Imagine this…

You have a brilliant mobile app idea. You want to make a mark in the world.

That’s good. We understand your excitement.

But if you’re developing a mobile app for the first time, then there are certain mistakes that you’re bound to make.

You see, the journey of launching a successful mobile app starts with hiring the right mobile app developers. And if you make the mistakes that we’re going to discuss in this article, then your mobile app will fail for sure before it has been launched.

Why?

It’s because only the right development team can help you set off the right foot on the success journey.

And if you hire the wrong team, then you’ll end up wasting a lot of time & money.

The worst part? — you’ll not get the desired application that you imagined and all your efforts will go ashtray.

So, if you’re going to hire mobile app developers, avoid the following 5 mistakes to set your mobile app up for success.

5 Mistakes to Avoid When Hiring Mobile App Developers

Nowadays, almost every small-to-large businesses are developing their own mobile apps for obvious reasons.

Let’s dive in and take a look at the deadly mistakes that you should avoid at all costs.

1 — Not Looking for Developers Outside Your City

The first mistake that most entrepreneurs & businesses make is looking for mobile app developers only within their locality.

While it’s definitely a privilege to be able to meet in-person with developers.

But when you choose to go this way, your options become very limited.

For instance, let’s say that you live in Sydney, Australia and you want to hire mobile app developers who are from this city.

Now, if you’re lucky, you may find a good developer, but you’ll still miss out on great developers outside your city simply because you put a limit on your options.

The point is, in today’s digital world, location doesn’t really matter for mobile app developers.

In fact, many businesses as well as brands like Alibaba, Apple, and others have embraced the idea of outsourcing their mobile app development projects outside the city or country.

2 — Not Conducting Proper Interview of Candidates

Many businesses make the mistake of not conducting a thorough interview of mobile app developers.

They often find references of developers from friends, former colleagues, or from family members, then take a look at their resume and portfolio and hire solely on the basis of that.

Now, think for a minute. You’re going to invest probably thousands of dollars in developing your app.

Are you really going to make the hiring decision solely on trust?

We really hope that you don’t!

Or it may lead you in a situation where the developer doesn’t communicate often enough or well enough and you may not be able to take appropriate action.

So, schedule an interview with qualified candidates and see if they have the ability to translate your vision into a useful mobile application.

3 — Hiring Developers Solely Based on Experience

Sure. Experience matters.

But there is another aspect that should not be overlooked while making the hiring decision.

Expertise.

Expertise is equally important when you’re hiring mobile app developers.

You see, it’s not necessary that hiring the highest experienced developer will be capable of developing your specific mobile app.

This is where expertise comes into the picture.

When you’re interviewing qualified candidates, look at their past work to see whether they have developed a similar app and how did they app turned out to be.

This brings us to the next mistake.

4 — Not Analyzing Their Past Work

If you’re developing let’s say a food ordering app for your restaurant business, it is recommended that you look for developers who have developed a similar app in their past.

Checking the past work thoroughly is equally important to experience.

In fact, you should also download all the applications which the developer has built in the past.

While it may take some time for downloading and signing up, but this exercise will help you evaluate the work they have done before and also get an idea of what quality you should expect from them.

5 — Hiring Developer Based on Price

When you’re a small business or an entrepreneur, it feels right to hire the cheapest or the most affordable option available.

This is especially true when you have to stick to a budget. And we understand that very well.

But, making this mistake will actually cost you more money.

Moreover, it’s just impossible to develop a mobile app which is of high quality and very low in the price unless it is a static mobile app.

So, avoid developers or companies that promise to do the job for a low price. Instead, find a solid developer who has developed successful apps in the past and hire them quickly as these developers are always in high demand.

Summary

To summarize the article, here’s what you need to do:

• Find developers outside your city
• Interview the qualified candidates thoroughly
• Verify their credentials by checking their past work
• And hire developers who have experience in developing a similar app.

If you still have any doubts regarding your project, feel free to contact or hire mobile app developers from Credencys.

Avoid These 5 Mistakes When Hiring Mobile App Developers was originally published in Quick Code on Medium, where people are continuing the conversation by highlighting and responding to this story.

Front-end Development and Back-end Development — What is the Difference?

Whether you want to build a web application or a mobile app, front-end and back-end development is an integral part of it.

If you are a non-technical person, then you won’t be able to understand the difference between front-end development and back-end development. Both the development has a different set of technologies to build a robust working web or mobile solution.

Are you sure you will be able to pick the right set of technologies for the front-end and back-end development of your application?

It seems challenging. Am I right?

Not anymore!

I would like to help you by providing you a detailed insight into both types of development. It will remove your confusion and help you to understand the cohesion between front-end and back-end development.

Front-End

When the user types the URL of your website or web applications and downloads your mobile application, they view an interface with the ultra-clean layout of it. This user faced interface is called front-end in the technology arena.

It is a very critical component as the user gets engaged with your application only if you have easy to use and fully functional interface. To stay competitive, it is very essential to build a robust front-end that works flawlessly.

What Is Front-End Development?

As I mentioned earlier, everything that users can see and interact on your website falls in front-end development. Front-end development mainly focused on creating the user interface and user experience for web and mobile solutions.

All the elements such as slider, dropdown menu, layout, fonts, colors, etc. are the part of front-end development. HTML, CSS, and JavaScript play a crucial role in creating the eye-catchy front-end.

Before designing the final user interface, it is essential to create mockups, wireframes, and clickable prototypes. It helps you to identify the issues in the user experience of your application. And, if you know the issue, it becomes easy to resolve it and make the influential front-end.

To create a perfect front-end for your mobile or web application, it is very essential to partner with the reliable web development service provider that understands your specific needs, goals, and opportunities and offers front-end development accordingly.

What Are The Front-End Development Languages?

HTML

HTML is the abbreviation of Hypertext Markup Language. It is used to design the web pages using the markup language.

It is the combination of Hypertext and Markup Language. Hypertext defines the links between the pages. On the other hand, the markup language is used to define the structure of web pages.

CSS

CSS stands for Cascading Style Sheets. It is a design language that simplifies the process of making application pages presentable by allowing developers to apply different styles to the web pages. Most importantly, CSS works independently than HTML to make up for each web page.

JavaScript

JavaScript is an immensely popular language that helps in making applications interactive for users. It is used to enhance the functionality of the website to run web-based software or cool games.

What Are The Front-End Development Technologies?

There are many front-end technologies available in the tech world. We are going to discuss a few of them here.

AngularJS

AngularJS is an open-source JavaScript framework that is mainly used to build single-page web applications. It is one of the continually evolving front-end technologies that enables developers with better ways to build web applications.

It holds the capability to convert the static HTML into the dynamic one. Being an open-source technology, it can be changed by anyone and used freely.

React JS

It is a flexible, effective, and declarative JavaScript library for front-end development. It helps in developing a brilliant user interface. ReactJS is a component-based and open source library that is a responsible view layer of the application. The technology invented and maintained by Facebook.

Bootstrap

It is an open-source and free tool for developing responsive web applications and websites. Bootstrap is the most popular JavaScript, CSS, and HTML framework that allows to build mobile-first and responsive websites.

Back-End

As the term itself suggests, it’s a set of technologies that manage server-side and database related processes of your website or web application or mobile solution.

What Is Back-End Development?

The back-end is a server-side development in the software development process. It stores and manages the data and makes sure everything works seamlessly on the client-side of the website.

It’s a part of the software development process with which users cannot interact as well as see it. It processes the actions taken by users on the front-end. Thus, users can indirectly access the back-end of the users.

Back-end development involves a bunch of activities that consist of working with system components without the user interface, writing APIs, creating libraries, integrating databases, and more.

What Are The Back-End Development Languages?

When it comes to back end development, you have many options in terms of programming languages to choose from for your application. Let’s check out the back-end development languages one by one.

C++

C++ is a widely used programming language nowadays for competitive programming. It is popular as a back-end language too.

PHP

It is a server-side scripting language specifically designed for web application development. As PHP is executed on the server-side, it is popular as a server-side language.

Node.js

Node.js is a cross-platform and open-source run time environment that allows to execute the JavaScript code outside the browser. It is neither a programing language nor a framework.

It is used to develop back-end services like APIs for mobile or web apps. Node.js is highly used by Fortune 500 companies like Uber, PayPal, Wallmart, Netflix, etc.

JavaScript

It can be used as back-end or front-end programming languages.

Java

Java is one of the most popular programming languages and widely used by the developer community. It is a highly scalable platform as the components of Java are easily available.

Python

Being one of the leading programming languages, Python allows developers to integrate the systems efficiently and work or quickly.

What Are The Back-End Technologies?

If we talk about backend technologies, it contains various frameworks and libraries. There are a lot of leading back-end technologies, but here we are considering a few that are highly used.

Express

Express is a free and open-source framework of Node.js that is used to build web applications. It is released under MIT license. It allows to build APIs and web applications.

Laravel

Laravel is a free and open-source PHP web framework. It simplifies the common tasks that are used in the majority of web development such as caching, routing, authentication, and sessions. It eases the development process for programmers without compromising application functionality.

C#

C# is a flexible and powerful programming language. It can be used to build a wide range of applications. The technology is used for diverse projects such as development tools, websites, and even compilers. C# helps in creating object-oriented programming languages.

Conclusion

To build a powerful application with front-end and back-end, you need to understand the difference between the types of development. It is very essential to choose the right one from a wide range of technologies. I hope this post provides you with insights about both the front-end and back-end technologies.

Still, if you have confusion in selecting the right set of technologies, consult with a reliable web development service provider who ensures you about the successful development and implementation of your project.

Front-end Development and Back-end Development — What is the Difference? was originally published in Quick Code on Medium, where people are continuing the conversation by highlighting and responding to this story.

Artificial Intelligence has made an impact on our lifestyles. For some time now, it has been making its space in the digital signage world.

AI is transforming digital signage and offering new and better opportunities to its users. Today, we are focusing on those opportunities and see the most critical facets of the combination of AI and digital signage.

Currently, you will conclude that Artificial Intelligence would enhance the capabilities of digital signage. It will use all the data it has to work with to improve how content is created and displayed to the target audience.

Digital signage is a multifaceted tool, and the addition of Artificial Intelligence expands that versatility and ensures it gets as smooth as it can be.

Now, let’s have a look at how Artificial Intelligence and Machine Learning has impacted the world of digital signage.

1) Simpler data collection

The primary purpose of digital signage is to disseminate information. However, today it has emerged to the point where you can collect data with the help of AI.

Using next-gen digital signage solutions with components like facial recognition, retailers can have a more distinct understanding of who their customers are.

Since facial recognition comes with its honest share of privacy concerns, the acquired data can impact business strategies or directions in which a firm may go to accommodate their audience. Moreover, digital signage can take the collected information and even use it in real-time.

2) More personalized user experience

As human beings, we are emotional at heart. In fact, something as cold and lifeless as robots and AI can provoke emotion in us. Research has even shown that despite knowing the nature of AI, people still respond to it as if it were a real person. That is why AI brings a new paradigm to the personalized user experience digital signage already offers.

In digital signage, a customer feels special if the technology treats them in a more personal way. Artificial Intelligence learning enables digital signage to learn and interact with real people in a unique way.

Digital signage AI can recognize a client and greet her or him. It can communicate the product offers and discounts based on the person’s purchasing history, and more.

3) More interactive interface

While personalization is an exciting element, when it comes to transactional purchasing, every customer appreciates efficiency.

Interactive in-store digital signage is always an option. Consumers can see available products, their features, and get more information quicker without waiting for a staff member. Some people might even favor browsing without interruption.

In the future, AI will make the shopping experience better for customers. For example, a customer will be able to bring one or several items to a nearby display to examine prices and characteristics.

Digital signage might even enable comparing two products in no time. This can genuinely help to deliver omnichannel shopping experience by bringing many components of online shopping to the real world.

4) More relevant content

We’ve mentioned promoting special discounts based on previous purchases of customers. This aspect of Artificial Intelligence can also come into play in producing content. This data can help digital signage to display specific ads.

On a rainy day or in chillier weather, some products may be preferable to others. You will observe the umbrella vendors come out in real life.

Likewise, weather information can automatically adjust digital signage content and probably affect purchasing decisions. Ads could be displayed based on not only analytics but also based on weather, time of day, week, year, and more.

5) Better advertisement scheduling

Artificial Intelligence is much more than a technology that identifies a customer’s face. AI also plays a vital role in purchasing ad space.

It has been here around online for quite some time in the area of showing programmatic ads. It allows the delivery of relevant content and makes real-time bidding more effective.

Applying this concept to digital signage for retail, proper ad placement can be accelerated. Retailers can take part in programmatic advertising, buying ad space on digital signages worldwide. The efficacy of these ads would be similar to online ads, as digital signage AI uses data about the customers to select which ads to show to them.

As AI further develops and merges with technology like digital signage, the level of personalization will grow to a great extent. The question is only how far. Productivity will increase as a result of Artificial Intelligence. With digital signage already making customer experience in retail more comfortable for the customer, AI will push this even further. The ease with which consumers find the products and the speed with which they become aware of products suited for them will grow, as well.

6) Deep Learning and AI

Deep learning is a subset of ML (machine learning) in Artificial Intelligence, where artificial neural networks emulate the human brain in processing information and creating patterns for use in decision making.

AI-powered engines have access to vast amounts of data. With deep learning, AI-driven platforms can assess large data sets, mostly in real-time, leading to specific reactions.

With more precision and data processing comes a more solid understanding of the users. But Artificial Intelligence doesn’t necessarily think for you. It’s all about automation. It draws conclusions, detects patterns, and responds to situations.

7) Context-aware digital signage

The adaptability of smart digital signage allows for different content to be scheduled and displayed at distinct times of the day or even days of a week.

Content can also be presented in real-time to reflect quickly-changing environments. For example, context-aware digital signage can show content relevant to the weather outside: ads for sunglasses when the sun is shining, or ads for umbrellas can automatically be shown when it rains.

Conclusion

It can be concluded that AI and digital signage go together hand in hand. The market of digital signage is expected to grow to $32.84 bn by the year 2023, and the market of AI as a whole to $191 bn by the year 2024.

Both of them have a bright future, from not only a market growth perspective but also the perspective of new developments.

Several aspects of Artificial Intelligence are already becoming a part of the digital signage world, and it is only a matter of time before they become the famously accepted match.

7 ways AI is taking Digital Signage to The Next Level! was originally published in TDS Archive on Medium, where people are continuing the conversation by highlighting and responding to this story.

The DevOps turned 10 last year.

But, despite being in the market for over a decade, most organizations don’t seem to have much clue as to how to implement it.

It’s like the saying that goes “Progress comes with Challenges” & DevOps is no different.

DevOps, for those who don’t know, is basically a set of software development practices that help to shorten the development cycle, while increasing the frequency of updates, features, and fixes.

Although there are many companies, big & small, that are progressing towards adopting the DevOps model into their operations. For instance, the DevOps adoption rate reached 17% in 2018 from about 10% in 2017.

A simple Google Trends search also shows a consistent upward growth of DevOps.

But, despite DevOps’ increasing popularity, organizations are facing many challenges while implementing DevOps in their day-to-day operations.

In this article, I will share the top 3 DevOps adoption challenges and how organizations can overcome them in the best way possible.

Top 3 DevOps Adoption Challenges

Though DevOps is famous for achieving automation, but implementing DevOps correctly is an extremely challenging task.

Below, we will look at the top 3 DevOps Adoption Challenges and ways to resolve each challenge during the DevOps implementation process.

Let’s get right into it!

1 — Migrating From Legacy Systems to Microservices

Old infrastructure, even though it has served an organization for years, can still be pretty problematic.

For instance, old infrastructure might cause a lack of support, stability problems, and not to mention the biggest risk of falling behind the rapidly advancing competition.

DevOps, on the other hand, can solve this problem through microservices.

Microservices is basically an architectural pattern in which the individual pieces of functionality are encapsulated in microservices to form a whole system.

Microservices together with Infrastructure-as-a-code can help to achieve continuous innovation.

To put it simply, microservices can modify the software development cycle in a way that can help organizations quickly adapt to the changing needs of their customers.

However, replacing microservices with old infrastructure comes with its own problems that must be managed. For starters, an organization must partner with DevOps services company to establish required foundations of automation, continuous delivery, and configuration management in place to cope up with the increased workloads that come with microservices.

2 — Overcoming the Dev Vs. Ops Mentality

The “DevOps” term basically means “Development + Operations” and it is all about integrating both teams together to ensure that both teams share the same priorities and goals.

In simple words, team integration & collaboration is at the heart of DevOps, and it is the main hurdle an organization must overcome to successfully adopt DevOps in their day-to-day operations.

The best way to overcome the dev vs. ops mentality for any organization is to encapsulate better collaboration practices. For example, instead of working at cross-purposes, both the dev and ops team focus on one common goal.

There are, in fact, many organizations moving towards creating a cross-functional, product-aligned team rather than managing projects. This basically allows an organization to bring developers, testers, and business representatives on the same page through the collaborative process.

This, as a result, helps an organization to boost the developers’ productivity and thus the development speed of their project.

3 — Focusing too Much on Tools

When you’re implementing DevOps for the very first time, it’s tempting to use as many DevOps tools as possible.

While the flashy tools of DevOps may seem like they’re the right answers to all your problems, but in reality, much of the DevOps adoption success depends on your team and your organizational structure.

Let me explain…

Tools indeed play an important role in successful DevOps implementation, but an organization must also focus on training their staff to use them correctly.

In addition to this, it is also equally important to ensure that the tools you’re using meets all the security requirements and are well-integrated into your existing infrastructure.

Simply put, it is of utmost importance that you, as an organization, focus on your team rather than tools. Once you’ve defined the correct structure and processes, you can easily determine the right tools needed to meet the processes.

Therefore, focus on your team more than tools and make sure that they’re well-trained for the newly implemented processes and chosen tools.

Concluding Thoughts…

These are the main 3 DevOps adoption challenges that, if you overcome successfully, will definitely make the DevOps transition a lot smoother.

Though there will be discomfort at the beginning but with the right DevOps partner, you can rest assured that the pay off will be huge in the long run.

If you’re interested, we’ve also written a comprehensive article on how to apply DevOps in your Product development. Be sure to check that out!

Top 3 DevOps Adoption Challenges & Best Ways to Overcome Them was originally published in Quick Code on Medium, where people are continuing the conversation by highlighting and responding to this story.

Digital wallets have grown significantly in the past 5 years.

For example, the worldwide digital wallet transactions reached $4,296 billion USD in 2018, and the same is expected to reach $13,979 billion USD by 2022.

What’s more surprising is that the innovations in digital wallets have just begun. In the next 3–5 years, more and more digital wallet technologies will emerge, which will make digital payments more secure and convenient in the near future.

So, if you’re an entrepreneur looking to build a digital wallet app, then you must know about the digital wallet trends that will dominate in the near future.

In this article, I will share 5 most innovative digital wallet trends of 2020 & beyond.

5 Digital Wallet Trends to Look Out for in 2020

Let’s look closely at the most innovative mobile digital trends that will be a big hit in 2020 and beyond.

1 — Cryptocurrency Wallets

Cryptocurrency, in case you didn’t know, is no longer reserved for the multi-million dollar brands or exclusive investors. It has been widely adopted by startups to small-to-medium businesses.

As a matter of fact, there are millions of cryptocurrency wallet app solutions.

According to Statista, the number of cryptocurrency wallet solutions have drastically increased since 2016, from 6.7 million to 42 million in 2019.

The reason behind this drastic growth is also quite obvious!

For instance, the cryptocurrency & blockchain technology basically eliminates the need for a third-party in a transaction, which not only leads to more secure transactions but also lower costs.

As a result, the businesses or startups that have incorporated this technology are witnessing enormous benefits and it will continue in the future as well.

2 — Smart Speaker Payments

Smart Speakers have witnessed dramatic growth since Amazon launched the first-ever smart speaker in 2014.

In fact, soon after the launch of Amazon’s smart speaker, Apple and Google both joined the race of smart speakers with Google Home in 2016 and Apple smart speaker in 2017.

Today, smart speakers or voice assistants have become quite mainstream among the majority of households.

According to Statista, 82 percent of people have used the voice assistant to retrieve information, while 35% of people have bought products through voice assistants and smart speakers.

And as far as online payments are concerned, 28% of the smart speaker users have made direct payments for purchases and send money.

Though the number of users making online payments using smart speakers is considerably less as of now, but the number is forecasted to rise in the near future as soon as the smart speaker technology becomes more convenient and secure.

In fact, the future of smart speakers being used for making payments already looks promising in the United States.

Business Insider forecasted that the usage of smart speakers for making payments will increase from 18.4 million to 77.9 million users by 2022.

So, overall 30 percent of US users would start making online payments using smart speakers in the next 3–5 years.

3 — NFC-Based Wallet Solutions

In the last five years, the usage of NFC-based or contactless wallet solutions in the UK has increased considerably.

For instance, 2014 was the biggest hit for contactless payments in the UK. The total contactless spending set a record of reaching £2.32 billion, a whopping 255% increase from the last year’s figure.

What’s even more surprising fact is that by the year 2017, a total of 119 million contactless cards were issued in the UK, which is nearly 2 cards per person.

According to UKFinance, two-third of UK adults shop or pay using contactless payments.

So, now that you know how much popular contactless, or NFC-based payments are, it’s time to learn how Contactless or NFC-based Wallets actually work.

Basically, today’s smartphones come with NFC technology through which they communicate with the NFC card machines.

Though most smartphones need not touch the point of sale device in order to make the payment, however, they do have to be in close proximity from the terminal.

As far as the demand for NFC wallet solutions is concerned, the NFC technology has already gained a tremendous amount of popularity as we saw earlier, which means building an NFC-based digital wallet app development is definitely a worthwhile investment.

4 — AI-Based Wallet Solutions to Automate Routine Transactions

Artificial Intelligence (AI), just like NFC technology, has rapidly made it’s way to being one of the best-emerging technologies. And not only that, but AI technology has also improved drastically over the span of the last 5 years.

For example, nowadays a lot of ecommerce companies have employed AI-based chatbots who help these companies & brands address their customers’ concerns.

And as far as the digital wallets or mobile payments are concerned, AI chatbots have become capable of enough to be useful in executing and automating basic transactions with customers’ approval.

In fact, AI can now also handle voice instructions and execute payments related to routine tasks such as number verification or ACH payment processing automatically.

5 — International Remittance

International remittance is basically a transfer of money from a foreign worker to their family, friends, or other individuals in their home country.

In fact, international remittance, in many countries, constitute a significant portion of a country’s GDP.

According to the World Bank’s latest Migration & Development Brief, the total amount of global remittance in low and middle-income countries reached $529 billion in 2018, while in high-income countries, this number reached $689 billion in the same year.

And guess what? — one of the reasons behind this high growth of international remittance is the penetration of smartphones and the heavy adoption of digital wallet solutions.

Smartphones and digital technologies have quickly transformed the entire landscape of remittance and the overall finance industry.

Concluding Thoughts…

Digital wallet solutions or mobile app development in general have hugely impacted the finance sector, and it is expected that it may soon become the default mode of payments in the near future.

As of now, these are the main 5 digital wallet trends of 2020 that are most innovative. So, if you’re an entrepreneur interested in building a digital wallet app solution of your own, be sure to keep these 5 trends in mind.

5 Most Innovative Digital Wallet Trends of 2020 was originally published in Quick Code on Medium, where people are continuing the conversation by highlighting and responding to this story.

Artificial Intelligence and space technologies have a close relationship. Space research and exploration was one of the first fields to implement AI in its daily operations.

One of the key reasons for using AI in space exploration is because it has to deal with a lot of data. With so much data to process, one cannot wholly rely on human intelligence. AI is helping us by reducing human errors and making the estimations close to reality.

Let’s have a look at how AI is benefiting humankind by contributing to space exploration and research.

#1 Earth Observation

We have been utilizing satellites for communication, navigation, remote sensing, etc. for almost half a century now. AI has been helping us to use this technology more efficiently and effectively.

One of the main tasks of satellites is to collect and transmit data back to us. In its entire lifetime, satellites collect a lot of data. A majority of it is useless. AI is beneficial to figure out which data makes sense.

Machine Learning algorithms are applied to analyze an enormous quantity of data. These algorithms analyze data in a matter of minutes, which helps us to get vital information quickly.

A good example could be the safeguard measures placed in the areas of migration. Apart from these, there are many other applications of AI that helps us understand our earth better.

#2 Urban Planning

Since AI is already helping us to map earth in a better way, it helps us to plan and design urban areas in the best possible way. Satellites are used to take pictures of land for plotting.

Moreover, satellites and AI can also be used to manage traffic across a city or a town. AI can provide a suggestion to manage traffic in dense traffic areas.

Since the world is moving towards renewable energy sources, it also helps us to identify the best place to place wind turbines, or water turbines, or solar panels for optimum results.

Based on this data, we can plan our cities accordingly and pave our way for a more sustainable future. Ultimately, AI will help us create a better environment by ensuring the places we work and live keep up with today’s demands.

#3 Renewable Energy Prediction

AI is helping the weather forecast department by helping them to identify the weather patterns beforehand. Using satellite as the primary input device, AI is helping us to predict weather patterns.

For example, it helps us to identify where in the world the intensity of tides is higher. Based on this information, we can take the maximum advantage of tidal energy to convert it into electrical energy.

The more we understand our renewable sources of energy, the more advantage we can take of them to make our earth more sustainable. More and more countries have started to leverage AI to optimize the usage of renewable energy sources.

#4 Pollution Monitoring

AI helps to reduce pollution in many different ways. One of the latest ways in which it is helping us is by sending signals to the other nearby ports and ships if a certain port is crowded or congested.

This will not only help to manage traffic at ports but also help to reduce pollution near ports and cities. Using satellites, it can help reduce the negative consequences caused by shipping.

With the help of satellite images, AI can figure out the safest and fastest route for shipping. It will help us to optimize the shipping process globally.

#5 Transportation

AI and GPS location tracking can revolutionize public transportation. For example, AI can detect humans at the bus stop and notify the bus driver as to how many passengers should he/she expect at a particular stop.

It can also help soldiers with transportation by detecting malicious activities on their route. Apart from this, train maintenance is also an area where it can bring massive benefits.

Machine Learning algorithms can help us determine the carriages that require special attention by looking at the satellite images. Overall, AI and space technologies will streamline the transportation of anything or person.

Conclusion

Companies and Innovators can continue to take benefit of business opportunities presented by the combination of AI, ML, and space technologies. As technologies advance, our everyday lives will continue to progress thanks to these and new advancements.

Written by Sandeep Agarwal, CEO at Credencys, an iPhone app development company.

How AI is Upgrading Space Technologies for a Greater Good? [Top 5 Areas] was originally published in TDS Archive on Medium, where people are continuing the conversation by highlighting and responding to this story.

During Google I/O 2017, Google announced Kotlin as an official programming language for building Android apps.

Though the announcement was a bit surprising for the Android development community since Java had been the preferred language for developing Android apps.

However, it’s been two years now, and since then Kotlin’s popularity has only increased.

For instance, a quick search on Google trends proves that Kotlin is picking the pace fast than imagined.

Thanks to the solid support from Google and Jetbrains, both developers as well as businesses, Kotlin’s adoption is on a quick rise.

In fact, according to Kotlin’s official website, many tech giants including Uber, Evernote, Pinterest have adopted Kotlin for their Android version of mobile apps.

If you’re also considering to use Kotlin for your next Android app project, be sure to first understand what exactly Kotlin is, its benefits, and disadvantages of this programming language.

What is Kotlin?

Kotlin is an open-source, statistically-typed programming language created by JetBrains.

It was named after Kotlin Island which is located near St. Petersburg, Russia and it basically allows creating code that can seamlessly run on the Java Virtual Machine.

Although, Kotlin’s syntax is not compatible with Java, the common-used language for developing Android apps, however, it can easily interoperate with the Java code.

In laymen’s terms, Kotlin code can easily work with Java exactly the way it does natively.

Apart from this, JetBrains has also enabled Kotlin to use aggressive inference to decide the type of expressions and values in case they weren’t defined by Android app developers.

This, in turn, makes Kotlin even more distinctive than Java. Kotlin tutorials are a great way to learn more about Kotlin for Android beginners

However, the aim of this article is not to compare Kotlin with Java. Rather, the main focus is to discuss the pros and cons of using Kotlin for Android app development and determine whether it’s the right technology for your project.

Let’s start with the pros.

Pros of Kotlin for Android App Development

Kotlin is clearly loved by companies as well as Android app developers. Here’s the list of Kotlin advantages that makes it the prime option to build Android apps.

1 — Interoperability with Java Code

Kotlin is 100% Java-Interoperable programming language, which means switching from Java to Kotlin is a piece of cake for experienced Android app developers.

This is possible because Kotlin is consistent not only with Java but also with its frameworks and tools. And in case you have an existing Android app developed using Java language, you can still write new features or simply update your Android app in Kotlin language.

2 — Easy Maintainability

Most of the IDEs available in the market today provide support for Kotlin, which ultimately helps in maximizing productivity as it eliminates the need for learning new IDE for the developers.

3 — Boosts Team Efficiency

Thanks to its intuitive and succinct syntax, Kotlin is a compact and clean programming language that boosts team efficiency to a great extent.

In laymen’s terms, developers can get more work done using Kotlin compared to Java, as Kotlin takes fewer lines of code to build and deploy Android applications.

4 — Kotlin is Much More Reliable

Compared to other emerging programming languages such as Flutter, Kotlin is a much more mature programming language. It first came into existence in 2011.

As far as reliability is concerned, ever since Kotlin’s inception, it has gone under numerous Alpha and Beta tests before JetBrains finally released its final public version.

In fact, JetBrains also made Kotlin’s latest version reversely compatible with many of its previous language versions, giving much more reliability for the existing Kotlin-based Android apps.

Cons of Kotlin for Android App Development

Just like anything in life, Kotlin is not a perfect programming language. And if you’re going to use Kotlin to build Android app for your startup, business, or Enterprise, it’s imperative to take its cons into account before making the final decision.

1 — Fluctuation in Compilation

In many cases such as performing incremental builds, Kotlin is faster than Java, there is no doubt about it. However, Java remains a clear winner when it comes to creating clean builds for Android apps.

2 — Less Talent for Hire

Although, Kotlin’s increased popularity, especially after Google announced it as the first-class Android app development programming language, has certainly increased the number of Kotlin app developers in the market.

There are, however, still less number of Kotlin developers available in the market compared with Java developers.

3 — Limited Learning Resources

Though the number of Android app developers switching to Kotlin is increasing almost every day, there is still limited number of resources available in the market to learn and master Kotlin.

This basically leads to extra time to try and figure out how to do or build certain things in an Android app using Kotlin programming language.

The good news is, a lot of Android app development companies have mastered the language even with limited resources, so building a seamless Android app for your business using Kotlin is no longer an issue.

4 — Kotlin is Still Not Java

While Kotlin and Java have a lot of similarities, making the switch from Java to Kotlin will take some time for developers to get familiar with how everything works in the Kotlin programming language.

This means if you’re an existing Java-based Android app and want to switch it to Kotlin, additional expenses for training the team will be definitely required.

Final Thoughts…

Having official support from a tech giant Google is definitely a clear sign that the future of Kotlin is bright.

However, this doesn’t mean that you need to hurry in replacing your existing technology stack with Kotlin. So, even if you have an existing Android app, try baby steps instead.

What I mean is, instead of rewriting the entire application in Kotlin, you can build the next feature in Kotlin. This will help you get better familiarility with Kotlin while still maintaining an efficient Java-based Android app.

Pros and Cons of Kotlin for Android App Development was originally published in Quick Code on Medium, where people are continuing the conversation by highlighting and responding to this story.

Deep learning technology has impacted almost every other industry. Sports is no different. Deep Learning is helping businesses associated with sports to expand.

From NHL to MLB, NBA, NFL, and NASCAR, almost every major sports league in U.S.A is now incorporating AI to expand its business.

According to Statista, the North American sports market is predicted to reach $80.3 billion in 2022. The revenue may come from merchandising, gate revenue, media rights, and sponsorships.

The Ultimate Learning Path for Deep Learning in 2019 & more... | Data Driven Investor

There are many different areas in the sports industry, where AI plays an important role. For example, wearable technology, marketing, automated journalism, and incorporating computer vision.

These smart Neural Networks can figure out various parameters affecting an athlete’s performance and provide recommendations to prevent an injury or fatigue.

These were only a few use cases that give an overview of the capabilities of AI and Deep Learning. Below mentioned are some of the top applications of Deep Learning in Sports.

1 — Sports Production

Deep Learning is used to create fully-automated sports production that looks almost identical to professional sports broadcast, including panning, camera zoom-ins on the action, etc.

The least we should expect from a decent-level automated sports production is to identify the players and ball. Identifying the ball is a difficult task in football. It can be anywhere on the ground, i.e., with players or in the hands of a goalie.

If you think about it, in all these distinct circumstances, the ball “looks” different, yet, we, as humans, have no problem distinguishing it as a ball from a single frame.

Recognizing the players is not straightforward either, as the system will have to differentiate between on-field players, bench players, and referees, etc.

2 — Recognizing the Court/Field

For the Deep Learning algorithm to figure out between ball and players, you first need to help it identify the field/court. Calibration will limit the scope of options for the Deep Learning algorithm by discovering within each frame which pixels are part of the court/field and which ones aren’t.

By determining the area of the court/field, it is possible to discriminate between players who are inside the court/field and others outside of it, such as coaches, bench players, spectators, etc.

3 — Data Annotation

As stated above, a part of the DL model training is a demand for an extensive data set to develop the “ultimate truth” for the DL algorithm. This is a key take away that should be done regularly as the algorithm is evolved, and more data is gathered.

There are many options to achieve this. Humans must annotate a minimal number of frames. Apart from these, several methods that require less effort are:

1. YouTube/Google Images — It is possible to augment the data set by searching “football players” on YouTube or Google. This will produce images or frames that include football players; in other words, they have been “pre-annotated” as football players.
2. Unsupervised Learning — This method uses un-labeled data by applying a supplementary “non-DL” algorithm to the first portion of the area of the potential players. For example, one can use known background subtractors such as MOG to recognize players roughly.
3. Augmentations — Another usually used technique is to alter or augment the images. For example, modify angles, to stretch them, etc. These augmentations generate an additional data set that has been already labeled.

4 — Sports Marketing

Essentially every major sports league in the U.S.A could utilize additional marketing at any given point in time to increase that league’s resources and bolster their ROI.

Human intervention is crucial to make a marketing campaign successful, and DL algorithms can help sports workers achieve their goals.

Today, there are several human tasks can be replaced by AI and Big Data, including consumer research, to generate campaigns that help us to understand customer interests.

Content creation serves as another marketing tool where DL can play a part in. Moreover, technology can keep track of content performance to determine how well a campaign is doing.

Conclusion

As we’ve seen that with Deep Learning technologies, computers can comprehend sports action, opening new possibilities in sports production that were never plausible before.

If appropriately used, Deep Learning can mimic the decision-making process of a human camera operator as well as a video editor, providing the same experience of a professional live sports broadcast, at a reasonable cost.

This revolution in technology will allow semi-professional and amateur sports clubs to broadcast the games to their fans in a way that it can monetize their content.

Written by Sandeep Agarwal, CEO of Credencys a mobile and web app development company.

How Deep Learning and AI is Changing the Sports Industry? was originally published in DataDrivenInvestor on Medium, where people are continuing the conversation by highlighting and responding to this story.

Over the past recent years, cross-platform app development has gained notable momentum and the majority of its credit goes to the various mobile app development frameworks that are out there.

The mobile app development frameworks not only offer a cheaper option to build mobile apps, but they also deliver native-like user experience, which is what a business or a company with strict budget needs.

Although, it is critical to choose the right mobile app development framework, as the choice of framework can make or break the success of your mobile app.

What is a Mobile App Development Framework?

A mobile app development framework is a library that is designed to help developers in building mobile apps. It basically provides a fundamental structure that not only supports mobile application development, but it also boosts the process while reducing the costs at the same time.

In this article, I have listed the 5 best mobile app development frameworks that we highly recommend to all of our clients.

5 Best Mobile App Development Frameworks in Detail

Choosing the right mobile app development framework depends on a number of factors.

That’s being said, let’s understand the best 5 mobile app frameworks individually that make the mobile app development simple.

1 — React Native

React Native was launched by Facebook in 2013, and since then it has become the prime choice of mobile app developers.

React Native is a Javascript-based, open-source cross-platform app development framework that allows developers to build high-performance mobile apps with shorter development cycles and faster deployment times.

The best part about React Native is that it’s a JSX-based (JavaScript-XML) framework, which means developers need not learn any complex programming languages such as Swift or Java in order to build mobile apps.

The framework takes care of converting the React Native code into native views before rendering so that grants a native-like experience for its end-users.

Advantages of React-Native:

• Optimal Performance
• Reusability
• Proficiency
• Lots of third-party plug-ins
• Modular architecture

2 — Flutter

Flutter was launched by Google and is basically an open-source software development kit (SDK) for developing mobile apps. Unlike React Native apps or Hybrid Apps, Flutter is capable of fully compiling to native code.

This compilation allows mobile app developers to give not native-like but truly-native feel. Google made this possible through its graphics engine called Skia, which is a popular 2D graphics engine built by Google.

Flutter uses Dart as its primary programming language and it can construct cross-platform mobile apps for both iOS and Android that can run on any device.

In a nutshell, Flutter is considered to be the best mobile application development framework amongst all frameworks available in the market.

However, you should utilize Flutter only for a certain type of mobile app projects. And this is why you must consult with a mobile app development company if you’re not completely confident about the framework you’re planning to use.

Advantages of Flutter:

• Flexible UI
• Light-weight components
• Lighting fast speed
• Native performance

3 — Ionic

Ionic is free, open-source, and also one of the most widely used mobile app framework for building mobile apps.

Ionic basically enables mobile app developers to build native-based apps for various platforms with the combination of HTML, CSS3, and JavaScript.

It uses minimal DOM to maximize performance and better efficiency and also provides native APIs like Ionic Native and Cordova.

Apart from this, the element of HTML5 in Ionic also allows developers to build hybrid apps.

Advantages of Ionic:

• Fast Execution
• Near-Native Performance
• Cordova Plugins
• Easy to adopt

4 — Xamarin

Microsoft bought Xamarin from its founder in 2016 and they made it open-source ever since.

Xamarin is basically a cross-platform app development framework based on C# programming language that takes a slightly different approach than the rest of the mobile app frameworks.

For instance, Xamarin allows code sharing, which ultimately saves a lot of developers’ time in building mobile apps for multiple platforms.

In addition, Xamarin also comes with an excellent native UI, which allows businesses to build truly-native apps to give the best user experience to their customers.

Advantages of Xamarin:

• Native UI
• Easy API Integration
• Shared Code Base
• Huge Community
• Less complex development environment

5 — Adobe PhoneGap

Adobe PhoneGap is another popular mobile app framework that uses HTML5, CSS3, and JavaScript to build mobile apps.

One of the main reasons why it’s in the list of best mobile app development frameworks is its best-in-class performance, which enables mobile app developers to build apps without facing any hardware restrictions.

Apart from this, PhoneGap also supports using inbuilt hardware features such as Storage, Phonebook, Accelerometer, Camera, GPS, etc.

In fact, unlike most hybrid mobile app frameworks, PhoneGap can build mobile apps for almost all major operating systems including Blackberry, Windows, Ubuntu, Firefox OS, Mac OS, and of course, Android & iOS.

Advantages of Adobe PhoneGap:

• Supports most major OS
• Based on HTML5, CSS3, JavaScript
• Uniformity across platform
• Robust support
• Flexible with web technologies

Conclusion

Mobile app development frameworks are basically driving tools to build mobile apps. And the above-mentioned 5 frameworks have proved to be the best mobile app development frameworks in the market.

Although, the choice of a mobile app framework largely depends on the type of app your building and its specific requirements. So, if you’re planning to build a mobile app, it’s best to consult with a mobile app development company to maximize the outcome of your app idea.

5 Best Mobile App Development Frameworks Businesses Need to Consider Using in 2019 was originally published in Quick Code on Medium, where people are continuing the conversation by highlighting and responding to this story.

Every time the discovery of a new drug brings excitement in the general public as well as the academic community, mainly when it provides cure to an incurable disease.

Whether it is about curing a rare mental illness or cancer, drug discovery has always been a crucial element of health care development and human well-being.

Everyone knows that drug discovery is an expensive business. Moreover, sometimes, it takes years to find the right cure for a global epidemic. It is estimated that, on average, a pharma company spends 10–15 years and around $4 billion to bring the new drug to the market.

Once the medicine is formulated, it’s time for testing. The clinical trial is quite important as it decides the efficacy of a medicine. For that, pharma companies require volunteers who are ready to bear everything that comes with the cure.

This process is so risky that it can put any pharma company’s existence in grave danger. Pharma companies have to “insure” every volunteer before performing experiments on them, which increases overall R&D expenditure.

Diseases like Alzheimer’s and Parkinson’s, which affect the central nervous system, do not have a cure. Neither does it have a vaccine that would prevent it from happening.

How Machine Learning Helps Here?

The whole process of creating a new drug generates a lot of data. Machine learning offers an excellent opportunity to process chemical data and create outcomes that help us in drug development.

Machine learning can help us process the data that has been collected over many years and some time decades in very little time. Also, it will help us make more informed decisions, with otherwise are taken by predictions and experiments.

McKinsey says, if we utilize Big Data and Machine learning to its full potential, then it could help the healthcare sector to generate $300 billion in revenue every year.

Experts predict that Machine learning could help with predictive modeling of biological processes. It will help us in developing successful medications in less time.

Challenges Associated with Implementation

There are many challenges associated with processing data using machine learning. However, today, there is no lack of data collection. The only challenge we have today is to nurture and process the complex data generated.

Drug Development and Machine Learning — An Ideal Match?

Emerging technologies such as AI, ML, AR, VR, and MR are going to be the paramount technologies in the world of healthcare. A colossal amount of data is being generated by hospitals and pharma companies every day.

Crunching this data via AI and ML can help to find the right cure for some of the incurable diseases as well. These AI and ML algorithms will help us establish new molecules and identify the biological effects of each drug beforehand.

In May 2018, 8 big pharmaceutical players and MIT researchers formed a new consortium, that’ll focus on applications of ML in the drug discovery process.

Big research companies like WuXi, Pfizer, Amgen, Bayer, Sunovion, Novartis, Lilly, and BASF are a part of MLPDS (The Machine learning for Pharmaceutical Discovery and Synthesis).

They look into research areas such as experimental design, toxicity, molecular representation, and binding affinity. Currently, they are using ML tools to figure out the exact recipe for the medications of various diseases.

Researchers at MIT have invented a smart WiFi box that monitors a wide variety of physiological signals such as gait, breathing, mobility, behavior, sleep, and heart rate. Based on these factors, an ML algorithm analyses how a person’s body is being affected.

They use sensors to transmit physiological signals, which helps to identify how medicine is affecting the patient’s physiological conditions and disease progression. This data can help us decrease the length of clinical trials, reduce cost, and improve the confidence in the results.

Other Companies

Apart from these institutions and companies, there are other players as well who are researching applications of machine learning in drug discovery.

DeepMind Health has been driving research with hospitals such as Moorfields Eye Hospital, University College London Hospitals NHS Foundation, the Department of Veterans Affairs in the US, and Cancer Research UK Imperial Centre.

DeepMind Health, collaborating with the AI health team at Google and consortium of leading clinicians, is researching to identify the signs of breast cancer in mammograms.

The primary reason why breast cancer is claiming half a million lives around the world every year is because of inaccurate detection. The breast screening sometimes detects cancer even if it’s not there. While sometimes, it even fails to detect cancer in the final stage.

DeepMind Health’s aim is to use machine learning algorithms to analyze historic depersonalized mammograms from around 7,500 women carefully and improve the quality of screening reports.

Rules and Regulations

One of the greatest risks associated with ML in drug development is related to bias. The data sets that are chosen for processing might belong to a particular genetics group. Hence, new medicines might work only for a certain group of patients.

Moreover, techies will have to convince organizations like FDA and EMA that approves medicines for public use. The benefits and applications of machine learning in drug discovery are still in theory. A lot of questions will arise as pharmaceutical companies will put it into practice.

The acceptance of machine learning in pharmaceutical companies will take time, and so will its impact on the industry and our lives. It is crucial to get pharma companies, researchers, and regulators involved in a conversation regarding the implementation of ML and how to achieve its full potential.

Final Thoughts

It is evidential from the above discussions that ML has fantastic potential in drug discovery and the pharmaceutical industry. But, it still requires some polishing and reinforcement to put it into practice.

A graduate student from MIT and 2018 DARPA Riser, Connor Coley, said that machine learning has always been a part of the pharmaceutical and drug discovery industry, but primarily in the form of structure-property regressions. People have now started to realize its potential that’ll change the development paradigm.

Written by Sandeep Agarwal, CEO at Credencys.

How is Machine Learning Revolutionizing Drug Discovery? was originally published in TDS Archive on Medium, where people are continuing the conversation by highlighting and responding to this story.