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Technology and its Usefulness in Battling Coronavirus

The novel coronavirus or COVID-19 outbreak occurred in mainland China at the end of December 2019, which has now spread globally to infect millions of people. It is marked as a global crisis and the WHO itself has declared the situation as a ‘pandemic’.

Governments and healthcare authorities around the world are rigorously working to fight this virus. Among the efforts put in place, the role of technology is inevitable. For instance, the deployment of numerous types of AI-powered tools and gadgets is proving effective in carrying out diverse relief operations. Meanwhile, the vitality of robots to carry out interactions with sick patients is quite relaxing.

Earlier, the use of high-end technological aid was majorly deployed across China. However, with the Coronavirus outbreak intensifying across Europe and North America, healthcare services are being very diligent with their options.

This blog focuses on highlighting the utility of technology for countering Coronavirus at the global level. Below mentioned are the prime tech advantages put in place to fight this rare illness:

Active Use of Robots and Drones

It is very important to know that Coronavirus is contagious; therefore, human-to-human interactions need to be managed remotely. Both in public and hospitals, carrying out remote communication between patients and health workers should occur without any transmission. As a safer solution, robots along with several other automation tools are being preferred.

For instance, robots are actively used to communicate with infected people, disinfect rooms, extract vital information, and even deliver medications. Interestingly, a robot was used in Seattle to assist doctors to treat an American patient diagnosed with COVID-19.

AI-Based Diagnosis

Metabiota and BlueDot, two public health data surveillance firms were responsible for tracking the initial outbreak of COVID-19. It was BlueDot which successfully informed its clients about the coronavirus risk days before the WHO (World Health Organization) had officially issued a global warning.

At present, similar technology has been distributed across channels to monitor social media posts along with publicly available content to spot signs of the virus’s spread.

By conducting a deep analysis as to what every COVID-19 patient is receiving, AI is capable of chalking out satisfactory treatment strategies. For instance, Jvion, a renowned health care analytics company, is making good use of AI to examine 30 million patients across its data collection for identifying people who are highly susceptible to COVID-19. This is made possible by bringing along 5,000 plus variables which cover medical history, lifestyle as well as socioeconomic factors. Further, Jvion’s platform helps to create a proper list of people who need to be contacted regarding their vulnerability to COVID-19.

Potency of Smartphone

Believe it or not, smartphones are listed among the topmost tech aids helping in reducing virus exposure. For example, delivery apps assist in contactless delivery, where the riders are guided to drop food at a specified location. Meanwhile, the use of mobile payment apps is proving effective in reducing transmission as compared to paper money, which is known to carry the virus for up to 17 days.

Big Data Indicator System

The smart implementation of a transparent and handy public data has permitted the creation of dashboards for tracking virus outbreak. Till now, not only the WHO but many small organizations have contributed immensely to cater to the development of such big data dashboards. As a result, users can go through real-time updates conveniently via familiar apps.

Online Platforms for Business Stability

With a worldwide epidemic on the loose, there is a serious challenge to maintain business operations. It is observed that several tech organizations are lending a helping hand by offering free online collaborative tools. Furthermore, the use of online meeting applications has assisted other businesses to successfully imposed work-from-home policies. This also includes the usage of LBS technology and collaboration platforms to ensure a streamlined working of an employee.

Soon, this fight with Coronavirus will strengthen and technology will surely lead from the front. Several software testing companies including ImpactQA have readily followed work-from-home guidelines and are maintaining business operations using shared online platforms.

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How is Drone Technology Effective in Tackling Coronavirus?

In a matter of few months, Coronavirus or COVID-19 has transformed into a pandemic starting its track from China and reaching the United States with a global infected count of 1,018,649 and the death toll rising to 53,281. The foremost steps taken by authorities are to upgrade medical facilities and practice social distancing. These measures have proven effective for China to fight this virus in its 3-4 months of struggle. 

The role of technology cannot be sidelined as it is one of the crucial components used to curb Coronavirus. For instance, the Chinese government has been advising methods to implement drones for providing vital assistance in this alarming situation. Many nations have taken positive out of these experiments and have responded actively to this global health crisis.

At present, both public and private health systems are trying to extend the use of drone technology with a vision to mitigate future chaos due to Coronavirus. Below mentioned are few important ways how drones are proving advantageous in the battle against this rare virus.

Aerial Disinfection

The sole purpose of using drones was originally to spray pesticides under agricultural applications. However, China adapted well with this technology and started to spray disinfecting chemicals across several public spaces and on prevention vehicles that travelled between infected areas. Since Coronavirus is majorly transmitted through respiratory droplets and can transfer by contact through contaminated surfaces spraying disinfectants is a good way to help reduce virus transmission.

For ensuring a safe model for aerial disinfection operations, several in-bound organizations in China such as XAG Technology, China Agricultural Machinery Distribution Association, DJI Agriculture, etc., have joined hands to issue operational guidelines and technical provisions to interact with local authorities. Such measures are essential in streamlining the efforts so that the purpose is served without any hindrance.

Supply Medicines and Test Kits

According to a recent study, it was revealed that the delivery of supplies made using drones can help in covering a larger consumer space in Europe. Interestingly, close to 40 million Europeans will benefit from drone delivery under current circumstances. The correct use of Artificial Intelligence (AI) with drone technology is the reason for the success of such operations.

This model has been carefully tweaked and there are test runs to provide Coronavirus test kits with the help of drones. It is simply through the elimination of humans to transport test kits, we get to majorly lessen the tendency for community spreading of Coronavirus. The reduction of human contact is a must and through this technique, it helps to reach out to a vast patient count in lesser time.

A lot of Europeans, Americans, and populations in other infected nations are scared of community transmission and extended quarantine time. Drone technology is a suitable way to effectively curb these scares by the delivery of food, vaccines, and medicines.

Social Advantages

As analyzed by researchers, the use of drones to transport groceries, medical supplies, etc., in the U.S can enormously benefit the Americans in battling it out with COVID-19. It is highly evident that drone delivery would increase social distancing; hence, reduction in the spread of Coronavirus. Areas that are already marked as high-risk zones for COVID-19 can make the most out of drone services.

Furthermore, the active merger of drones and public health response is a greater benefit to people who reside on the outskirts of major towns and cities. This group can now receive essential groceries and other supplies from stores that are located at a distance from their place. In simple words, drone technology would effectively expand the options related to grocery stores and other important services in remote areas while maintaining social distancing.

Let us see in the coming months how governments and medical authorities across the world inject modern technology to control the spread of coronavirus. This combat against Coronavirus requires a systematic blend of technology and medical assistance. Drone technology has been suitably fed with Artificial Intelligence (AI) and other automation upgrades to make it more resourceful. Software testing firms like ImpactQA have been supportive in testing newer AI upgrades and validating their effectiveness by carrying out system checks and corrections.

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What is the Impact of Artificial Intelligence on Software Testing?

The propagation of Artificial Intelligence (AI) as new technology has received worldwide recognition.  Although it’s not a new concept, the implementation of AI techniques across software testing has proven advantageous. It is interesting to know that, development teams across various platforms are switching to online and e-learning assets all thanks to AI.

However, the misery for QA Engineers at present is linked to surplus difficulties and time wastage while looking for a solution. The scope for making new additions or expanding existing new codes requires them to carry out fresh tests. It is a rigorous process and if planned manually, does overwhelm the QA experts.  

This is where the usefulness of an AI-based testing approach comes into play. Such an arrangement can help identify changed controls skillful in comparison to manual efforts. Furthermore, the identification of even the slightest alterations with the algorithms can be observed by including AI in the process.

This write-up aims to highlight the vitality of AI testing towards software testing and how it will provide supreme assistance in the coming years.  

Importance of AI for Software Testing

The future is untold but technologies such as AI have already given us a positive outlook about what comes ahead. Artificial intelligence is praised as a smart addition to software testing, with future innovations expected to drop more surprises. Below mentioned are some of the notable effects of AI on software testing which should be learned and acknowledged. 

  • Regarding automation testing, the utilization of Artificial Intelligence is primarily associated with object application categorization fixated at all user interfaces. Under this, recognized controls get categorized when tools are created. Moreover, testers are equipped to pre-train controls which are usually available in out of the box arrangements.
  • We already know testing simply means the confirmation of results; hence, one does require possession of surplus test data. As a modern concept, Google DeepMind has an AI program that is structured across deep reinforcement learning efficient enough to play video games by itself. Such an action permits the acquisition of sufficient test data.
  • In the coming years, Artificial Intelligence is likely to monitor users who perform exploratory testing contained within the testing site. This also covers human involvement for assessing and spotting the applications which are getting tested. Consecutively, such a step will attract business users to actively implement testing and customers would be given the chance to fully automate test cases.
  • Risk automation helps users in specifying which tests should be imposed to achieve greater coverage under limited time. As AI testing is added to the test build, execution, and data analysis, it permits testers to permanently get rid of spot links flanked by bugs and components in a much better way.

AI Testing & Related Advantages  

Finally, we mention some of the prominent benefits of AI testing which makes it a bonus inclusion for software testing:

Fastens Manual Testing

It is a well aware fact that countless test lines are coded even by the most skilled application development companies.  Manual testing is not that efficient in maintaining speedy processing even after all efforts are put in place. Above all, functional testing tends to be expensive, thereby, consuming additional time and money.

The incorporation of AI testing is known to facilitate and address time-wasting issues. As a result, developers are relaxed when it comes to writing all scripts and investigating large chunks of data sets since they are now managed in a faster manner. Artificial intelligence is capable of sorting via log files, thereby, saves precious time and improvises programming accuracy.

Assistance to Developers and Testers

The usefulness of shared automated tests can be reaped by developers for identifying problems before passing it on to QA. To be precise, tests can be executed automatically every time the source code variations are checked in. This also functions as an effective move to notify the team in case of a failure.

Enhanced Time-to-Market

Software tests are repeated whenever the source code is altered. It should be understood that manually repeating such tests is indeed time-consuming and can also prove highly expensive. However, automated tests can be operated multiple times without any additional cost and at a quicker pace.

Some of the AI-based test automation tools include Appvance, Testim.io, etc.

Advanced Test Coverage

As AI is merged with automated testing, it works to enhance the overall depth and scope of tests. Automated software testing can easily access memory, file contents, data tables, etc., for determining the working status of the software. On the whole, test automation is capable of carrying out 1000+ test cases related to each test run offering coverage that isn’t doable with manual tests.

The potency of AI testing and its collaborative actions under software testing is very well defined in this blog. As the testing arena is gaining strength and skill in this modern setup, the superiority of AI-based software testing operations will achieve a greater position in the near future. If you hold any queries related to the expanse of AI within software testing, simply connect with testing experts at ImpactQA.

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5 Mobile App Testing Trends Set to Surface in 2020

The role of mobile apps in the currently thriving modernized setup has acquired an imperative stature. It is primarily to enhance the scale of convenience both at the consumer and enterprise-level that mobile apps have grown to become a major hit!

For the success of any software or application, there are different stages of testing. App quality is the foremost factor that predicts the success and sustenance of a particular mobile application. Over the years, mobile app testing trends have shown serious variations. The sole reason for this shift can be attributed to the rising count of mobile devices, thereby, supporting enormous disintegration in terms of screen sizes, OS, etc.

Furthermore, it becomes essential for a mobile app testing company to adapt to new features and restrict threats linked to new bugs. According to recently updated research, the global market for mobile app testing services is anticipated to exhibit USD 13585.73 Million by 2026. These are mind-boggling statistics highlighting the importance of mobile app testing in today’s time with an expected CAGR growth of 20.3 % by 2026-end.

Mobile App Testing Services Market Expanse (Image Source)

A new decade has initiated to bring in new technological trends in the world of mobile app testing. Let us focus on the five prominent mobile app testing trends set to unfurl in the year 2020.

Automation is the Key

Automation has taken over the global mobile app testing market. In 2020, it is expected that the majority of the testing companies will actively stride towards automation which functions as a prominent factor towards quality assurance. In addition, the selection of automation tools and frameworks is known to lessen testing time. Such advantages are likely to benefit the mobile app testing market with soaring results.

Spotlight on IoT

These days, you will find that most devices are linked to each other, thereby, preaching comfort as the fundamental aspect. For instance, mobile devices are now connected to headphones, smartwatches, home accessories, etc. This overall concept is termed as the Internet of Things or IoT. Although the incorporation of IoT does exhibit convenience, security threats are rising since devices are getting more complex.

In 2020, it is expected that a mobile app testing company would be able to access more sophisticated technology. In simple terms, the IoT testing process will involve not just mobile phones but several other hybrid devices for quality assurance.

Testing with Real Device Cloud

As per research insights, close to 1.5 billion smartphones will be operative in 2020 having different screen resolutions, OS versions and more. It is practically impossible to test a particular mobile app on all devices which are used by the customers. As a valid solution, incorporating a real device cloud is the perfect way to enhance testing efficiency. For the current year, the favorable strategy implied for mobile app testing is concentrated at amalgamating the use of real devices with cloud technology.

Such an arrangement will pinpoint evident performance defects. Moreover, the chances of having forged positives or negatives are also decreased. Among the latest mobile app testing trends, the deployment of real device cloud is highly efficient since it targets everything, be it network failures, hardware issues, etc.

The future holds untapped mystery, especially when it comes to technology and its wonders. As the year passes, it is believed that Artificial Intelligence (AI) and Open Source Tools will surely share a significant role in accelerating the mobile app testing market.

AI Testing

The popularity of Artificial Intelligence as a growing technology has brought major changes within the software research arena. It is observed that the implementation of machine learning and artificial intelligence over the testing platform can prove fruitful. For instance, the AI testing algorithms can be useful in creating better test cases, scripts, reports and data to receive efficient outcomes.

The usefulness of AI testing can also be highlighted while designing test models to determine errors and loopholes effective for mobile app development. With the power of smart visualization and analytics, AI is extremely serviceable to search and rectify defects without much hassle.

Propagation of Agile and DevOps

The reputation of Agile has escalated in the market since organizations are switching towards rapid changes. Moreover, the collaboration of DevOps for accomplishing speed requirements is another factor that is expected to rocket in the near future. It is expected that DevOps will implement the rules and practices together to set out operations and development processes on mobile apps.

It is a major advantage for testing teams with the merger of DevOps and Agile for creating better mobile apps. Quality and speed are the foremost factors that are meticulously assessed with this productive association.

It is essential to take a look at all 5 mobile app testing trends set to rise in 2020. This allows us to polish and improvise mobile testing methodologies for the future. For additional information and insights, you can connect with professional testers at ImpactQA.

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8 DevOps Trends to be Aware of in 2020

  • Automation will become the major focus
  • Shifting attention from CI Pipelines to DevOps Assembly Lines
  • Rise in Artificial Intelligence (AI), Data Science Boost
  • Concept of “everything as code”
  • Hype in using Server Less Architecture
  • Automation through AI and Data Science
  • More Embedded Security
  • Kubernetes has evolved significantly

According to a collective study, DevOps market generated 2.9 billion in 2017 and the market is expected to reach at $6.6 billion by 2022. DevOps has become a key focus and has shaped the world of software and many experts predict that DevOps is going to be the mainstream and is going to reach its peak at 2020.

Enterprises are not only showing interest in DevOps but are gradually adopting DevOps-related practices and technologies. As per Hackernoon article citing Statista, there was a 7% boost in DevOps adoption from 2017 to 2018. DevOps software market is projected to grow from $2.9 billion in 2017 to $6.6 billion in 2022 (source: estimates from IDC).

DevOps Projected Growth 2019

Fig: Google trend is shown for “DevOps” and a hypothesis of its estimated growth in 2019.
DevOps offers the following benefits:

  • Fast response towards an amendment
  • Offers great speed and makes the security arrangement more agile
  • Establishes a perfect channel of collaboration and communication
  • Fast identification of bugs or vulnerabilities in the code
  • Team can effortlessly put their sole attention on other critical things instead of focusing on security features

Many enterprises are adopting DevOps and there is a boost up to 17% in the year 2018 than what was about 10% in the year 2017 (according to Statista)

Image source: Statista

Predictions of 8 DevOps Trends to be aware of in 2020:

1. Automation will become the major focus

Companies that have already implemented DevOps have seen high efficiency and faster deployments. When it comes to DevOps, DevOps automation is what we talk more about. Zero-touch automation is going to be the upcoming future. Understanding the 6 C’s of the DevOps cycle and to apply automation between these phases is the key, and this is going to be the major objective in 2020.

2. Shifting attention from CI Pipelines to DevOps Assembly Lines

The final goal of DevOps is to improve collaboration between planning and automation of the delivery procedure. It is not just about doing Continuous Integration (CI) but it is all about CD (continuous delivery). Companies are investing extra effort and time into understand about automating their whole software development process. In 2020, the attention is going to shift from Continuous Integration (CI) pipeline to DevOps assembly lines.

Advantages of Assembly Lines:

  • Powerful nested visibility
  • Native integrations
  • Fast on board and scale with “as-code” philosophy
  • Perfect CD (continuous delivery) with interoperability
  • Team-based business intelligence and analytics

3. Rise in Artificial Intelligence (AI), Data Science Boost

Growing number of Artificial Intelligence-driven apps will push data science teams to look for DevOps philosophy in their workflows. DevOps method is expected to be their prominent option in dealing with automated pipelines, maintaining, and testing multiple deployed models in the production chain.

This is going to boost further as data science & development teams move closer for high efficiency in development, deployment & managing AI & ML-driven apps.

4. Concept of “everything as code”

We cannot deny the fact that coding has now become the backbone of the IT sector. Understanding various DevOps tools and automating scripts plays a crucial role in the software development and this is going to dominate in 2020. The future of this industry depends on the technical capabilities of the developers, testers, and people of the operation.

Since, DevOps is all about easing the delivery cycle, there is a need to bring in the code which can be used to increase the software production cycles efficiency. The thought of “everything as code,” is DevOps’s built-in practice and it can be present in the SDLC to create a wave in the DevOps trend 2020. Software Testers are likely to suffer if they do not learn to code and write their test scripts.

5. Hype in using Server Less Architecture

DevOps can be reached to the zenith level with server-less architecture. This is not free of server; however, there is a cloud service which takes care of the complete architecture. This extraordinary architecture allows the software developers to concentrate focus on the “Application Part”. BaaS and FaaS are the two critical aspects of the server less architecture. By employing server-less architecture, you can save time, cut down the costs, and ensure resilient work flow.

6. Automation through AI and Data Science

The main objective of 2020 is zero-touch automation. The continuous increase of Artificial Intelligence and Data Science has become a game-changer. Various apps are fueled with AI, which is pushing DevOps teams to seek automation possibilities to discover prospects within their workflow streams.

7. More Embedded Security

With the exponential growth of security breaches and the bad impacts to the company’s reputation, cyber-security has become business imperative. In 2020, DevOps will rapidly include security.

Recently we have seen a buzz trend of DevSecOps. DevSecOps is all about injecting security first in the app development life cycle, therefore decreasing vulnerabilities and improving business reputation.

The shift to DevSecOps will also bring great collaboration in software development. It will ensure the development processes remains flawless, efficient, and effective.

8. Kubernetes has evolved significantly

Kubernetes has turn out to be the top growing container technology. Globally, technologists and CIO’s have preferred Kubernetes because of its offerings and it is expected to grow by 2020. This year, we saw the adoption of Kubernetes take off as companies of all sizes embraced containers for running cloud-native apps. In 2020, we will start to see container orchestration software replacing several old DevOps functions.

Solution- How can we help you?

Whether it is all about offering software development services or other services, DevOps has become the inevitable part of any organization. By staying up to date with the newest trends, you set your business up to get the enormous benefits from DevOps.

As an industry leader in DevOps Testing Solution, ImpactQA give holistic agile and DevOps adoption services across diverse domain segments, backed by its dedicated DevOps Continuous Testing practice. We implement a robust plan to manage both resources and testing tools in a new environment and to facilitate continuous testing and delivery.

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How IoT and Machine Learning is changing the World?

  • What is Machine Learning?
  • What is the Industrial Internet of Things (IIoT)?
  • How IoT (Internet of Things) and Machine Learning affect our life?
  • Challenges- IoT and Machine Learning
  • Solution

IoT and Machine Learning are getting smarter. Companies are incorporating artificial intelligence (AI)—in specific, machine learning—into their IoT apps. From smart thermostats to wireless sensors, IoT devices are gradually but positively garnering mainstream adoption. Virtual assistants like Siri, Alexa, and Cortana are only making this technology easy to adopt.

The core purpose behind advancement in the IoT space is to help information move smoothly and seamlessly. For as much as we condemn technology, we can all recall a moment when the right message has appeared at the right time, with perfect user experience.

The truth of IoT and Artificial Intelligence – specifically machine learning – is far less sinister. It is shaping the way we live, travel, work, and communicate. In fact, it is shaping our lives smartly and the decisions we make.

The proliferation of smart IoT devices is shaping the future and gives instant access to the information world.

Let’s have a glance at these burning IoT statistics:

  • There are about 17 billion inter-connected devices in the globe as of 2018. With more than 7 Billion of these IoT (internet of things) devices. (Source- IoT Analytics)
  • According to McKinsey Global Institute, each second, 127 new IoT devices connect to the net.
  • The global IoT market is expected to be worth $1.7T in 2019. (Source: CBI Insights)
Worldwide  Iot Active Connection Graph
Worldwide IoT Active Connection Graph

What is Machine Learning?

ML is one of the critical components of AI, where a computer is programmed with the ability to improve its performance. In short, Machine Learning is all about analyzing big data – the automatic extraction of information & using it to make predictions.

Netflix, Amazon, Google, and other E-Commerce platforms use it to bring semantic outcome. It is based on algorithms that analyze the user’s purchasing history to predict their preference. Machine learning is gradually integrating into all verticals, through automation of physical labor, we are improving the connectivity and shaping the future of AI and the IoT.

What is the Industrial Internet of Things (IIoT)?

The Industrial IoT or Industry 4.0 or the 4th industrial revolution are the terms generally used for IoT technology in a business setting. The concept is similar to the consumer IoT; to use wireless networks, a mix of sensors, big data and analytics to optimize industrial processes.

IoT devices provide information and analytics to connect the world of hardware devices and high-speed internet.

We can separate the Industrial IoT into two main categories:

  • Industrial IoT- The Industrial IoT, connects devices and machines in sectors like healthcare, transportation, power generation, etc.
  • Commercial IoT– Commercial IoT sits between industrial IoT and consumer and shares aspects of both.

How IoT (Internet of Things) and Machine Learning affect our life?

IoT and ML are improving the way we live and communicate in our lives. For instance, the AlterEgo headset easily responds to our brainwaves to control appliances and on the other hand, Alexa and Amazon’s Echo enables the voice-activated control of your high-tech smart-house.

This amalgamation of IoT and Machine Learning is changing various industries and the relationships that companies have with their clients. Businesses can easily gather and transform data into valuable information with IoT.

IoT is also transforming business models by helping companies to move from concentrating on products & services to companies that give the best outcomes. By impacting organizations’ business models, the blend of IoT-enabled devices & sensors with ML creates a collaborative world that aligns itself around results & innovation.

Challenges- IoT and Machine Learning

These days’ enterprises are flooded with data that comes from IoT devices and is seeking AI to help manage the devices. It is tough to manage and extract crucial information from these systems than we might expect.

There are aspects to IoT like data storage, connectivity, security, app development, system integration, and even processes that are changing in this space. Another layer of complexity with the Internet of Things has to do with functionality level.

Critical challenges that companies face with IoT and ML are with the application, ease of access, and analysis of IoT data. If you have a set of data from varied sources, you can run some statistical analysis with that data. However, if you want to be proactive to predict events to take future actions, a business needs to learn how to use these technologies.

Many firms are turning to the main cloud platform providers — for instance, Google, Amazon, Microsoft, Alibaba Cloud, or IBM. These companies offer a range of services to store IoT data and prepare it for data analytics, plus to train and run machine-learning models. They also assist in creating graphs, dashboards, and other simple-to-grasp layouts to visualize the information these models generate. Overall, IoT and Machine Learning are combined to provide high visibility and control of the wide range of devices connected to the Internet.

Solutions-How can we help you?

Futurists say ML (Machine Learning) and the Internet of Things (IoT) will transform business profoundly than the digital and industrial revolutions combined.

Are there some kinds of risks? Yes, as with any new technology, we have to accept both the profit and risks that come with mainstream adoption. We can do this with the confidence only when these technologies are tested against several odds.

One of the innovative solutions for seamless operation flow is IoT testing. There will be several other types of testing which require to be considered to cover the comprehensive functionality of IoT devices.

As part of ImpactQA’s Advisory Services, we also provide an implementation plan to help our clients improve time-to-market while keeping their business goals in mind. We use our assessment frameworks (like Chatbot testing framework, RPA Testing framework, etc.), based on industry best standards, focusing on processes, tools, and infrastructure.

Collaborate with our specialists to improve all QA areas – people, processes, tools, and infrastructure across the delivery life-cycle.

Learn More

How IoT and Machine Learning is changing the World?

  • What is Machine Learning?
  • What is the Industrial Internet of Things (IIoT)?
  • How IoT (Internet of Things) and Machine Learning affect our life?
  • Challenges- IoT and Machine Learning
  • Solution

IoT and Machine Learning are getting smarter. Companies are incorporating artificial intelligence (AI)—in specific, machine learning—into their IoT apps. From smart thermostats to wireless sensors, IoT devices are gradually but positively garnering mainstream adoption. Virtual assistants like Siri, Alexa, and Cortana are only making this technology easy to adopt.

The core purpose behind advancement in the IoT space is to help information move smoothly and seamlessly. For as much as we condemn technology, we can all recall a moment when the right message has appeared at the right time, with perfect user experience.

The truth of IoT and Artificial Intelligence – specifically machine learning – is far less sinister. It is shaping the way we live, travel, work, and communicate. In fact, it is shaping our lives smartly and the decisions we make.

The proliferation of smart IoT devices is shaping the future and gives instant access to the information world.

Let’s have a glance at these burning IoT statistics:

  • There are about 17 billion inter-connected devices in the globe as of 2018. With more than 7 Billion of these IoT (internet of things) devices. (Source- IoT Analytics)
  • According to McKinsey Global Institute, each second, 127 new IoT devices connect to the net.
  • The global IoT market is expected to be worth $1.7T in 2019. (Source: CBI Insights)
Worldwide  Iot Active Connection Graph
Worldwide IoT Active Connection Graph

What is Machine Learning?

ML is one of the critical components of AI, where a computer is programmed with the ability to improve its performance. In short, Machine Learning is all about analyzing big data – the automatic extraction of information & using it to make predictions.

Netflix, Amazon, Google, and other E-Commerce platforms use it to bring semantic outcome. It is based on algorithms that analyze the user’s purchasing history to predict their preference. Machine learning is gradually integrating into all verticals, through automation of physical labor, we are improving the connectivity and shaping the future of AI and the IoT.

What is the Industrial Internet of Things (IIoT)?

The Industrial IoT or Industry 4.0 or the 4th industrial revolution are the terms generally used for IoT technology in a business setting. The concept is similar to the consumer IoT; to use wireless networks, a mix of sensors, big data and analytics to optimize industrial processes.

IoT devices provide information and analytics to connect the world of hardware devices and high-speed internet.

We can separate the Industrial IoT into two main categories:

  • Industrial IoT- The Industrial IoT, connects devices and machines in sectors like healthcare, transportation, power generation, etc.
  • Commercial IoT– Commercial IoT sits between industrial IoT and consumer and shares aspects of both.

How IoT (Internet of Things) and Machine Learning affect our life?

IoT and ML are improving the way we live and communicate in our lives. For instance, the AlterEgo headset easily responds to our brainwaves to control appliances and on the other hand, Alexa and Amazon’s Echo enables the voice-activated control of your high-tech smart-house.

This amalgamation of IoT and Machine Learning is changing various industries and the relationships that companies have with their clients. Businesses can easily gather and transform data into valuable information with IoT.

IoT is also transforming business models by helping companies to move from concentrating on products & services to companies that give the best outcomes. By impacting organizations’ business models, the blend of IoT-enabled devices & sensors with ML creates a collaborative world that aligns itself around results & innovation.

Challenges- IoT and Machine Learning

These days’ enterprises are flooded with data that comes from IoT devices and is seeking AI to help manage the devices. It is tough to manage and extract crucial information from these systems than we might expect.

There are aspects to IoT like data storage, connectivity, security, app development, system integration, and even processes that are changing in this space. Another layer of complexity with the Internet of Things has to do with functionality level.

Critical challenges that companies face with IoT and ML are with the application, ease of access, and analysis of IoT data. If you have a set of data from varied sources, you can run some statistical analysis with that data. However, if you want to be proactive to predict events to take future actions, a business needs to learn how to use these technologies.

Many firms are turning to the main cloud platform providers — for instance, Google, Amazon, Microsoft, Alibaba Cloud, or IBM. These companies offer a range of services to store IoT data and prepare it for data analytics, plus to train and run machine-learning models. They also assist in creating graphs, dashboards, and other simple-to-grasp layouts to visualize the information these models generate. Overall, IoT and Machine Learning are combined to provide high visibility and control of the wide range of devices connected to the Internet.Top 5 Mobile Application Testing Tools

Solutions-How can we help you?

Futurists say ML (Machine Learning) and the Internet of Things (IoT) will transform business profoundly than the digital and industrial revolutions combined.

Are there some kinds of risks? Yes, as with any new technology, we have to accept both the profit and risks that come with mainstream adoption. We can do this with the confidence only when these technologies are tested against several odds.

One of the innovative solutions for seamless operation flow is IoT testing. There will be several other types of testing which require to be considered to cover the comprehensive functionality of IoT devices.

As part of ImpactQA’s Advisory Services, we also provide an implementation plan to help our clients improve time-to-market while keeping their business goals in mind. We use our assessment frameworks (like Chatbot testing framework, RPA Testing framework, etc.), based on industry best standards, focusing on processes, tools, and infrastructure.

Collaborate with our specialists to improve all QA areas – people, processes, tools, and infrastructure across the delivery life-cycle.

Learn More

5 Ways AI is Shaping the Future of Software Testing

Artificial Intelligence is the hottest buzzword these days and advancement in AI allows Enterprise and industries to make smart decisions and radically transform processes. As software tests shift gears from manual to automation for embracing the speed for DevOps and digital transformation, Artificial Intelligence has emerged to be the key lever for this change. AI [...]Learn More

How AI Adoption Actually Bang and Turn QA Expectations?

Software testing industry is becoming extensive with every passing day. With the sudden boost in the technology challenges, apps are growing in complication which creates an incessant need for effective software testing. Software testing is the premeditated way where an app can be observed under definite conditions and where software testers can detect the risks [...]Learn More