Technology News Archives - Page 5 of 7

Differences Between Native Apps and Hybrid Apps

January 2, 2021/in Technology News/by Top World Business

Understanding the Differences Between Native Apps and Hybrid Apps

Before diving deep into the differences between native apps and hybrid apps, let us learn the basics of modern smartphone apps.

Smart mobile phones have become the ultimate necessity for living in modern times. A typical smartphone today has more features and processing abilities than the computers that were used to send the first rockets into space. Similarly, the ability to use multiple types of applications is the most important feature of these small-sized yet very powerful devices.

The development of the iOS store and the Google Play Store has allowed millions of app developers to build something from their own imagination. Furthermore, this is now a very lucrative career and largely successful individuals and companies have already made hundreds of millions. Similarly, mobile apps are also one of the topmost priorities for businesses as most of their customers spend a significant amount of time on their smartphones. Depending on your goal and target audience, you might want to choose between native apps and hybrid apps.

Native Apps and Hybrid Apps: Basic Concepts

Native apps are those mobile apps that are designed to work on a specific device and built on a specific platform. The most common mobile device platforms are iOS and Android. Similarly, both of these platforms have a dedicated application store where independent developers and companies can build and sell their apps. Most importantly, these types of apps only work on the hardware they were designed for, as they live upon specific operating systems.

Hybrid apps are those types of apps that contain features of both native and web platforms. These types of apps are not designed for specific platforms and devices but are universal. They use cross-compatible web technologies like HTML, CSS, and Javascript and you can also deploy them in multiple mobile application stores.

Differences Between Native Apps and Hybrid Apps

Now, let us learn about the differences between native apps and hybrid apps on the basis of the following factors.

Major Features

Native apps are generally more reliable than hybrid counterparts because they are designed by keeping the specific platform in mind. They are optimized to their best according to the operating system and the hardware. Similarly, this also facilitates better responsiveness and a seamless user experience. Furthermore, they can easily interact with hardware sensors and modules like GPS, Bluetooth, camera, microphone, and fingerprint.

Hybrid apps, on the other hand, have better cross-platform performance and user experience. They have better viewing on both mobile and desktop devices.

Programming Languages

Native apps are typically built on two main programming languages. You typically use Java for building Android apps whereas both Objective-C and Swift are suitable for building iOS apps.

Hybrid apps, on the other hand, are typically built using HTML, CSS, Javascript, and a myriad of other frameworks. These frameworks ease the process of deploying into multiple specific platforms.

Development

One of the major differences between native apps and hybrid apps is their development process. The development of native apps takes more time because it must lie within the boundaries of specific operating systems and hardware support. Similarly, you would need different developers for different mobile platforms. Therefore, the development cost is also greater than that for hybrid apps.

On the other hand, hybrid apps take less amount of time because of their flexibility. With a single code base, you can run these apps on multiple platforms. Furthermore, since you do not need different developers for different platforms, it is also significantly cheaper.

User Experience

We have already understood that native apps feature a superior user experience over hybrid apps. This is because you specifically design native apps for a single mobile platform with dedicated support for different screen sizes. Furthermore, they also take into account the hardware capabilities and operating system support.

On the other hand, hybrid apps are not built with a specific device or platform in mind. Therefore, they might not provide a quality user experience on some platforms. Similarly, since you do not design it for specific screen sizes, there might be some distortions and deformations.

Conclusion

In this blog, we have learned the difference between native apps and hybrid apps in terms of their features, programming languages, development time and cost, and user experience. In conclusion, your choice of native apps and hybrid apps all comes down to your objectives and goals. Similarly, both of them have their own advantages and disadvantages and you need to decide the best fit for yourself.

Technology news must be a top priority if you want to learn about the current state of the market and its possible evolution. As a highly reputed source of technology-related news, we at Top World Business make sure that you stay updated on the latest trends and receive the correct information. In this fast-changing world, we make sure that you won’t miss a high potential investment.

Do You Need to Learn a Programming Language to Build an App?

December 30, 2020/in Technology News/by Top World Business

Do You Need to Learn a Programming Language to Build an App?

Mobile apps development has been one of the most lucrative careers over the last decade. The introduction of app stores for iOS and Android platforms has been a great opportunity for independent developers and companies. Anyone can build and sell their apps on the app store and highly successful developers have been able to make millions. Most importantly, there are a number of advanced tools that have eased the process of building apps. You might not need years of college education or advanced knowledge of programming language to build an app.

Building Apps Without Programming Language

Even though you do not need advanced knowledge of programming language to build an app, you must understand the development process. App maker platforms will provide you with modules and drag-and-drop features. However, you must understand the following steps:

Design and Appearance

When you are not using any programming language to build an app, you must design your appearance according to the available themes. Likewise, you might want to keep your appearance consistent with your branding scheme. You must keep track of colors, logos, font style, and custom icons. Modern app builder platforms will likely consist of all these types of features so you can customize them according to your needs.

App Content

You must add content according to the available templates when you are not using a programming language to build an app. These templates consist of frequently used content types that you can edit for your business needs. Some of the most common types of templates include the contacts page, about us page, service page, application and registration page, and loyalty programs.

Final Steps and Publishing

The final steps of building an app include defining platform-specific attributes. This might be the screen size and type for a seamless viewing experience in all types of devices. Likewise, you might want to optimize some features according to the operating system and hardware capabilities. Furthermore, you have to keep consistency in both web and mobile viewing.

Finally, after all these steps, you are ready to publish your app. You must keep proper information on copyright and publishing rights. Likewise, you must consider the guidelines regarding age and audience which is defined by the application store. Most importantly, make sure that you have done enough marketing so that you can gain a decent number of users.

Common App Maker Platforms

If you do not have the knowledge of programming language to build an app, you must be aware of available app maker platforms. Some of the most popular platforms are:

AppMakr

AppMakr is one of the most widely used platforms that require no experience and advanced experience of programming language to build an app. You can design apps for multiple platforms like Android, iOS, and HTML5. First, you need to sign up for a free account. After that, you can create any number of apps you wish from its available modules and themes. When you are done building your app, publishing is the only difficult part. Similarly, you would need to pay for a Google Developer account or Apple Developer account when you want to publish in their app stores.

Appy Pie

Appy Pie is also one of the popular app builder platforms that require no programming language. You can create apps for Android, iOS, and Windows on both web and mobile platforms. If you come from a non-technical background with little to no coding experience, Appy Pie is a great option for you. Similarly, you can create native, cross-platform, and hybrid apps depending on your goals and budget. It supports push notifications, GPS, real-time analytics, QR, and other advanced features.

Appy Pie lets you make websites, mobile apps, chatbots, and graphic designs for free. However, some of its advanced features come with a pricing plan. The most common pricing plans include:

Standard Plan

Supports 2000 tasks per month
40 connects
5 Premium Apps
5 minutes run time interval
Starts at 9.99 USD per month billed annually or 12.49 USD monthly

Professional Plan

Supports 5000 tasks per month
Unlimited connects
Unlimited Premium Apps
2 minutes run time interval
Starts at 9.99 USD per month billed annually or 12.49 USD monthly

Moreover, Appy Pie allows a free fourteen-day trial period where you can check out its features and make your decision.

Appery.io

Appery.io is an excellent platform that allows you to build apps without prior programming knowledge and experience. It features a drag-and-drop UI builder feature that you can use to build mobile, web, and hybrid apps. Likewise, it is cloud-based, which means it removes all the hassles of libraries and dependencies. You can build apps in days instead of months. Similarly, once you build an app, you can deploy it to multiple platforms with its cross-platform support. Furthermore, it supports easy collaboration with team members and also allows you to deploy your own custom mobile backend.

Appery features multiple pricing plans range from 25 USD per month (Beginner) to 500 USD per year (Ultimate). The Beginner plan allows you a single developer to build up to 2 apps per month. Likewise, the Ultimate plan allows up to 10 developers to build up to 12 apps per month.

Building Apps With vs Without Programming

Now that we have learned about the app development process and available app builder platforms, let us compare building apps with vs without programming.

The following are the key characteristics of building apps without programming:

Ready-to-use templates and modules make it easier to build apps for people who come from a non-programming background.
If you are a business owner wanting to enter the app space quickly, these platforms will help you build working apps within days.
If you have common computer knowledge and do not want to spend on hiring a professional developer, this can be a good option.
With a single codebase, you can deploy your app to multiple platforms.
App builder platforms maintain high optimization which means your apps will run best according to the hardware and operating system capabilities.
Adding custom services can be difficult if it is not available within the developer platform.

On the other hand, building apps with programming knowledge has the following characteristics

You can build apps tailored to your specific needs. Updating features is easy because you know all the whereabouts.
If you are a novice developer, building apps can take time. As you grow your experience, development time will reduce considerably.
There will likely be hundreds of errors during the development process. However, you will be able to debug them with documentation and community support.
In case any problem arises, you will be able to track and remove such problems.
You can still integrate your code with app maker platforms if there is a need for rapid deployment.
Building native apps for different platforms will require multiple developers.

If you have time, we recommend you learn a programming language to build an app. This knowledge will be very important even while you use app builder platforms. Similarly, programming will teach you about practical problem solving which you can use in other applications.

Conclusion

In this blog, we have learned the nuts and bolts of how you might not need the knowledge of programming language to build an app. Likewise, we discussed some of the major app builder platforms in use today. Finally, we concluded with the comparison between building an app with vs without programming language.

Technology news must be a top priority if you want to learn about the current state of the market and its possible evolution. As a highly reputed source of technology-related news, we at Top World Business make sure that you stay updated on the latest trends and receive the correct information. In this fast-changing world, we make sure that you won’t miss a high potential investment.

Big Data Analysis to Understand Customer Behavior

December 26, 2020/in Technology News/by Top World Business

Understanding Customer Behavior With Big Data Analysis: An Overview

It is a common understanding that big data analysis is one of the hottest topics for researchers and industries today. Big data refers to the large volumes of data, which can be both structured and unstructured. Likewise, they are most commonly characterized by the 5 Vs.

Volume

Understanding the volume of big data is crucial for anyone who wants to take advantage of big data analysis. Big data systems deal with terabytes(TB) units and above and are out of the range of most personal computers.

Velocity

Understanding the rate at which the data is being generated is also a crucial part of big data analysis. Sometimes, a low volume of data with perfect timing can provide a greater advantage over a large volume.

Variety

Anyone who has a basic understanding of big data analysis knows that not all data are the same. Today, smart sensors and processors can be embedded in any type of application. This is due to the fact that they have exponentially grown powerful while simultaneously lowering their size. Businesses have to find out which type of data can provide the most fruitful insights.

Veracity

Veracity is one of the key factors that big data analysis sits upon. It refers to the quality and accuracy of the data obtained and whether or not they can provide value.

Value

The value that the obtained data offers is the final piece of the puzzle. If your data cannot provide valuable information for your business, it is not worth employing such complex systems at their high cost.

Why is Data Getting Big?

In less than two decades, the Internet has become one of the most important human inventions. Similarly, it has been an inseparable part of human lives, and the convenience it has caused is immeasurable. Therefore, it is only common that there will be unfathomable amounts of data on this platform.

Some of the reasons why such enormous amounts of data are being generated every day are:

Most of the communication and interaction between people happens on the Internet today.
The number of people who use e-commerce has grown massively in the last decade.
The use of the Internet of Things (IoT) in many industries and applications has given an enormous volume of sensor-generated data.
Social media sites, streaming sites like Netflix and Amazon Prime, and e-commerce sites can record the finest details involving customer interactions.
Many technologies and applications that remained inside labs and private spaces have been released for open-source research.

Due to the above-mentioned reasons, systems that store and process such data volumes have become crucial for businesses and governments.

Big Data in Customer Behavior Analysis

Customer behaviour refers to the process of understanding your customers through data and using this information to make business decisions. You can understand and segment your market, predict future customer needs, develop new products, and improve existing products. Today, there are millions of analytics tools and platforms that you can embed into your websites and IT infrastructure.

Similarly, customer experience can be a point of difference between you and your fierce competitors. The nature of the new buying population prefers brand relationships and experience over price and products. Therefore, this is vital for customer acquisition as well as retainment.

The following are some of the ways how big data analytics could grow your business and your profits by understanding customer behaviour.

Customer Acquisition and Retention

Customer acquisition and retention are some of the toughest jobs for businesses today. Since products and prices do not have as much differentiation power as they used to, companies have to search for new ways. Likewise, it is very easy for customers to switch from one brand to another because of the available options. Therefore, it is up to the brands to provide quality products and services and maintain meaningful relationships. The prospect of big data analysis, in this case, is massive. Understanding customer behaviour will help you design products and services that best suit their needs. Furthermore, you can design loyalty programs, discounts, and giveaways to support your goal of retainment. Moreover, you can capture your future customers before they reach buying capacity. For example, Airlines can identify frequent-flying future customers like students in business schools and reward them with loyalty programs.

Prediction of Customer Needs

Prediction of customer needs is one of the most important applications of big data analysis for businesses. Since buying and selling over the internet has exponentially increased all over the world, failing to capitalize on this means you will get behind. E-commerce sites have analytics tools that can record customer buying behaviour and predict their future needs. We have already seen product recommendations that pop up almost instantly after product viewing or buying. Furthermore, you can also use predictive analysis to provide a tailored experience for your customers.

Understanding Reviews and Feedbacks

Collecting reviews and feedbacks for your products and services has never been easier. You can get them through your websites or different social media handles. Since reviews are public and can be seen by anyone, it is important that you address your shortcomings instantly. Furthermore, you must understand that reviews affect buying decisions. If your product has bad reviews, there is a high chance that new viewers will instantly avoid it. The use of big data analysis is vital to understand what people are saying and writing. For example, text analysis systems can derive sentiments of the people from what they have written. Similarly, you can understand the keywords in the bad reviews which will tell you what to improve upon.

Understanding Your Competitors

For any business, staying ahead in the competition requires an understanding of competitors. Due to the rise of e-commerce, it is very easy to understand your competitors’ pricing and programs. Likewise, you can also look for reviews and feedback on their products and services. This will help you understand what you are lacking and what you should avoid. Furthermore, you can develop your own new strategies and programs to attract customers from your competitors.

Improve Indicators Measurement

Big data will improve upon the inaccuracies and biases in traditional marketing and indicators measurement. For example, the Net Promoter Score (NPS) is a measure of how likely customers are to recommend your products and services in their circles. However, this is error-prone as not all customers will provide real answers. In contrast, big data analysis will take into account real interactions and purchases, which will derive more accurate indicators.

Conclusion

In this blog, we have learned how big data analysis is key to understanding customer behaviour. Similarly, we have also discussed how you can use the power of data to acquire customers, improve their experience, design new products, and understand your competitors. Furthermore, employing such systems has been very easy as there are a number of cloud-based providers. You need not invest huge amounts of money in sophisticated hardware.

Technology news must be a top priority if you want to learn about the market’s current state and its possible evolution. As a highly reputed source of technology-related news, we at Top World Business make sure that you stay updated on the latest trends and receive the correct information. In this fast-changing world, we make sure that you won’t miss a high potential investment.

Medical Tech: Will AI Replace Doctors?

December 23, 2020/in Technology News/by Top World Business

Will AI Replace Doctors? A Brief Overview

Before answering this question of will AI replace doctors, let us understand the growing use of AI in the field of medicine.

Artificial intelligence and machine learning have been some of the most quickly adopted technologies in a multitude of industries. This can range from manufacturing and finance to medicine and defence. Typically, AI is used to model complex relationships that would be practically impossible for humans because of the sheer amount of data involved.

AI in Medicine

The use of AI in medicine has brought a revolution in how we identify, record, and diagnose patients. The following are the branches of AI that have their own specific applications in medicine.

Genetic Algorithm

Genetic algorithms have found a fruitful application in the field of radiology and disease screening. There have been a number of researches on the use of genetic algorithms for breast cancer detection. Likewise, they have been continuously used in the study of Positron Emission Tomography (PET) and Magnetic Resonance Imaging (MRI) images.

Data Mining

Data mining is a technique that is used to gather important insights from an enormous amount of data. There is a growing use of this technology in the research and development of new medicines. Likewise, it also finds its use in measuring the effectiveness of medical treatments.

Pattern Recognition

Pattern recognition is also one of the most widely used technologies in the field of medicine. Recording, classification, and interpretation of medical signals and images have been important for doctors in clinical decision making. Some of the specific examples include the detection of eye diseases, hypertension, and cancer cells.

Neural Networks

Neural networks are some of the most versatile technologies that have found multiple uses inside the field of medicine. They have a promising future in the modelling of complex human biology. Likewise, they are used in the interpretation of medical images to detect tumours and cancers. Similarly, telemedicine or remote health monitoring is also a great application of neural networks.

So, Will AI Replace Doctors?

The question of will AI replace doctors is a very challenging one. However, you can be pretty confident that AI will work in conjunction with doctors in the near future.

If it is the case that AI replace doctors in the future, the following will be the most common areas.

Patient Health Monitoring

Since a doctor cannot provide personalized monitoring and treatment to hundreds of patients, this is where AI comes in. Medical sensors can provide real-time data about the status of patients and send it to the cloud. Healthcare professionals and doctors can then monitor hundreds of such data and identify those patients who need immediate attention. Likewise, electronic health records will be crucial in studying the development and evolution of diseases.

Imaging and Signal Analysis

If technologies like machine learning and AI replace doctors, medical imaging and signal analysis will be one of the most common areas. Machines powered with artificial intelligence algorithms have been able to understand body signals and detect diseases, tumours, and cancers in image scans. The accuracy of such algorithms has massively increased over the past few years. Furthermore, in third world countries in Asia and Africa, there is a single MRI machine for tens of millions of people.

Without an automated diagnosis system, it is impossible to provide timely health services for all the needy people. Similarly, for remote health monitoring systems, signal analysis systems must be a top priority as there is tons of data involved. Moreover, AI and ML can learn the nature of pandemics and support in their containment.

Complex Surgeries

One of the most promising fields where technologies like nanorobots and AI replace doctors is complex surgeries. Nanobots can precisely reach the targeted areas in the human body. They can carry required doses of chemicals and medicines within the cells. Similarly, they can report the status of the human organs and automatically classify and report different stages. This will eliminate the need for large cuts and unnecessary interventions inside the human body. Furthermore, even in nonrobotic surgeries, gesture recognition applications have allowed surgeons to view the inners of the body without a controller in hand.

Now, let us learn some of the areas where human doctors are still vital over machines.

Human Touch

Even if technologies like robotics, nanotechnology, and AI replace doctors, there is always one thing missing: the human touch. Through years of research and practice, humans have somewhat mastered the art of empathy. It is still too early to say that AI will calm a patient undergoing surgery or interact rightly with a patient on anaesthesia. Furthermore, not everyone will feel confident that machines are working inside their body. Likewise, they will likely not let machines make a life-altering decision and recommend medicines without the guidance of doctors.

Understanding Never-Before-Seen Circumstances

Although AI will improve upon its problem-solving skills in the future, it is still immature in terms of creativity. Not all patient cases are straightforward and they cannot be estimated with the help of past data. Likewise, not all patients will live the same lifestyle and in the same environment. Sometimes, there might be a never-before-seen case even for experienced doctors. In this case, they might have to consult others in their community and also call for a joint investigation. We should never forget that the knowledge that humans have today is based upon thousands of years of trial and error. AI will likely not have the ability to adapt and solve new types of problems as humans.

Operating AI-powered Machines

Even though AI can crunch tons of numbers and analyze signals and images, they still need monitoring from humans. Even though surgical robots have greater precision in terms of movement, they are still being operated by human doctors. In many cases, data and information learned by machines still need to be inspected and verified by experienced doctors. Furthermore, humans will still have to tell AI where to go and what to do and then it can handle the complex calculations that come after.

Paperworks and Administration

Healthcare professionals like doctors and nurses do more than diagnosis and treatment. Since medicine is a critical field full of life or death situations, there is a lot of paperwork involved. Doctors will still have to carry out administrative tasks that will be difficult and time-consuming for intelligent machines.

Conclusion

In this blog, we have learned how and where can AI replace doctors and where human knowledge and reasoning still comes out on top. AI will certainly change the way medicine and healthcare are delivered, but it is very unlikely that they will take jobs from doctors. Most importantly, we must understand that it is not our need for one to replace the other. AI will possibly take care of data crunching, modelling relationships, and analyzing images and signals. On the other hand, medical professionals can focus more on finding new ways of treatment and new medicines. Since they can work much better in conjunction than in isolation, we must find ways to make this possible.

Technology news must be a top priority if you want to learn about the current state of the market and its possible evolution. As a highly reputed source of technology-related news, we at Top World Business make sure that you stay updated on the latest trends and receive the correct information. In this fast-changing world, we make sure that you won’t miss a high potential investment.

Reasons You Should be Using an APM Software

December 20, 2020/in Technology News/by Top World Business

Top Reasons Why You Should be Using an APM Software

It is a common understanding that software has become one of the most crucial parts of any business. There is hardly any business that can survive and prosper without computer support and a basic level of automation. Similarly, you need to use hundreds of software services to maintain a functioning IT infrastructure. This includes websites, mobile apps, cloud services, marketing, customer management, and accounting software. Furthermore, there are several third-party APIs that you must integrate to widen your business possibilities.

Managing this highly complex system requires a large number of developers, testers, system administrators, and managers to work in an agile fashion. Even minor limitations in this link will degrade your performance and image among customers. Furthermore, you still cannot compromise on time since competition is fierce. This is where the APM software comes in.

Application Performance Management, or APM software, is a tool that helps developers identify performance-related issues after deployment. For example, you might need to assess the performance of your website or mobile app on all types of computers and mobile devices. This is important to maintain a high-quality user experience consistently. An APM software will provide better visibility of the user experience that you are currently delivering.

Improved Visibility of Your Technology Stack

With APM software, you get better visibility of the applications and services in your technology stack. Likewise, you will be able to understand how they link to one another and how they perform together. Similarly, since most of the available APM software is cloud-based, you will be able to monitor your performance from anywhere. This will also help you track and solve any type of problems that may arise during operation. Most importantly, you will always maintain a quality user experience and make sure the complaints are limited. Furthermore, there will be fewer disruptions so that your organization runs smoothly.

Reduction in IT Costs

APM software will help you understand the limitations of your IT infrastructure. Similarly, they will also help you predict possible failures and degradation in user experience. This will guide you to make timely adjustments and upgrades to your existing architecture. This approach will save a huge amount of money in the long run. It is better to stay prepared before the disaster occurs.

Better Market Visibility

Most modern businesses have an online infrastructure for rapid marketing and maintaining a wide customer base. There is fierce competition between companies to get better visibility in social media and web searches. Search engines like Google and Bing rank your websites according to their architecture and performance. With APM software, you can understand the performance of your website and make necessary improvements.

Boost in Revenue and Sales

For modern businesses, the Internet is a very crucial place for acquiring new customers. Maintaining brand consistency and quality is very important and has a huge impact on the company’s revenue. Since there are several options to choose from, customers can quickly change their preferences. For example, if you are an e-commerce site and your orders database goes down, you are likely to lose a significant number of customers.

Increased Innovation

When a company spends significant amounts of time and money on recovering from failures and service breakdowns, innovation can take a hit. Similarly, with APM software, your development team is less involved in fighting failures and more on developing new plans and strategies. The companies wishing to maintain agile development and delivery practices need to constantly monitor their application’s performance.

Conclusion

In this blog, we have learned the reasons why your business should be using APM software. In conclusion, APM software will maintain a robust IT infrastructure for any business and predict possible failures. Understanding the possibility of failure and mitigating risks early will save both operational time and costs. Furthermore, this is also important to maintain a quality user experience and a strong presence in the market.

Technology news must be a top priority if you want to learn about the current state of the market and its possible evolution. As a highly reputed source of technology-related news, we at Top World Business make sure that you stay updated on the latest trends and receive the correct information. In this fast-changing world, we make sure that you won’t miss a high potential investment.

Understanding the Internet of Things

December 1, 2020/in Technology News/by Top World Business

Understanding the Internet of Things: The Easy Guide

Internet of things or IoT is a network of connected devices that has the ability to record and communicate data over a wireless medium. Just like the Internet connects webpages stored in servers all around the world, the Internet of things connects everyday devices like refrigerators, water heaters, and microwave ovens. For example, imagine that your refrigerator is able to record the data of all the food items it is currently storing. Likewise, it will be able to notify you when your food stock decreases below the predefined value. Furthermore, with more advanced functionalities, it may be able to order the food you require automatically.

How Does the Internet of things (IoT) Work?

Experts predict that there will be more than 40 billion connected devices by the mid of this decade. It will also be a major contributor to the fourth industrial revolution. Therefore, understanding how the Internet of things works is essential for anyone whatever your background or profession is.

The following are the major components that go into the working of IoT.

Sensors

Sensors are devices that are used to measure some physical quantities. They are designed in such a way that the quantity to be measured will produce an electric signal (in most cases). For example, a light sensor may have a component that gives a voltage depending on the intensity of light upon it. These voltages can be read by a digital device and stored in digital form. The major function of a sensor in IoT is to collect and if possible, store data.

Wireless Communication

Wireless communication technologies are at the heart of IoT. At present, most of the IoT devices work on Bluetooth and WiFi technologies. However, they are limited in range and data rates. With the rise of 5G technologies, you can expect rapid development of IoT devices and applications.

Processing Hardware

The processing hardware could be a microcontroller that interacts with the sensor and transmits data. Much of the development in the Internet of things, or digital technologies in general, is powered by the exponential advancement in microprocessor manufacturing technologies. Processors are getting smaller, powerful, and easier to interface day by day.

Processing Software

IoT devices transfer enormous amounts of data every day. The processing software must be able to receive, store, process, and analyze them for extracting fruitful information. Big data technologies will facilitate the handling of billions of data coming from tens of thousands of interconnected devices.

Major Applications of the Internet of Things

IoT has the potential to transform any industry from automobiles and healthcare to disaster management and security. Some of the major areas of applications are listed below.

Healthcare

The development of wearable medical devices and sensors can change the way healthcare is provided. Doctors can read the health information of patients from a remote location and store it in electronic medical records. Likewise, it will reduce congestion in hospitals, and thus management will be easier for doctors and nurses. Furthermore, we are beginning to see the use of robots in surgeries.

Agriculture

The Internet of things will power the smart farms of tomorrow. These devices can automatically detect the chemical quality and moisture in the soil and report to farm owners. Furthermore, they can add water and nutrients when it is required. The major advantages of using these technologies in agriculture is the reduction in water usage, energy, and early identification of diseases in crops.

Industries and Manufacturing

With the Internet of things, all the machines and equipment in the industry can be monitored and controlled accordingly. This will help technicians to identify possible malfunctions and anomalies early on. Furthermore, the applications of robots and digital manufacturing technologies are also the major features of the fourth industrial revolution. Multiple machines might have to work together and transfer enormous amounts of data between them swiftly.

Smart Homes

With the Internet of things, you might be able to control all the devices on your home with your voice or touch command. Google Home and Alexa are some of the most common examples. Although they may not be mainstream now, their applications are expected to increase in the coming years.

Smart Cities

The Internet of things will be the core of digital and smart cities in the future. They will improve the supply of electricity and water, monitor traffic on roads and bridges, assess the health of degrading structures, and measure pollution and greenhouse emissions.

Major Challenges of the Internet of Things

Even though the Internet of things has a promising future, it is not free from challenges. One of the greatest challenges is the security of such high volumes of data and information being transmitted daily. Breaches and hacks in critical information like medical and financial records can be fatal. Likewise, breaches in privacy is also a major concern. A single person can disrupt the coordination of hundreds of machines in an industry. Furthermore, it requires billions of devices to manufactured which can stress the available resources on our planet. Moreover, power consumption will also be a crucial factor.

Conclusion

In this blog, we have learned what the Internet of things is, how it works, the major application areas, and the challenges it faces.

Technology news must be a top priority if you want to learn about the current state of the market and its possible evolution. As a highly reputed source of technology-related news, we at Top World Business make sure that you stay updated on the latest trends and receive the correct information. In this fast-changing world, we make sure that you won’t miss a high potential investment.

Do Smart Homes Make People Productive or Lazy?

November 28, 2020/in Technology News/by Top World Business

How Smart Homes Will Make You More Productive Than Lazy

The word “smart” has been fairly popular for the past few years. This has been possible due to commercial advancement and success in IoT (Internet of things) technology. One of the most popular applications of IoT is the Smart Homes or Home Automation System.

Before learning how smart homes make people productive, let us understand what it is and what goes into building such type of systems.

Smart Homes: An Introduction

A smart home is made by incorporating automation and control features to appliances and devices that you use on a daily basis. It includes controlling the electrical appliances, lighting system, ambience, temperature, and other attributes remotely by using a mobile or desktop device. Similarly, the smart home system can record and learn the pattern of your appliance usage. They can suggest, remind, and sometimes act on their own to ensure optimum performance. Simply stated, you have complete control of your home at your fingertip.

Components of a Smart Home

A smart home system contains a lot of mini-systems. A user can choose which system he/she wishes to implement. Let us list some of the components that comprise a Smart Home system.

Automated Monitoring and Security System

This ensures that the house can be monitored even when you are outside. This means you can look after your pets and children when you are at work. Likewise, the security system can be used to detect intruders and unknown people. In the case of a breach, it can fire alarms and notify you instantly.

Automated Lighting System

This system consists of a network of smart lighting devices. The intensity and gradient of lights can be varied according to need. Similarly, the network can also operate automatically to optimize energy usage or manually at your discretion. For example, hotels use lights that turn on when there is a person nearby.

Smart Ports to Control Electric Appliances

These smart ports can sense when your charging device has been fully charged and will disconnect the power supply. This will enhance the battery life of those devices.

Automated Temperature

This system maintains the home temperature at a desired constant level throughout the year.

Automated Gardening System

This system automatically waters the plants in your garden. Some advanced systems even monitor the plant growth automatically.

Automated Gates and Door Systems

As the name suggests, it automatically opens and closes the doors in your house. For example, you can use a remote that sends our radio signals to the receiver at the gate. Then, the receiver will command the actuator to open or close the door. This action is always under your control and is thus secure.

Connected Devices in the Home Network

In a smart home system, all the devices are connected and can be controlled through a central system. For example, you can heat your favourite dish inside an oven so that it is ready when you get home.

Now that we have understood the basics and the major features, let us learn how smart homes make people productive.

You Don’t Need to Keep Moving Around the House Doing Things

One of the ways how smart homes make people productive is that you don’t have to keep moving around the house to do things. All the tedious and non-productive works inside your home can be completed at the touch of a button. Furthermore, you are free of frequent interruptions and distractions. You can utilize the saved time at your discretion doing things that interest you.

Smart Homes Motivate You to Keep Up with the Advancing Technology

This is one of the unseen ways that smart homes make people productive. Once you have installed a smart home system, you will want to keep up with new advancing technologies. In doing so, you will feel motivated to update yourself with the latest technology that can be used to make your daily activities easier. And, ease in doing tedious tasks doesn’t mean that you will be lazy. In contrast, you can utilize the saved time learning and updating yourself about newer technologies and trends.

Smart Homes Save a Lot of Energy and Reduce Costs

One of the ways smart homes make people productive is that you don’t need to calculate your energy consumption and stress about bills. Smart homes consist of devices like smart lights, appliances, automated taps, etc. Likewise, these devices are very efficient and consume less energy. Similarly, these devices also identify when energy is being wasted and reduce wastage. For example, the smart lights turn on if it’s night and if someone is present in the room. If there is no one, it turns off automatically.

Conclusion

From this blog, we have understood how smart homes make people productive by automating most of the daily, tedious tasks.

Technology news must be a top priority if you want to learn about the current state of the market and its possible evolution. As a highly reputed source of technology-related news, we at Top World Business make sure that you stay updated on the latest trends and receive the correct information. In this fast-changing world, we make sure that you won’t miss a high potential investment.

How AI Technology Will Prevent Pandemics

November 25, 2020/in Technology News/by Top World Business

How AI Technology Will Prevent Pandemics: The Easy Guide

The discussions on how AI technology will prevent pandemics have become mainstream after the coronavirus crisis in 2020. This recent crisis has exposed many limitations to our modern lifestyle and challenged us to improve upon them quickly. Likewise, our existing resources and technologies have been unsuccessful to control and prevent this disaster. Similarly, more than 1 million people have died and we still have not been able to control the spread. Furthermore, hospitals are at maximum capacity and the number of healthcare workers is insufficient.

Artificial intelligence is one of the most versatile technologies that is finding applications in multiple fields and industries. Therefore, a lot of research and experiment has been devoted to how AI technology will prevent future pandemics. Some startups have already begun to develop working models to predict the spread and improve contact tracing. Most of the applications are focused on early identification of warning signs, surveillance of spread, contact tracing, and assistance to healthcare workers.

How AI Technology Will Prevent Pandemics

There is growing optimism that AI technology will prevent pandemics or at least assist us in prevention in the future. Before the coronavirus outbreak became significant, a Candian startup named BlueDot was able to spot the signs in Wuhan. Similarly, other startups have been able to design software that can detect infections. Furthermore, some researchers have been leveraging the power of AI to develop vaccines.

Let us discuss these contributions in more detail.

Early Prediction

Early prediction is one of the common ways of how AI technology will prevent pandemics in the future. Through natural language processing techniques, AI can learn and analyze social media sentiments, news reports, and government briefings. With this knowledge, AI can predict the seriousness of the disease and the possibility of a full-blown outbreak. This is exactly what BlueDot did before reports started coming from local authorities at the epicentre of the coronavirus pandemic.

Digital Tracking of the Outbreak

Digital tracking of the outbreak can help contain the disease and prevent further spread. AI can analyze data coming from a wide range of sources and predict the possibility of infections in other places. For example, flight data from the epicentre of the outbreak can predict the next possible hotspots. Similarly, since the spread also depends on the nature of the climate, AI can learn about the places where the spread is favourable.

This allows governments and local authorities to prepare with healthcare resources if a serious outbreak occurs.

AI-assisted Diagnosis and Testing

The coronavirus pandemic has exposed the limitations of available healthcare resources. The available manpower and technologies have been unable to prevent deaths even in countries with highly advanced facilities. By assisting in early diagnosis and testing, AI technology will prevent pandemics to spread uncontrollably. AI can help for medical imaging purposes which can be used to accelerate diagnosis and testing. Patients with possible warning signs can then be put in quarantine before the disease can spread.

Human Contact Minimization

There is a high possibility of spread in areas such as quarantine centres and hospitals. Since much of the spread is due to human contact, as with coronavirus, AI can be used to minimize this contact. Robots can be used to deliver food and medicine to highly infected patients. Similarly, as we prepare for a normal life after the coronavirus pandemic, we must consider the frequency of human to human interaction. There is a high possibility that robots will be used in restaurants and banking facilities for sterilization, cleanliness, and service delivery.

Personalized Information

It is rightly said that information is the most precious resource in the 21st century. And during pandemics, it is even more important. Social media sites have been providing information about the status of the outbreak in a person’s local area. This allows people to be more conscious and follow preventive measures. Furthermore, they have been able to separate the fake news from credible information. All of this is powered by the use of AI and big data in the background.

Vaccine Development

The use of AI in vaccine development is projected to grow in the coming years. AI can be used to study the nature of the human immune system and its response to a wide range of remedies. This will allow researchers to virtually test a wide range of options and develop the best remedies. Although this will not be a quick fix, the assistance of data-driven models will be highly valuable.

Even though the signs are promising, using AI technology to prevent pandemics is not free of challenges. Some of the major challenges are:

We do not yet have a system that can take all the factors into account while understanding the nature of the outbreak.
Not all information shared on the internet is credible. It is difficult to separate the facts from the lies.
Understanding the lifestyle of each and every person is impossible while predicting the possibility of spread.
Diagnosis and medical records can be difficult to gather because of privacy laws.
Imaging techniques cannot be relied upon completely because the symptoms can be hidden.
We do not have enough information on the nature and evolution of viruses and bacteria. This will create a major challenge in developing vaccines.

Conclusion

In this blog, we have learned how AI technology will prevent pandemics. Similarly, we also understood where we stand currently and the challenges we may face.

Technology news must be a top priority if you want to learn about the current state of the market and its possible evolution. As a highly reputed source of technology-related news, we at Top World Business make sure that you stay updated on the latest trends and receive the correct information. In this fast-changing world, we make sure that you won’t miss a high potential investment.

Battery Technologies: Charging Ahead to the Future

November 25, 2020/in Technology News/by Top World Business

Battery Technologies: The Present and the Future

Today, there is an increasing likeability and adoption of electric vehicles and battery-powered applications around the world. Therefore, a huge sum has been poured into the research and development of better battery technologies. This is necessary because energy storage devices like batteries must keep up in terms of efficiency with the devices they power.

What is the Battery?

A battery is a pack of a number of cells that store energy in the form of electrochemical energy and can be used to power various electrical devices. We need to supply external electrical energy in order to reverse the chemical reaction inside the cell for rechargeable batteries. Likewise, the components of an electrochemical cell include a negative electrode, a positive electrode, electrolyte, separator, and current collectors.

Battery Technologies: Present Status

Li-ion Batteries

Li-ion batteries have become quite popular in portable electronics due to their higher energy density, higher specific energy, and the abundance of Lithium metal on earth. The Li-ions formed are inserted in the crystalline lattice through a process known as intercalation. In simple terms, the transfer of Li between electrodes depends on the intercalation mechanism rather than the redox mechanism.

The present state of the art Li-ion battery technologies ensures better power efficiency for each cell. They can be discharged and recharged a number of times before the cell reaches the end of life. Likewise, recent advancements in Battery Management System have considerably increased the safety and stability of the battery pack. Furthermore, they have lower self-discharge rates compared to other batteries which give them an advantage.

The current Li-ion battery technologies are far better than they were before. However, they have not yet reached optimum improvement and there is still a lot to do. We must understand that today, people are much wary of how they utilize their time. Spending hours on charging devices and cars can diminish productivity and cause irritation. The charging time is not generally limited by the currently available battery technologies but by the power supply system from the grid. However, battery capacity and performance are highly dependent on the existing battery technologies.

Future Battery Technologies

Future Battery Technologies should ensure and take into account the following factors:

It must have enhanced battery performance and increased capacity.
The batteries must be recyclable to help maintain environmental sustainability.
They should be able to upscale to satisfy commercial needs.
It must address newer algorithms to prolong battery life.
It must be smart to increase safety and reduce internal cell ageing.
The materials used to build the battery should be abundant and easily available.

Battery chemistry ultimately means better battery performance and capacity. Let’s see what the future for Lithium Battery chemistries holds.

All-solid-state Lithium-ion

In the current Li-ion batteries, during discharge, lithium ions move from the negative electrode to the positive electrode. This is done by using the liquid electrolyte present in the cell. However, in all-solid-state batteries, the electrolyte present is a solid compound that facilitates the movement of lithium ions. Likewise, solid-state electrolytes are better in terms of higher thermal stability, higher safety, increased durability, and simplicity. Furthermore, if higher ionic conductivity can be ensured, this technology is very promising.

Lithium-air

The Li-air battery is a kind of metal-air battery and has gained attention due to its very high theoretical energy density. In this battery, lithium oxidizes at the anode and oxygen reduces at the cathode to induce a current flow. Likewise, it also has a very high specific energy and is generally comparable to the specific energy of gasoline. However, its design faces a lot of challenges in cathode selection, electrochemistry, and stability.

There are other post-lithium battery chemistries that hold the potential future as advanced battery technologies.

Sodium-ion Batteries

Na-ion batteries are similar to Li-ion batteries. However, they use sodium ions as charge carriers. These batteries deliver very high specific power, cost less, and ensure high safety. Likewise, the materials used are abundant on earth and these batteries are highly efficient. However, it is a less developed technology and is undergoing research to make it commercially feasible and viable.

Conclusion

From this blog, we have now become familiar with the present state of battery technologies and what the future holds for this exciting field.

Technology news must be a top priority if you want to learn about the current state of the market and its possible evolution. As a highly reputed source of technology-related news, we at Top World Business make sure that you stay updated on the latest trends and receive the correct information. In this fast-changing world, we make sure that you won’t miss a high potential investment.

Top Machine Learning Algorithms You Must Know

November 22, 2020/in Technology News/by Top World Business

Top Machine Learning Algorithms: What You Must Know

Machine learning is one of the most exciting technologies that exist today. It has been able to attract a large number of interested learners and industry professionals. Machine learning algorithms allow a computer to learn from data without having to be manually programmed. In traditional computing, the user provides input and commands which the computer will execute to produce output. However, in applications where writing a manual program is not feasible for a wide range of situations, machines are taught to learn from incoming data and make its decision.

Over the past few decades, machine learning algorithms have found applications in a variety of fields from healthcare and finance to astronomy and warfare. One of the major reasons is the accelerated development of processor manufacturing technologies. Since machine learning algorithms tend to work with enormous amounts of data, it requires high computing power. Furthermore, cloud service providers like Amazon, Google, and Microsoft have made access to powerful machines easier.

There are four major categories of machine learning algorithms. We will learn about the top algorithms in each of the major types.

Supervised Learning Algorithms

In supervised learning, both the samples and their corresponding labels are passed to the machine learning algorithms. The algorithm learns from the training data and develops a model that is used to predict the results of unlabelled samples. Classification and regression are the two major types of supervised learning algorithms.

The top machine learning algorithms for supervised learning are:

Linear Regression

Linear regression is one of the most basic machine learning algorithms which you will typically learn in the first place. In this case, you will provide samples of data containing an independent variable and a dependent variable. Then, you will fit a function (typically a straight line) which will describe the relationship between those variables at best.

Let us consider that your data shows the number of flights per year over the past few decades. With linear regression, you can fit a model that can be used to predict the number of flights in the future.

The regression model is defined by the equation of a straight line

y = ax + b

Here, y is the dependent variable and x is the independent variable.

The values of a and b come from minimizing the defined cost function, which is typically the sum of squared errors. Here, the error is the difference between your input data points and the data points defined by the model.

Logistic Regression

It is one of the most basic machine learning algorithms used for classification. It is used to classify a data sample into two or more categories. If the number of categories is 2, it is called binary logistic regression whereas if there are more than 2 categories, it is multinominal logistic regression. This algorithm makes use of what is called an activation function which is used to map obtained values as probabilities. These obtained probabilities define the category of the input sample.

Consider a model that classifies whether an email is a spam or not. A feature vector keeps the information of the sender address, and frequency words like ‘discount’, ‘offer’, etc. You can use this to train a logistic regression model which will produce different values for spam and non-spam emails. The algorithm maps these values to different probabilities which then defines the category.

Decision Trees

Decision trees are also one of the most commonly used machine learning algorithms for both classification and regression. It consists of a tree-like structure formed by splitting the original set into multiple subsets. The flow advances from the top of the tree to the bottom node through these subsets where there is a test of a property. Classification is done based on the results obtained from each property test. Similarly, in the case of regression, you make a prediction using information from the same test.

kNN (k- Nearest Neighbors)

This is also one of the supervised machine learning algorithms used for both classification and regression. This algorithm decides the class of a sample based on the information about its neighbours. Consider a classifier that categorizes the image of fruit into ripe and raw. First, it maps the sample fruit into a feature space and inspects the status of its neighbours. Since similar types of samples are likely to be located closely, Since similar types of samples are likely to be located closely, you can then obtain the class. Despite its versatility and higher accuracy, it is still computationally expensive.

Unsupervised Learning Algorithms

In unsupervised learning, the algorithms work with unlabelled data i.e. the samples do not come with corresponding results. Therefore, there is no need for prediction. Clustering, or the segmentation of samples into different groups, is a type of unsupervised learning.

The most common machine learning algorithms used for unsupervised learning are:

k-Means Clustering

The major objective of k-means is to segment unlabelled samples into a number of groups or clusters (the number is defined by k). Consider a customer segmentation application. The application will take into account the purchase history, types of goods, and purchase amounts and map this information into a feature space. Similar types of customers will yield information that is likely to be closer in this feature space. k-Means will form a boundary between a cluster of data points that separate different types of customers.

Dimensionality Reduction Algorithms

Most of the machine learning algorithms typically work with large amounts of data. However, sometimes, the dimensions can be too hard to handle. This is true when you should consider a lot of features while developing models. Not all of these features are significant enough to be considered. The purpose of dimensionality reduction is to leave out insignificant features to increase the speed and efficiency of learning. Principle Component Analysis is a popular algorithm used for this purpose.

Reinforcement Learning Algorithms

Reinforcement learning algorithms are based on taking actions to maximize rewards in a particular situation. In contrast to supervised learning where the answer is known already, the agents learn from their experience and improve continuously. The application areas of reinforcement learning include robotics, industrial automation, and business management.

Conclusion

In this blog, we have learned the top machine learning algorithms that you should know and where they are applicable.

Technology news must be a top priority if you want to learn about the current state of the market and its possible evolution. As a highly reputed source of technology-related news, we at Top World Business make sure that you stay updated on the latest trends and receive the correct information. In this fast-changing world, we make sure that you won’t miss a high potential investment.