’ll tell you then.

The Big Difference Between ADSL And Fiber Optic – Speed

Before starting to detail and list the differences between these two types of connectivity, it should be noted that the main difference has to do with speed.

ADSL is slower, it covers lower speeds than Fiber, but it has more network coverage. That is, it reaches more homes.

Fiber can reach 600 symmetric megabytes, while ADSL barely exceeds 20 Mb.

In addition, if you contract Fiber Optic, you will be able to connect several devices simultaneously and not notice a drop in speed. On the other hand, with ADSL, you can have a lower speed than the one contracted.

Advantages and Disadvantages of Fiber Optic

In short, fiber optics has become the best Internet solution for companies.

This is the latest and fastest solution, but it is still under development. Its only handicap has to do with coverage since there are still many corners it does not reach.

Although it will not be a problem for a long time, since companies are investing to increase the deployment of Fiber Optic and today, there are many other ways to get a good connection in isolated areas.

On the other hand, with Fiber Optic, the speed you contract is the one you receive, and the price depends on the speed you want to contract.

In addition, it guarantees more excellent stability, avoids annoying network drops for users, is immune to magnetic interference and has a higher level of security than ADSL, thanks to its FTTH ( Fiber To The Home ) installation.

Also Read: The Technologies Behind The Rise Of Robots

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What does this mean for companies? If you are stuck with the traditional approach to security, it is time to restart your security initiative to reflect a limitless computing environment. The IoT is very different from IT, and it is essential to focus on the network and the overall data environment rather than the specific device.

The IoT Is Simply The Next Phase Of IT Security

Nothing could be further from the truth. Connected devices and systems represent a more decentralized approach to computing and cybersecurity. Moving to the IoT requires a substantial conceptual leap for IT teams as they are no longer the buyer or device owner.
The problem is that IT teams are trying to use the same tools and approaches when Fort Knox was founded. You approach a business problem as an IT problem. The IoT is not about laptops and smartphones, and it’s not about protecting user networks. It’s a whole different world that revolves around protecting business processes and data.

Business leaders who understand IoT realize that taking a holistic, data-centric approach rather than making everything more complex can make cybersecurity easier.

IT Should Oversee The Security Of The IoT

Typically, when IT is responsible for the security of the Internet of Things, it uses conventional tools, technologies, and approaches to the task. This “one-size-fits-all” approach often leads to disappointing results. The IoT goes beyond the limits of traditional computer systems. Data resides on various devices inside and outside a company and flows through many other points of contact.

But there is another, sometimes bigger, problem. With IoT spanning teams, departments, and companies, it’s easy to put up with an isolated approach to cybersecurity. In some cases, different groups dealing with security issues can duplicate or even inadvertently use conflicting methods – and ultimately leave an organization unprotected.

Alignment between IT and cybersecurity teams is even more critical in the age of IoT. This requires close collaboration between CIOs, CSOs, and CISOs. You need to analyze, identify all of your resources, and understand how, why, and where data is being used. Only then can you design a framework that is optimized for the IoT. This may require hiring or retraining people with the right skills and expertise.

Traditional Security Tools And Strategies Will Protect Us

The castle-and-moat approach to cybersecurity can actually “undermine” IoT security. While still valuable, malware protection and other traditional tools were not designed for managing data streams across sensors, edge environments, and modern multipurpose devices.

This does not mean that an organization should remove these protections, and it just needs to redesign them and add new features as they become available. This could be, for example, data encryption during transmission or tools for network monitoring that detect when data is particularly at risk. It could also be setting up separate networks for different types of data. Even if someone hacks a device or system, they may not get anything of value.

AI can find IoT devices on a network, including previously hidden devices, ensure they have received critical updates and security patches, and identify other potential problems. Machine learning enables IoT devices to be grouped based on security risks without additional security software and manual processes. This approach allows for risk assessments of when devices function “normally” or “suspiciously” and helps enforce IoT guidelines.

It’s All About Protecting Your Device

The application of conventional IT security thinking to the IoT opens another trap. IoT security requires a broader approach that includes network authentication, connectivity, clouds, and more. “It is time to stop thinking of IoT devices as small PCs. Most of these devices are simple and dumb,” says Utter.

Thousands or tens of thousands of IoT sensors and devices make it impossible to protect everyone in an intelligent business, supply chain, or city. While it’s essential to cover a medical device or car from hacking attacks, many connected sensors and devices have read-only components that cannot be compromised. As a result, enterprise IoT security measures must revolve around more complex relationships between systems and data.

“You really have to start with the basics,” emphasizes Utter. “That means that you have to create a zero trust framework.” In this new order of IoT, the network is the thing – and all sensors, devices, systems, and data have to be viewed holistically. “By classifying data, setting up zones, and creating whitelisted applications and processes, it is possible to identify the right protective devices and tools for the right task.”

This means, for example, that one has to move away from a traditional model in which all sensors and devices are integrated into the same network. Instead, a company can benefit from organizing its systems according to business tasks, data security, and trust levels. It is then necessary to create network nodes, departments, or zones and implement tools and protective devices that meet the security requirements.

Manufacturers’ Safety Precautions Are Critical

The prevailing mentality is that vendors need to build strong safeguards into their products. And if there is a patch, the user has to rush to install it after installing it. Unfortunately, this is a flawed concept in the age of connected devices. That’s not to say that security shouldn’t be built into products. It just isn’t to say that an organization shouldn’t consider the safety of IoT device providers as the primary form of protection.

Because many sensors are just “dumb endpoints” that are replaced and not patched, even when it comes to more complex devices, “most companies use IoT components and never update or patch them.” The problem is that firmware patches and upgrades become a nightmare for thousands of networked devices.

The bottom line? Security on the device becomes much less critical when data and network controls are in place. The IoT requires a broader overarching strategy that spans all device manufacturers. Ultimately, protecting the IoT doesn’t have to be a chore.

Also Read: Internet of Things [IoT] – Simple Gadget or The Start of a Revolution?

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A new acronym has invaded our social networks: “IoT” for “Internet of Things” (Internet of Things) and all its variations (“Connected objects,” “Quantified self,” “Internet of Everything,” “Cloud of Things,” “Industrial IoT“…).

When we talk about the Internet of Things, the examples that immediately come to the general public’s mind are usually refrigerators, televisions, or connected street furniture. The reality is more comprehensive. Today there are a host of more or more minor exotic applications: tires, shoes, skis, tennis rackets, scales, light bulbs, WCs, toothbrushes, showerheads, thermostats, wine cellars, cat litter …

On the business side, the objects in question essentially impact their equipment (energy meters, internet boxes, waste containers, rail infrastructure, advertising panels, etc.) and sometimes on employees and customers themselves via the sensors they embed or host.
Even though the Internet of Things may be seen as just a fad at first glance, it would be a mistake to reduce it to that. It is more like an unavoidable phenomenon for two reasons:

1- The Race To Get to Know Business Customers and The Rise of New Practices Among Specific Individuals

Companies have embarked on a vast process of acquainting their customers with the – a priori virtue – to offer them more suitable offers and products. This customer knowledge certainly requires better use of the available tools (contractual and commercial data, customer journey on the web and social networks, cookies, etc.). Still, it can also be developed thanks to the data generated by connected objects: these are Google’s approaches with the takeover of Nest (manufacturer of connected thermostats) or Axa with its connected bracelets offered to 1,000 policyholders. Individuals are not left out. They increasingly appreciate measuring their parameters (health, water consumption in the shower, number of tooth brushings, etc.) to compare themselves, to improve,

These two trends make the meeting between supply and demand more than probable, with a new logic: “Company exchanges playful and desirable object against valuable data.”

2- The Opportunity For Companies To Better Control Their Costs

Beyond this customer knowledge, companies face another challenge: better control of their resources and expenses thanks to connected objects. This is particularly the case in energy, where the generalization of Smart Meters indeed allows the energy ecosystem to imagine and offer new services and for distributors to better understand their networks in real-time and better plan investments, maintenance, and interventions. This is becoming the main lever for the digital transformation of companies because there are very significant sources of gains there.

Don’t Underestimate The Inherent Threats.

While the Internet of Things represents a significant opportunity, we should not lose sight of the fact that it also includes risks, which must be anticipated.

Threat 1: The Security of Goods and People

Having a real-time view of the activity of the inhabitants of a dwelling… It is the dream of every burglar. Penetrating the piloting bodies of thousands of connected devices is becoming a new El Dorado for hackers. Today, the corresponding object is perceived as a gadget by its holder but as a source of information for a malicious organization: it is therefore naturally through these objects that the next significant cyber-attacks will come.

Threat 2: Increasing Complexity, a Source of Industrial Risks

While the technologies seem sufficiently robust to consider industrial deployments, their complexity, mainly linked to the interoperability of different protocols (Bluetooth, low wifi energy, CPL, 4G, etc.), remains a hard point. Standardization initiatives are in their infancy, and it isn’t easy to know which technology to invest in. 

This complexity creates a real divide for individuals, of course, but even more so for companies that already today have great difficulty in controlling all of their equipment and their interdependence. The IoT will generate a higher degree of complexity (thousands of sensors/actuators speaking different languages, risk breakdowns compared to sound old mechanical systems, etc.). Talented resources in Industrial IoT will quickly be insufficient, which is already seen in major Smart Meters deployment projects from digitogy

Greater Porosity Between Products and Services

In the future, service providers (insurers, energy distributors, etc.) will have to extend their business model to upstream equipment. Conversely, hardware manufacturers will have to raise their services thanks to the data they can benefit from. Business value chains will therefore be profoundly modified. However, it is rare for prominent industrialists to have prepared for this revolution. The winners will be those who have anticipated and put in place – in time – new modes of development in digital codes (partnerships, test & learn, open innovation, etc.) and who will have been able to develop their skills in the technical and underlying security.

Also Read: Strategies For The Adoption Of IIoT In Industries

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It happens that whenever we talk about the Internet of Things, we paint a future full of these solutions, of smart cities in which pedestrians gain ground over vehicles, with smart buildings, and much more. We forget that, on many occasions, IoT solutions will go unnoticed by the majority, as is the case with IIoT, the Industrial Internet of Things.

The IIoT focuses exclusively on industrial applications, such as chain production, manufacturing, or processes in the agri-food industry. In other words, we remove all products for domestic applications from the connected equation and focus on increasing process efficiency, health, and safety.

How can the industry take advantage of this technology? What strategies are the most suitable for its adoption?

IIoT adoption strategies

First of all, a little clarification: IIoT has existed in industries for more than half a century. Since then, industries, factories, and factories have sensors connected to computers, dedicated to collecting data and recording it for analysis. That is the basic principle of the IIoT, and also of the IoT. Today, with other technologies combined and with better sensors, we can go further (and we coined an acronym), but the basis of everything is older.

Consider IIoT at the edge

In the past, adding a single sensor could be cost-prohibitive. The normal thing was to use sensors and actuators in specific areas, related to critical safety equipment, for example. Today, the reduced costs of new technologies allow IIoT to be applied on the periphery, where it was not profitable before.

The IIoT has benefited from low-cost sensors and cost savings of ownership as many of its workloads migrate to the cloud. In addition, it is much easier to analyze the data thanks to machine learning.

Use hidden sensors to reduce costs and control downtime

The low cost of today’s sensors invites them to be used in places that were traditionally supervised by human operators, such as a packaging or assembly line. If a small glitch occurred in those chains that stopped the process for, say, 15 seconds, manually recording that glitch could be a hassle (and not done).

By introducing low-cost sensors that can help monitor these small, almost unnoticed failures, we will gain information that will allow us to optimize those processes. The profitability, in those cases, is enormous given the low investment in components.

Going for the Cloud to reduce equipment ownership costs

Among the many benefits of the cloud is undoubtedly cost savings. We’re not just talking about the initial deployment, but also the cost of infrastructure ownership. In this way, companies can capture IIoT data without the need to employ specialists or invest in expensive on-site equipment.

No need to implement a complete IIoT strategy from the start

As in many cases, a progressive approach is often much more interesting and efficient than tackling a complete transformation in one step.

Also Read: MACHINE LEARNING FOR COMPANIES: ADVANTAGES OF ARTIFICIAL INTELLIGENCE FOR YOUR BUSINESS

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Find Fault

First of all, you should determine where the problem is in your network. To find out whether your router can even establish an Internet connection, it is often enough to take a look at the device: The status LEDs should tell you directly if something is wrong with the connection and then usually flash. Depending on the model of the router, these characters are different – have a look at the manual of the device to decipher the LED signals.

A simple and tried and true method is to restart your router. Some devices have a corresponding button for this, or you can restart it via the browser user interface of your router. Alternatively, pull out the power plug for at least ten seconds. Once you have reconnected the router to the mains, you should wait a while until the device is fully operational again. You can also connect your router to the computer using a LAN cable to find out whether it is a WLAN problem.

These programs can block the internet

It doesn’t seem to be due to the router, but a connection via WLAN is still not possible? Then programs installed on your device could be the cause. If you use a firewall, antivirus software or VPN like privacyonline, you should briefly deactivate the corresponding program for network diagnostics. If the connection succeeds with the services switched off, an update or uninstalling and reinstalling the programs often helps.

Disturbance at the provider

It is possible that the problem has nothing to do with your devices and settings, but there is a fault with the provider. Before you call technical support and land in the queue, it helps to take a look at the websites. Here users can enter when their Internet or telephone connection is currently disrupted. If the messages pile up, the problem is most likely with the provider.

Unfortunately, there is only one piece of advice for this cause: wait. Until your provider has fixed the problem, you can practically do nothing. For very urgent matters, you can use LTE instead of WiFi and set up a mobile hotspot with your smartphone. However, you should have enough data volume available in your tariff for this. With a tariff with unlimited data volume, the time can be bridged well in this way.

Also Read: Does smart TV need a cable box?

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The beginning of cloud computing research is around 2006. In that year, large corporations such as Google or Amazon began to use the term cloud computing. The new term is used to define the new situation in which people access software, files, and data in general through the web more frequently. Instead of using their desktops.

To know more about cloud computing with Amazon, you can refer to the following article.

Cloud Computing, or cloud computing, comprises a series of technological services that are made available to any user. From anywhere. Virtually unlimited computing and storage power. Allowing to pay only for the use made of the service.

This new approach did not imply the creation of new technologies, but rather makes use of technologies such as the following:

• Virtualization
• Physical storage.
• Storage on the web.
• Data centers.
• Software over service (Saas).
• Web applications.
• Web operating systems.

The company responsible for the servers will be in charge of their maintenance, of preserving the databases. And solve all the associated aspects: connectivity, monitoring, growth, security, updates, etc.

Also Read: What Is Mean By Edge Computing? Is Edge Computing More Secure Than Cloud Computing?

Cloud Computing Actors

The actors or participants in cloud computing are very diverse. The main players who benefit from the advantages of cloud computing are:

• Suppliers or vendors: they are those who provide the applications and the technology, infrastructure, platforms, and information necessary to carry them out. For example Amazon AWS, Microsoft Azure, or Google Cloud.
• Supplier Partners: Bring suppliers and customers into contact. Your basic task is to create services for the cloud and offer and support them to customers. For example

1. Cisco devices: switches, routers, cabling, etc.
2. HP or IBM servers.
3. Antivirus applications, antimalware software.

• Business leaders: they are in charge of evaluating cloud services to contract and implement them in their organizations.
• End-users: are those who finally use the services offered through the cloud, either for free or by making some type of payment (periodic or punctual).

Examples Of The Use Of Services

Here are some examples of the use of cloud computing services as tools to change habits and models of use of information technologies:

• Google:  This large corporation has been including more and more complementary applications to its search engine. An example is found in Google Apps. Where Google offers services as varied as email, calendar, calendar, or office software through the cloud. These services are offered for free in their most basic version. Official Google Drive page.
• Azure Platform:  It is an application development platform through the cloud developed by Microsoft. It offers a set of functionalities as varied as:

                              Windows Azure:  Computing service for applications.

                              Windows Azure Storage:  Non-relational data storage.

                              SQL Azure:  Relational database in the cloud.

                              Windows Azure AppFabric:  Access control service 

• Amazon Web Services: It began by offering virtual storage and has gone on to create its own AWS (Amazon Web Services) infrastructure through which it offers global computing, database, analysis, application, and deployment services. All these services help companies to manage their information faster and at a lower cost in information technology. AWS official page.

In addition to the general advantages, in the business world, the advantages of cloud computing can be divided into five main groups: operational, economic, for the personnel, for the consumer, and for the provider.

Also Read: What is Business Intelligence & Cloud Computing

Operational Benefits

Operational benefits are those that are produced by the way the company operates, its action protocols, and the processes they carry out.

The main advantages of operational cloud computing that cloud computing can bring are the following:

• Reduced costs:  The payment of the technology is incremental, so the organization reduces costs in the long term.
• Growing storage:  The storage capacity in the cloud is much higher than that of a private network.
• Flexibility:  Applications can be easily tested and deployed.
• Automation:  Applications are automatically updated so that the organization’s staff can not worry about the expiration of versions and their installation and maintenance.
• Greater mobility:  Access to the cloud can be done from any location from which an Internet connection is available.
• Greater productivity:  By not having to worry about updating, maintaining, and improving applications and servers, IT professionals who are on the organization’s staff can dedicate the effort and time saved on other more fundamental tasks.

Economic Benefits

• Personnel:  One of the great advantages of cloud computing is that hiring them saves time and investment in human resources. Therefore, the company can choose to save costs by dispensing with professionals. And thus improve specialization and productivity. An increase in the work intensity of specialized personnel in IT (information technology) is achieved. These staff will work on fundamental tasks or redeploy staff to other competencies and/or departments.
• Hardware:  Costs and investments in physical components such as processors, networks, storage devices, and units, etc, are reduced … If more functionalities are needed, just hire them from the corresponding provider.
• Pay-per-use:  Cloud computing allows the company to pay only for those services it uses at any given time. So that a better estimate of the necessary resources is achieved. This allows a faster correction of excess investment in resources or its lack.
• Rapid market penetration:  The cloud makes it possible to obtain services and applications adjusted to the business model of any organization more quickly and easily. In this way, a company can more quickly bring its services to the market. Adapting to the needs of the market. Since no new infrastructure is required. Rather, it is only necessary to vary the contracting parameters of cloud computing services.
• Also Read: Cloud Technology -What Did This Pandemic Teach Us About The Cloud?

Benefits For Staff

• Even if there is a saving in terms of human resources of IT personnel, that does not mean reducing the headcount. The benefits of cloud computing for the staff of organizations multiply significantly with the use of cloud applications. Characteristics are the great ease of use and the low need for installation and maintenance.
• This greatly reduces training and learning time for employees who will be using the applications.
• Furthermore, it is common for applications used in web environments to promote more collaborative and participatory processes. In this line of work, these environments will promote teamwork. They will also promote the generation of incentives for workers.

Benefits For The Consumer

• They do not require any type of installation. Nor maintenance of the software to use the services, which is one of the greatest advantages of cloud computing.
• The deployment time is reduced. Since both servers and applications require little implementation time. Contrary to traditional methods.
• Adherence to the Service Level Agreement or SNA (SLA): This is a written contract between the service provider and its client. In this contract, a certain quality level is set. By adhering to this type of contract, the consumer is guaranteed a minimum quality at all times. For example, if there is an error in the execution of the applications, with the adherence to the SNA the provider will be responsible for the costs and their repair.
• Consumers will have updated applications at all times. Saving so much time, money, and employee training.

Provider Benefits

• Operating environment:  The supplier provides its own operating environment. Consequently, you have the ability to manage, control, and optimize your infrastructure.
• Revenue stream predictability:  Customers pay a minimum subscription fee for the use of services. This facilitates and speeds up the realization of income forecasts in the short and medium-term.
• Market research:  With the data provided by customers and the use of the different services offered, the provider can carry out market research to better understand their behavior. Keep in mind that the software used by consumers is hosted on the provider’s servers. This makes data analysis easier.
• Update schedule:  The vendor’s development team can more easily manage and schedule application and bug process management. So that updates, controls, and reviews are carried out continuously every certain period of time.
• Empowerment of relationship marketing: Another of the great advantages of cloud computing. Thanks to these services, providers can foster and enhance relationships with their customers. This is due to the fact that the subscription payment system facilitates the establishment of relationships more quickly and favors loyalty.

Know More at Top Most Business Opportunities In The Technology Sector

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Without a doubt, the most cutting-edge technological trend of recent years is everything related to artificial intelligence and data analysis. And it is that relatively recently there have been great advances in this field, which together with the availability of enormous amounts of data and increasing computing power are giving rise to all kinds of very interesting practical applications.

The problem comes when the terms related to the field become marketing empty words that in many cases are outright lies. It is very common to talk that this or that product uses artificial intelligence to achieve something and, sometimes, they are conventional algorithms making predictable decisions.

What is Artificial Intelligence?

Artificial intelligence (AI) was born as a science many years ago when the possibilities of computers were really limited, and it refers to making machines simulate the functions of the human brain.

AI is classified into two categories based on its capabilities:

• General (or strong) AI: that tries to achieve machines/software capable of having intelligence in the broadest sense of the word, in activities that involve understanding, thinking, and reasoning on general issues, on things that any human being can do.
• Narrow (or weak) AI: which focuses on providing intelligence to a machine/software within a very specific and closed area or for a very specific task.

Thus, for example, a strong AI would be able to learn by itself and without external intervention to play any board game that we “put before it”, while a weak AI would learn to play a specific game like chess or chess. Go. What’s more, a hypothetical strong AI would understand what the game is, what the objective is, and how to play it, while the weak AI, although it plays Go better than anyone else (a tremendously complicated game), will not really have a clue what it is doing.

One of the crucial questions when it comes to distinguishing an artificial intelligence system from mere traditional software (complex as it may be, which brings us to the jokes above) is that AI “programs” itself. That is, it does not consist of a series of predictable logical sequences, but rather they have the ability to generate logical reasoning, learning, and self-correction on their own.

The field has come a long way in these years and we have weak AIs capable of doing incredible things. Strong AIs remain a researcher’s dream and the basis of the scripts for many science fiction novels and films.

What is Machine Learning?

Machine Learning (ML) or machine learning is considered a subset of artificial intelligence. This is one of the ways we have to make machines learn and “think” like humans. As its name suggests, ML techniques are used when we want machines to learn from the information we provide them. It is analogous to how human babies learn: based on observation, trial, and error. They are provided with enough data so that they can learn a certain and limited task (remember: weak AI), and then they are able to apply that knowledge to new data, correcting themselves and learning more over time.

There are many ways to teach a machine to “learn”: supervised, unsupervised, semi-supervised, and reinforcement learning techniques, depending on whether the correct solution is given to the algorithm while it is learning, it is not given the solution, it is Sometimes you give or are only scored based on how well or poorly you do, respectively. And there are many algorithms that can be used for different types of problems: prediction, classification, regression, etc …

You may have heard of algorithms such as simple or polynomial linear regression, support vector machines, decision trees, Random Forest, K nearest neighbors … These are just some of the common algorithms used in ML. But there are many more.

But knowing these algorithms and what they are for (to train the model) is just one of the things that need to be known. Before it is also very important to learn how to obtain and load the data, do an exploratory analysis of the same, clean the information … The quality of the learning depends on the quality of the data, or as they say in ML: “Garbage enters, garbage comes out”.

Today, the Machine Learning libraries for Python and R have evolved a lot, so even a developer with no knowledge of mathematics or statistics beyond that of the institute, can build, train, test, deploy and use ML models for applications of the real world. Although it is very important to know all the processes well and understand how all these algorithms work to make good decisions when selecting the most appropriate for each problem.

What is Deep Learning?

Within Machine Learning there is a branch called Deep Learning (DL) that has a different approach when creating machine learning. Their techniques are based on the use of what are called artificial neural networks. The “deep” refers to the fact that current techniques are capable of creating networks of many neural layers deep, achieving unthinkable results a little more than a decade ago, since great advances have been made since 2010, together with large improvements in computing power.

In recent years Deep Learning has been applied with overwhelming success to activities related to speech recognition, language processing, computer vision, machine translation, content filtering, medical image analysis, bioinformatics, drug design … obtaining results equal to or better than those of human experts in the field of application. Although you don’t have to go to such specialized things to see it in action: from Netflix recommendations to your interactions with your voice assistant (Alexa, Siri, or Google assistant) to mobile applications that change your face … They all use Deep Learning to function.

In general, it is often said (take it with a grain of salt) that if the information you have is relatively little and the number of variables that come into play is relatively small, general ML techniques are best suited to solve the problem. But if you have huge amounts of data to train the network and there are thousands of variables involved, then Deep Learning is the way to go. Now, you must bear in mind that the DL is more difficult to implement, it takes more time to train the models and it needs much more computing power (they usually “pull” GPUs, graphics processors optimized for this task), but the problems are usually more complex as well.

What is Big Data?

The concept of Big data is much easier to understand. In simple words, this discipline groups the techniques necessary to capture, store, homogenize, transfer, consult, visualize, and analyze data on a large scale and in a systematic way.

Think, for example, of the data from thousands of sensors in a country’s electrical network that send data every second to be analyzed, or the information generated by a social network such as Facebook or Twitter with hundreds (or thousands) of millions of users. We are talking about huge and continuous volumes that are not suitable for use with traditional data processing systems, such as SQL databases or SPSS-style statistics packages.

Big Data is traditionally characterized by 3 V:

• The high volume of information. For example, Facebook has 2 billion users and Twitter about 400 million, who are constantly providing information to these social networks in very high volumes, and it is necessary to store and manage it.
• Speed: following the example of social networks, every day Facebook collects around 1 billion photos and Twitter manages more than 500 million tweets, not counting likes and many other data. Big Data deals with that speed data receiving and processing so that it can flow and be processed properly without bottlenecks.
• Variety: the infinity of different types of data can be received, some structured (such as a sensor reading, or alike ) and others unstructured (such as an image, the content of a tweet, or a voice recording). Big Data techniques must deal with all of them, manage, classify, and homogenize them.

Another of the great challenges associated with the collection of this type of massive information has to do with the privacy and security of said information, as well as the quality of the data to avoid biases of all kinds.

As you can see, the techniques and knowledge necessary to do Big Data have nothing to do with those required for AI, ML, or DL, although the term is often used very lightly.

These data can feed the algorithms used in the previous techniques, that is, they can be the source of information from which specialized models of Machine Learning or Deep Learning are fed. But they can also be used in other ways, which leads us to …

What is Data Science?

When we talk about data science, we refer in many cases to the extraction of relevant information from data sets, also called KDD ( Knowledge Discovery in Databases, knowledge discovery in databases). It uses various techniques from many fields: mathematics, programming, statistical modeling, data visualization, pattern recognition, and learning, uncertainty modeling, data storage, and cloud computing.

Data science can also refer, more broadly,  to the methods, processes, and systems that involve data processing for this extraction of knowledge. It can include statistical techniques and data analysis to intelligent models that learn “by themselves” (unsupervised), which would also be part of Machine Learning. In fact, this term can be confused with data mining  (more fashionable a few years ago) or with Machine Learning itself.

Data science experts (often called data scientists ) focus on solving problems involving complex data, looking for patterns in the information, relevant correlations, and ultimately, gaining insight from the data. They are usually experts in math, statistics, and programming (although they don’t have to be experts in all three).

Unlike experts in Artificial Intelligence (or Machine Learning or Deep Learning ), who seek to generalize the solution to problems through machine learning, data scientists generate particular and specific knowledge from the data from which they start. Which is a substantial difference in approach, and in the knowledge and techniques required for each specialization.

The post Clarifying The Concepts Of Various Technology Terms – Artificial Intelligence, Deep Learning, Machine Learning, Big Data, and Data Science appeared first on TechReviewsCorner.

Who to select and how?

• Check for the provider’s availability. All ISP’s do not provide services in all areas of the U.S.
• Look at the kind of connection that you may need by focusing on the number of employees, number of presents and prospective clients, and the kind of functions your business is set out to perform. That will help in choosing a package that most efficiently fulfills your demands.
• If your company has a few functions that can be dealt with, with a lower bandwidth then you don’t have to pay extra for a high-speed connection. In case you’re a venture with various areas and departments and have a long list of employees with varying degrees of responsibilities and obligations, a good speed with unlimited data may be your only hope.
• Once you have decided on the ISP and the package, be very careful with the terms of the contract. There may be hidden fees or rules that may put you in a bad place if you ever decide to cancel your subscription. Look for flexibility.
• Once you’re done with all of the above, try finding the ratings of the companies through customer reviews. This will be extremely helpful in finalizing the deal.

We’ve selected a few internet providers which we thought were providing the best services which can cater to most of the businesses. We took into account the availability of the connection, its speed, price, plans and packages, ratings, and flexibility.

Also Read: Low-Cost Social Media Management Services for Small Businesses

Verizon Fios Business plan

• Verizon is offering its consumers 5 internet plans.
• The download speeds range from 75 Mbps to a maximum of 940 Mbps.
• Its price starts from $64.99 a month during the first year, $69.99 for the second. Then on the higher side, the price starts at $214.99 a month through the first year and $224.99 for the second.
• These prices do not include equipment charges or any kind of fees.
• It’s not good if you are looking for a no-contract plan but that can be managed if necessary. Verizon’s contract lasts for only two years and requires customers to pay a cancellation fee that is just 35% of the monthly fee for the rest of the term.
• Another downside is its limited availability. You can find it in only a few metro areas in about 9 states along the East Coast.
• It has the best customer satisfaction rating among all its other contenders. 

Spectrum Business internet

• Spectrum is offering three internet speeds to its consumers. They start from 200 Mbps, from that it goes to 400 Mbps, and then reaches a maximum of 940 Mbps.
• The prices are extremely affordable though, which is a plus that goes in the favor of Charter Spectrum internet, starting at $44.99. You can check the rest of their prices and plans by clicking on the link and entering your business address. Offers may vary in different areas.
• An upside to Spectrum is that all their packages are contract-free. Moreover, since they are available in almost 44 states across the USA, most of you can find their services available in your area of choice. You can grow and expand your business while flying free.
• They get some mixed sort of reviews from the customers. So do try and read their fine print in detail before buying their services.
• All in all, Spectrum is a great, budget-friendly way to start your company with.

Comcast Business internet

• Comcast stands out among its competitors due to its high-speed. It offers the maximum fast-speed of 1 Gig or 1,000 Mbps. They deliver on their promise of outstanding download speeds.
• Its data plan’s business bandwidth starts from 25 Mbps and goes to 300 Mbps.
• They offer a pro packed feature for their Business connection. If for any number of reasons, your connection is disrupted, Comcast will shift you to a 4G LTE backup that will be wireless.
• To get an exact quote about their pricing for your business, provide them with your address.
• The downside to Comcast is that there is a 2-year contract. Additionally, their cancellation is also a little on the high side according to their customer’s reviews.

Frontier Business internet

• In case you’re a small business, running your operations out of your home, and do not want to invest too much on the internet, Frontier may be just right for you.
• Although the speeds offered by Frontier are the slowest, ranging from only 7 Mbps to 40 Mbps, their bundle deals are priced low.
• Any small store or service can benefit greatly from this because such low speeds will not pose any threat to your business.
• Their most budget-friendly deal includes Business Max plus Voice service at 7 Mbps with free Wi-Fi router and installation as well as a business phone, costing you $49.98 per month in a 2-year contract.

These were just a few of the ISPs that we think will benefit most people no matter how big or small their business needs may be. Try keeping a focus on flexibility as your requirements may get bigger once your venture starts expanding.

Also Read: KEYS TO PROTECT YOUR ROUTER: AVOID MALWARE AND DETECT IF SOMEONE STEALS YOUR WIFI

The post List of best business internet providers in the USA appeared first on TechReviewsCorner.