e-learning

Personalisation, on-demand and predictive analytics: e-learning’s next leap forward

ElearningMindfire Solutions

Introduction:

While online learning gained popularity in the 90’s, off late it has gained further traction. With the Covid-19 pandemic and its associated lockdowns, e-learning has emerged as one of the prominent uses of technology in the 21st century. E-learning as an educational experience is delivered electronically. It comprises many elements such as live or pre-recorded lecture content, videos, quizzes and other interactive elements.

While schools, colleges and other educational institutions shut down in early 2020, e-learning emerged as a saviour. With the gaining reputation of e-learning, many students and working professionals have started finding the easy, accessible and ‘at your own pace’ learning mode a friendlier way of educating self and others. Thus, it can be safely assumed that the e-learning market is well poised for a boom; researchers conclude that the market size of the industry will grow by 10.85% by 2025.

To make learning a holistic and egalitarian experience work for all, it is important for e-learning companies to create a personalized and accessible user experience. Big data tools such as personalization, on-demand learning and predictive analysis are helping the e-learning industry today to multiply, both in terms of scale and impact. Before we move onto exploring what role they can play in the future of education, let’s first take a deep dive into what these terms mean.

Personalization:

The word ‘personalization’, mostly used in sales and marketing is a popularly used term. Simply put, it means, one size does not apply to all. Firstly made popular by brands like Google and Amazon, personalized experience became a raging success with custom made services and communication for customers. The same personal details like name, birthdays and favourite colours that are used to tailor gifts for spouses and friends are amplified today by e-learning companies to tailor learning experiences based on learner needs. This has entailed higher learner engagement and improved performance.

On-Demand:

While the meaning of ‘on-demand’ is self-explanatory, in the realm of e-learning it would imply ensuring availability of learning solutions to the learner, anywhere and at any time. Post pandemic, millions of students are out of school. On-demand e-learning solutions guarantee easy access to quality course content and premium educators to learners from around the world

Predictive Analytics:

‘Predictive analytics’ is a tool that uses data, statistics and machine learning techniques to predict the likelihood of future outcomes based on available data. It has transformed e-learning by leaps and bounds. Educational institutions have been managing data for many years. Predictive analytics is a technology breakthrough when it comes to capturing educational big data.

E-learning’ next big leap :

The rapid proliferation of mobility devices has resulted in a situation where nearly all school students have a mobile device. With an explosion of the world wide web, innumerable small mobile devices have access to the internet. The affordability, accessibility and common usage of mobiles/ other internet devices makes e-learning a highly plausible vehicle of learning. So how can it become more democratic?

While personalization has existed in people’s lives for a long time, personalised learning has evolved as a new novelty in e-learning. It is the first step for tailoring content, pedagogy and learning environments to meet individual learning styles and learner needs. More than just individualization or differentiation, a personalized e-learning process enables students to customize several learning elements in their online learning process. This usually means that they set their own goals, pace and communicate with instructors to proceed as per their comfort. Ideally this indicates that the student is in charge of his/her learning and has a direct say in their education.

So, why is personalization important?
  • Each learner is different. For example – some learners perceive audio better and others video;
  • Every learner has a different coping speed. Some can learn large materials in a short time while others can cope only with small amounts;
  • Most learners have an independent and individual learning style. While some may like studying on the PC, others prefer a mobile phone or a tab.
  • One size does not fit all. Each learner is different and comes from a different place of learning.
On-Demand Strategy

On-demand is a strategy for learners to access knowledge based content anytime, anywhere. With ongoing education and learning an imperative for every organization, the question for professionals globally is: what are the best ways to deliver relevant and meaningful learning to multi-generational learners in today’s highly competitive world?

Technology, as always, has the answer to this question. Consumers and companies dominate the world in exchanging data. This data consists of millions of questions pertaining to multitudes of products and services, everyone expects information whenever they have an internet connection.

In the context of e-learning and especially with millions of learners, where each one of them differ from one another, on-demand e-learning contains elements such as flexibility, effective user engagement and leveraging the on-demand nature of the content, be it with respect to business or education.

The on-demand economy is here to stay and is yet to reach its fullest heights. However, technology will continue to revolutionize e-learning by conjoining it to on-demand learning. Whenever that happens, guided, self-paced learning formats and addressing the growing need to learn in a time-crunched world, will continue to be a priority.

In the context of e-learning, predictive analysis, a form of big data, is generated when a user engages on the Learning Management System, LXP or mobile app solution. For example – when a learner completes an assignment, their progress or results generated becomes a part of the “big data”.

Globally this data is gathered, analysed and decoded to be turned into intelligence.

Some insights gathered:
  1. Gain insights on learning and knowledge gaps.
  2. Preferred methods and modes of conducting learning events for learners of all age groups
  3. Understand and approach strengths and weaknesses for future learning strategies
  4. Understand how to personalise and customise an individual’s learning journey to improve the ultimate user experience along with the desired results.

Final Thoughts:

The world around us is rapidly transforming alongside a growing number of diverse students. All the three tools and processes mentioned above are useful for educational and professional organizations that work on complex data. This in turn is making best learning solutions available to students. It also provides tailor made learning that is accessible, with data insights that can improve learning for the future generations.

Like other businesses, if you too are looking to develop IT Solutions in e-learning industry, Mindfire Solutions can be your partner of choice. We have gained significant experience over the years working with Edtech Companies. We have a team of highly skilled and certified software professionals, who have developed many custom solutions for our global clients over the years.

Here are a few interesting projects we have done. Click here to know more:

Case study on site setup for selling online courses.

Case study on learning management system.

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Cloud first

Cloud first strategy: Driving innovation for credit unions

FintechMindfire Solutions

Cloud first strategy – The essentials:

Cloud services have transformed the way businesses operate across different sectors. This holds true, especially for the financial sector, where more and more financial service providers are making the transition. As per a recent survey by Celent, over 50% of the global financial institutions say that they expect their system to completely transition to the cloud within 5 years. Post the Covid 19 pandemic, cloud has paved the way for more remote operations within the financial industry, making its adoption more likely in the future.

As the name suggests, ‘Cloud first strategy’ is all about considering cloud-based technology solutions before any other. It allows businesses to save money on software and hardware infrastructure by subscribing to a service provider who can provide the same services at a cheaper cost, and at a premium quality.

As most people might know it, there are three kinds of cloud:

  1. Private cloud – operated solely for a credit union
  2. Public cloud – shared by several organizations and available to any paying customer
  3. Hybrid cloud – combining your private and public cloud functionality to find packages that best suit one’s needs.

IBM has referred to the public cloud phenomenon as “one of the most important shifts in the history of enterprise computing”. It is still a growing sector, as more organizations are becoming familiar with its increasing benefits.

Similarly, while there are credit unions who vouch for the benefits of the public cloud, others are unsure to bring about a complete cloud migration. CSI’s 2021 Banking Priorities Executive Report cites that over 60% bankers did not have the prerequisite information prior to investing in the public cloud. The next section talks in brief about some of the misconceptions associated with public cloud and how credit unions can benefit from the transition.

Misconceptions:

  1. The pace of transition: A popular misnomer about the public cloud is that the entire transition has to be made at once. Credit unions are creating a hybrid environment where some of the infrastructure remains on-premise.
  2. The fear of ‘all or nothing’ approach: Most bankings services are fearful of making the transition to putting everything on the cloud. The truth is most of their operations such as Office 365 and dropbox are already there.
  3. Security breaches: News of security breaches are often making the headlines nowadays. Many credit unions feel that being on the public cloud will make them vulnerable to data breaches. While such breaches do occur, they can be mitigated with proper security configurations.

With an increase in inclination towards adopting a cloud strategy by credit unions, it is important that proper security considerations are kept in mind while partnering with cloud providers. By carefully working with the right provider, businesses can look into the secure configuration of their environments. They can also maximise the cloud’s security and privacy benefits.

Benefits:

  1. Compliance – A strong cloud strategy provider ensures compliance with tight security measures, making audits much easier than ever before. Partnering with a public cloud provider entails outsourcing of important compliance related responsibilities. This allows credit unions to utilize a provider’s established framework. Many financial institutions have made large investments in cloud based compliance frameworks. These would have otherwise been highly unaffordable and unsustainable in an onsite infrastructure.
  2. Scalability – Physical servers are not compatible with scale. Credit unions therefore must take into account future needs and industry demands. By migrating to the cloud, institutions can bring about greater flexibility, agility and affordability. Migration to the cloud means more resources can be added to their environment while enjoying cost benefits from the process.
  3. Cost efficiencies – It is possible to buy only as much physical infrastructure. This leads to wastage and inadequate utilization. With the public cloud, a credit union can customise its purchases and expand its infrastructure only when needed. This leads to potential cost savings and allows credit unions to enjoy the benefits of a managed IT environment.
  4. Availability – The public cloud ensures a credit union with a resilient IT environment. It ensures a safety net during server malfunctions resulting in a smooth sailing of operations. It improves the overall day to day experience of both employees and customers, engaged in working with credit unions.
  5. Access – In the 21st century and especially in the post pandemic world, timely access to services is everything. Via cloud, credit unions can manage a remote workforce, use an increasing range of high-speed connectivity options, interact with a diverse range of modern cloud based resources and so on. With proper systems, the cloud strategy can transform financial institutions and their private networks.

Final thoughts:

The credit union industry has been slow on the uptake to adopt a cloud strategy due to analysis paralysis. With industry leaders paving the way, more and more people are opting for digital transformation through a secure cloud strategy.

With infrastructure reaching the end of its life, tech inventory mapping becoming challenging. Physical IT infrastructure becomes difficult to build, manage and maintain. With the increasing need to adopt resilient platforms such as Data Recovery, a cloud first strategy is imperative for credit unions.

A cloud strategy can bring down an organization’s costs by 30-50%, primarily by reducing dependency on infrastructure. It also offers an economy of scale by collaborating with cloud providers like AWS on security, compliance and new opportunities. This paves way for credit union IT systems to focus on forging new partnerships and boosting new applications, which they previously did not have the time to do.

Like other businesses, if you too are looking to develop IT Solutions in Financial Services industry, Mindfire Solutions can be your partner of choice. We have gained significant experience over the years working with Fintech Companies. We have a team of highly skilled and certified software professionals, who have developed many custom solutions for our global clients over the years.

Here are a few interesting projects we have done. Click here to know more:

Case study on e-Wallet mobile application.

Test automation of digital payments.

Case study on Smart card for pocket money.

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API

Capitalize on advances of API in Open Banking

FintechMindfire Solutions

Introduction:

While big data and its associated algorithms and analytics are a powerful step to gaining insight, a more fundamental building block for the data market is access. Most industries have started leveraging an easier access to data through API. The financial services industry considers it to be a priority too. Some of the global steps that have been taken to adopt data for public sector transparency and integrity include the G20’s Anti-Corruption Working Group and the European Union’s Payment Services Directive (PSD2).

Data sharing can be seamlessly accomplished through API or more popularly known as application programming interface. According to a Mckinsey report, API is an intelligent conduit that allows for data flow between systems in a controlled yet seamless fashion. APIs are in use in banking systems for years now. However, with the breakthroughs in advanced analytics and the positive market response to numerous non-banking fintech companies, APIs are once again in the limelight. Experts believe it has the potential to enhance the delivery of financial services across sectors, including retail and business.

Open banking with its benefits to consumers, banks and non-banks is expected to usher in a new financial services ecosystem where the roles of banks may undergo a marked shift. It also raises issues around compliance and data privacy. This is the reason why global markets have been leaning more towards increasing governance. There is a global momentum towards open banking models, leading to an overhaul in the blueprint based on which these systems have been previously operational. This requires banks and fintechs to position for success in a new environment while anticipating what its impact on customers could potentially be.

What is open banking?

As per the same McKinsey report, open banking is a collaborative model in which banking data is shared through APIs between two or more unaffiliated parties to deliver enhanced capabilities to the marketplace. API has been popularly adopted for decades, particularly in the US. This helps to foster the growth of personal financial management software, show billing details on bank websites and connect platform developers to payment networks like Visa and Mastercard. However, API was primarily used to share information rather than to facilitate the transfer of monetary balances.

Benefits of open banking:

The benefits of open banking are substantial. They include improved customer experience, new and increased revenue streams and a service model that can cater to traditionally unexplored markets. Examples include Mint, Lending Club in the US to Lenddo in the Philippines.

However, these advances are not as easy as they sound. Research says that with the emergence of integrated digital ecosystems, these ecosystems collide threatening operating models and preventing business innovation. Additionally, most of the breakthroughs have happened outside the realm of financial services. This makes rich data and their associated data flows look more like a threat than an opportunity. The non-banking sector has demonstrated a more serious market traction so far. Hence, open banking is a model still in its nascent stages.

However for the banking sector, there are inherent risks in sharing data flows. This makes data security and matters of compliance and governance of utmost importance.  The real API value proposition lies in streamlining systems integration for data access. The aforementioned issues of privacy and security makes it a monumental infrastructure challenge.

Facilitation of a futuristic collaboration:

Open banking models can facilitate a series of services for all stakeholders in the financial services. For example Wechat has enabled e-commerce through their platforms. This model can evolve into a one-stop-shop platform integrated with personalized experiences and commerce centered apps. Other services like Trustly provide credit extensions at checkouts, where a purchase decision can be influenced.

Open banking also ensures financial inclusion. This helps banks and financial networks arrive at a more precise risk and credit analysis of members who have been potentially excluded from the financial system. For example – Angaza in Africa. This is a unique way of introducing and including more consumers to the formal financial system.  This has the possibility of expanding market opportunities in a particular geography. Incubators and venture capitalists from around the world have shown particular interest in newbies who are aspiring to incorporate nonfinancial data with transactions based on data insights.

While it is true that open banking will reduce control in traditional banks, the banking ecosystem will however gain from larger profit pools. It can also position itself to play a leading role in combining artificial intelligence and predictive analysis. This in turn will improve integration of banking services for customers and the enhancement of business offerings.

Challenges:

The challenges vary by geography, demographics and the ecosystem development in that particular country. Banks with larger global footprints expect to face challenges in the future regarding regulations and standards. By 2023-24, banks should leverage their incumbent advantages by doing the following:

1. Be a game changer by staying ahead of the curve, exploring data sharing with fintech and non-financial services.

2. Explore the value of APIs and how they can benefit the bank’s service model.

3. Fully understand data privacy mandates and determine if their institution has the appetite for a less conventional approach. Also examine how API could facilitate future customer messaging without incurring any damage.

Final thoughts:

Open banking and API banking are two terms that are becoming universally popular. They have the potential of radically transforming customer experiences and making banking experience a more personalised and less time-consuming process. It is important that banks, fintechs, investment houses and other payment service providers look into its potential and explore opportunities around it.

Change is rarely comfortable, but with the market evolving across countries, it is slowly coming across as inevitable. It will be better if banks start defining the trend rather than waging a futile battle to repel it.

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Like other businesses, if you too are looking to develop IT Solutions in Financial Services industry, Mindfire Solutions can be your partner of choice. We have gained significant experience over the years working with Fintech Companies. We have a team of highly skilled and certified software professionals, who have developed many custom solutions for our global clients over the years.

Here are a few interesting projects we have done with API in Fintech industry. Click here to know more:

Case study on Student loan approval system

Case study on Smart card for pocket money

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CREDIT UNIONS

Reimagining member experience for Credit Unions and Microfinance Banks

FintechMindfire Solutions

Introduction:

Consumers today are more inclined to turn to credit unions due to competitive product pricings and personalized services. Building on these strengths and showing commitment to local communities, is a strong way for credit unions and microfinance organizations to attract and sustain loyal members.

To reimagine member experiences for these organizations, it is important to build on member engagement, technology and personalization. An important part of attracting new members and retaining the existing ones is by knowing who they are and what they want. This information can be utilized to provide data that can be managed, assessed and analysed to exceed the member’s expectations.

What areas should credit unions focus on:

Personalization:

Having one-on-one and personal interactions with your members is an important part of increasing members. Adding a personalised and human touch in the times of digital connectivity makes an interesting experience to begin with. Some of the ways in which credit unions and microfinance banks can add a human touch to their experiences are by following the strategies below:

1. Creating a culture when members can speak and feel heard

2. Customer engagement through surveys and feedback taking processes.

3. Share member feedback with other office members and management, including staff meetings

4. Acceptance of constructive criticism.

5. Matching staff experts to member needs because a tele-caller or a customer service executive might not be the best person to solve all needs

6. Hassle-free contact and communication experience for the member.

For example – if someone has a question about buying a home, they should be paired with a home loan or mortgage expert. This helps quicker problem solving and a smoother transition for both the interested customer and the bank. Various softwares are available to manage bookings between members and staff. Without a doubt, technology plays a big role in streamlining affairs for both parties.

In times of the Covid-19 pandemic, it is important to focus on targeted communication to build member loyalty. Periodic newsletters from experts in your company to members can help bridge the gap in times of uncertainty. This is a small way in which members can feel confident and included post the pandemic.

Relationship Building:

Across a spectrum of consumers, credit unions and microfinance banks have a core set of interests. As per a 2019 study by Accenture, most consumers said the following:

1. They expressed interest in a one-stop-shop for checking accounts and all the different loans.

2. 1 out of 2 customers said that they preferred customized services based on their spending habits.

3. They were comfortable with sharing data as long as they saw benefits in it and customer experience improved.

4. Integration of physical and online channels for a more integrated experience.

The report additionally found that consumers generally fell into one out of the four categories of pioneers, pragmatists, skeptics and traditionalists. This information helps to pay closer attention to each audience type along with the background and the demographic they represent. Credit unions and banks need to therefore ensure that they are meeting customer expectations.  Also, they can come up with a range of products and services, revamped for the post Covid-19 era and beyond.

Positive employee engagement:

Having a happy employee might not appear as an overt advantage, but an employee who is more comfortable at his workplace is bound to be more productive and build greater assets for the company. Flexibility in work schedules, a warm workplace and potential for growth are some of the parameters for employee well being.

The benefits of a positive employee experience include lower staff turnover, improved staff productivity, higher sales and better customer service. As per a latest study by MIT, company profitability can increase by 25% with high levels of employee experience. .

Thus, taking a proactive approach in recruitment, training and advancing staff skills means a better utilization of human resources who will be well equipped to local communities and a growing consumer base.

Technology Trends:

Majority of consumers prefer a superior digital experience over competitive rates and fees. While banks are investing billions to improve their mobile banking and overall digital experiences, credit unions and microfinance banks do not have the capital bandwidth to make that level of investment. But making some small changes can yield a huge impact for this sector. An easily navigable website for instance helps customers organize their time and queries better while avoiding long queues. It will also be helpful in guiding both potential and existing clients to find what they are looking for.

As per the 2020 Credit Union Innovation Index, only 11% of credit unions have innovated their data analytics in the past 3 years. Having 24/7 access to the credit union or microfinance bank through online chats is the easiest way to adopt digitization to ensure members feel supported and communicated with. Going digital is the best method of creating positive and accessible experiences for one and all. While digital strategies are associated with tech giants and industry leaders such as Amazon, Apple, Google and Microsoft, smaller organizations can adopt inexpensive and accessible strategies to improve overall customer experience.

How can Credit unions benefit from these trends:

There are online tools and digital channels that can not only prove to be an improved sales and marketing experience but useful for a personalized experience with your banking organization. This includes capturing big data to have a complete understanding of each community, geography and member.

One way in which one-on-one connections can be enhanced is by using appointment-setting software. Also, Dynamic queuing system can provide a quick and efficient way to cut to the chase for the customer.

CRM is also another important piece of the data analysis, an inexpensive medium to help track important members’ information such as birthdays and anniversaries. This can also help for further personalization efforts, spoken earlier in the article.

Credit unions and microfinances can improve their member experience by creating a data and digital driven strategy to strengthen employee engagement, embrace simple yet effective technology innovations and create a personalised experience for every member. Hence, CUs and microfinances can explore easy methods to drive member engagement.

In today’s tech dominated world, digital transformation cannot be overlooked by credit unions and microfinance banks. Attracting the younger, tech-savvy and smarter generations, will involve smarter products and services along with a higher trust quotient. This will in turn allow these institutions to be differentiated from the banking industry and not get lost amidst the growing competition of the post pandemic world.

Final thoughts:

Like other businesses, if you too are looking to develop IT Solutions in Financial Services industry, Mindfire Solutions can be your partner of choice. We have gained significant experience over the years working with Fintech Companies. We have a team of highly skilled and certified software professionals, who have developed many custom solutions for our global clients over the years.

Here are a few interesting projects we have done. Click here to know more:

Case study on e-Wallet mobile application.

Test automation of digital payments.

Case study on Smart card for pocket money.

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Virtual Health Services

Sustaining Virtual Health Services triggered by COVID:

Healthcare ITMindfire Solutions

Introduction:

Covid-19 was a challenge like no other. With a world connected like never before and intertwined economies the virus spread like wildfire across the globe. However, as they say, every new challenge is an opportunity to create a better and more secure tomorrow. Devastating as it was, the aftermath of Covid-19 toes the line. The pandemic saw academics, scientific community, medical professionals and data scientists come together to assess unique methods that are rapid and secure to tackle the crisis with virtual health services. Data sharing, a key component in creating solutions was incentivised along with model training and testing without the hurdles of conventional collaborations. Healthcare providers and researchers focused on addressing the challenges of meeting the critical clinical needs created by the crisis, with remarkable results.

As per the article Federated learning for predicting clinical outcomes in patients with COVID-19 published in Nature Medicine “The pandemic has emphasized the need to expeditiously conduct data collaborations that empower the clinical and scientific communities when responding to rapidly evolving and widespread global challenges.”

Since the Covid-19 outbreak, Investment in digital health has skyrocketed, Venture Capitalists are queueing up to invest in the digital healthcare more than ever before. Thus providing the impetus for further innovation. Artificial Intelligence(AI) is another sector which proves to be a strong pillar of support for the Data Scientists, Academicians, Healthcare Professionals and Regulatory Authorities.

Regulatory Changes:

There was a slew of regulatory changes brought in by the US Government to tackle the pandemic and ensure faster care to the patients. The regulations aim to improve the safety of the healthcare professionals. We look at some of the blanket waivers brought in during the Pandemic:

Emergency Medical Treatment & Labor Act (EMTALA): By waiving off the section 1867(a) of the act, it facilitates hospitals to screen patients offsite. This helps to prevent the spread of Covid-19.

Telemedicine: By waiving of certain sections related to 42 CFR, virtual health services became accessible to patients through an agreement with offsite hospital.

Quality Assurance and Performance Improvement (QAPI): This enabled the healthcare facilities to develop, implement, maintain and evaluate an effective and exhaustive data-driven QAPI. Thereby the hospital can solely focus on treating patients during COVID-19.

Electronic Case Reporting (eCR): The automated generation and dissemination of case reports from the electronic health record (EHR) to public healthcare agencies makes disease reporting faster and easier. It moves data securely and seamlessly—from the EHR at the point of care, to data systems at state, territorial, and local agencies. This also allows public health to provide information back to healthcare professionals. The timely data sharing provides a real time picture of COVID-19 to support outbreak management.

To cover the entire set of regulatory changes and waivers is beyond the scope of this article. For more details do go through the link.

Trends during the Pandemic:

The pandemic brought forth the need for an alternative method of healthcare and allied health services. While this blog is being written, digital technologies are being harnessed to help prepare for future challenges.

Dissemination of information from credible sources – IT platforms were widely used by regulatory authorities to deal with the misinformation and educate the masses about Covid-19. WHO rolled out the ‘Stop the Spread’ campaign across platforms. They also rolled out another campaign within the campaign Playbook to tackle the wastage of resources. The aim is to document and share innovative and good vaccination practices  to educate the countries and communities at large.

One sector which emerged as the sunshine sector during the Pandemic is the Telehealth. With regulatory changes which facilitated the accessibility becoming permanent like for eg; the reimbursable telehealth codes for the 2021 fees schedule for physicians, the sector is witnessing an expansion in terms of services that it can offer.

According to a report by McKinsey, Tele Health services has increased 38 times since pre Covid days. The report mentions that consumers continue to view telehealth as an important modality for their future care needs. But the view varies widely depending on the type of care.

In 2020, Mckinsey had estimated that the virtual enabled healthcare industry would become a $250 billion industry. Going by the recent trends the prediction is well and truly on course.

During the Pandemic the usage of Telehealth services surged as patients sought the safe access to seek virtual health services. Likewise for healthcare professionals it provided the luxury of discharging their duties without being on the frontline.

The Future Scenario:

During the outbreak of Ebola in 2015, workshops were organised by White House Office of Science & Technology Policy and the National Science Foundation broadly defined three areas where Robotics can make a significant difference. As a result, it set a precedence for handling Covid-19 pandemic.

• Clinical Care – Telemedicine & Decontamination

• Logistics – Delivery & handling of contaminated waste

• Reconnaissance – Monitoring Compliance

Covid-19 introduced a fourth area – contactless consultancy services. This opens up the future for Tele Health services with the possibility of remotely controlled robotic systems deployed to the frontline.

With 5G bandwidth and smart phones entering the public domain, the day won’t be far when Medical Conferences and seminars will be held virtually. As a result, this opens the door for virtual reality in the field of Medicine. Not only will such an initiative reduce infection rates, it will help in reducing carbon footprint as well.

During the pandemic, there has been an increase interest in decentralized and digitally connected rapid diagnostic tests to widen access to testing. As a result, this increase capacity and eases the strain on healthcare systems and diagnostic laboratories.

There is an urgent need for creating applications to predict future eventualities, availability of essential medical services and optimising medical resources. IT and IT based solutions is a force multiplier for the healthcare sector. The applications are efficient, fast and accurate. The other important aspect is that IT based solutions are cost effective. This makes healthcare accessible with virtual health services and reduces the burden on the Government and Hospitals. It is the future of medical services to meet the global demand of equitable healthcare.

Technology trends shaping the post Covid world:

Over a period of time, Artificial intelligence (AI) has evolved by leaps and bounds in detection, diagnosis, and treatment of diseases. In India, City Scan has helped in proof reading for Radiologist’s and reduced the time lapse for diagnosis. Similarly, eye testing etc. are widely using AI for faster diagnosis and treatment. Artificial Intelligence applications with proper implementation can address the global health care inequalities that exists today.

During Covid-19, Artificial Intelligence based technical models provided the following:

• Helped in reducing the response time to patients.

• Giving predictive models of mortality.

• Inventory management.

• Predictive model for scanning the wave of Covid-19.

• Predicting the end and resurgence of the wave.

Deep learning, a facet of machine learning, is based on artificial neural networks. It provides the healthcare industry with the ability to analyse data efficiently with pinpoint accuracy. It has the ability to reduce admin work and increase insights into the patient’s condition and requirements. This helps medical professionals to focus on their job – that is to save lives.

Along with AI and ML, Semantic analysis and Deep learning will be the buzz words in the medical field in the near future. Together they open up a possibility of transforming the sector altogether.

Digital technology can aid in the clinical research with symptom based case identification. During the Pandemic, online symptom reporting was done in Singapore and UK.

Final Thoughts:

With the global population going Tech Savvy, it has enabled virtual health business models to include a range of services. For eg: enabling longitudinal virtual care, integration of telehealth with other virtual health solutions, and hybrid virtual/in-person care models. It has the potential to improve consumer experience/convenience, access, outcomes, and affordability – Digital Healthcare is one for the future.

With increased awareness, the world is now more than ready to move from the norm and embrace the new.

Like other businesses, if you too are looking for IT Solutions for Healthcare Services, Mindfire Solutions can be your partner of choice. We have significant experience over the years working with Healthcare IT Companies. We have a team of highly skilled and certified software professionals, who have developed many custom virtual healthcare solutions for our global clients over the years.

Here are a few interesting projects we have done to develop virtual health solutions. Click here to know more: Case study on managing high risk patients.

Case study on PWA for mental health.

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SMART PARKING

Smart Parking Solutions

Transportation Application DevelopmentMindfire Solutions

Introduction:

With the increase in vehicular traffic in the urban landscape, authorities’ world over are grappling with parking issues. Such is the importance of parking spaces these days that parking convenience decides the footfall of say a movie theatre, mall or for that matter any public space. Convenient smart parking spaces come at a cost and are the most common area for conflict for urban planners, architects, builders and civic authorities.

With space at a premium and a burgeoning population, the pressure to find a solution to this growing problem is immense on the stakeholders. The question that automatically arises is – Can IT solutions if not eradicate but help ease out the parking issues.

We look at some of the ways IT can help develop smart parking solutions which has helped in sorting out the parking issues.

Satellite Parking Planning:

One of the solutions which is gaining momentum to solve the Parking conundrum is using Satellite imagery to solve the parking issue. Now Satellite imagery isn’t enough to solve the problem on its own. It has to be integrated with high resolution imagery and machine learning to spot vacant parking slots.

How this generally works is collecting images from Satellite and using specific satellite based algorithm to enhance the image resolution.  Then, through a set of machine learning applications vacant parking slots are detected.

Challenges:

First and foremost is the High Resolution Satellite imagery and second is the Cost. Without high resolution images and cost effectiveness, this won’t be a fruitful venture.

As the quality of images varies from satellite to satellite. The effectiveness of Satellite Parking Planning will depend a great deal on pairing the imagery (both low and high resolution) from various satellites and quantify those in machine learning algorithm.

The interface needs to be customised as different agencies and clients will have different UI/UX interface requirements. There will be instances where the Satellite images might not be available, then drone images or photographs from aerial photography can help to fill the gap. Create coherency between Satellite data and physical maps.

Solutions:

Creating a technical architecture for sourcing and processing satellite images with Artificial Intelligence along with Deep Learning to improve accuracy. Form partnership with companies that specialises in particular skill set to lower the cost.

‘The Research Institute for Housing America, part of the Washington, D.C.-based Mortgage Bankers Association, used satellite imagery and tax records this year to tally parking space totals in different – sized U.S. cities. It determined that outside of New York City, the parking densities per acre far exceeded the population densities’ – Excerpt from People Over Parking published in Oct’18 by American Planning Association.

The European Space Agency teamed up with an Austrian based start-up Parkbob to provide Satellite Driven Parking Services. Satellite Parking Planning will be an important milestone for developing advanced digital last-mile solutions and a great proponent of how public-private partnerships can aid implementation of new technologies in the market.

1. Access Point:

Access Points or gateways detect the passage of vehicles in and out of the parking zone in real time. This gives the authorities and the drivers accurate information on the accuracy levels of the parking zone at all times.

The Real Time information is important, as it saves the driver the hassle of searching for a parking space. Moreover, this leads to the  ripple effect of less congestion at parking lots, reducing fuel consumption and carbon footprint. The sum total of all this is Less Pollution. Thus, Access Points enables transport regulators to manage public parking zones optimally.

How does the system work?

Access Points receives data from the sensor nodes and send them to the data processing centre in real time. From a hardware point of view, the characteristics of the Access Points and Sensor Nodes are similar, except that unlike sensor nodes, they don’t perform the function of packing and unpacking of the data.

The Access points communicate with the sensor nodes using IPv6, the acronym for 6LoWPAN (Low Power Wireless Personal Area Network) communication protocol. If there is a node in the data centre acting as a border router, communication between the base station and the gateway will be done by 6LoWPAN. However, if the gateway is located very close to the data centre, a RS-232 (Recommended Standard 232. It is one of the oldest yet popular communication protocol for transmission of data over medium distances.

2. Parking Sensors:

Sensor based parking concepts are popular because they are cost effective & non-intrusive system of managing parking spaces. It’s based on wireless networks of photoelectric sensors that are deployed at various access points on the roads especially the entry and exit points.

The sensors detect the passage of vehicles and relay the information to the data centre. For instance, this gives accurate information on the number of vehicles and the occupancy levels in real-time. Thus, the data centre in turn relays the information to the drivers and authorities. This facilitates the former in finding an appropriate parking space and the later to take steps to control traffic in case of congestion.

Smart Parking Systems typically have pavements with built in sensors as well as overhead vehicle detectors for monitoring the availability of the parking spaces. These sensors use advanced algorithms for vehicle tracking. They also have the ability to determine if the location of a stationary vehicle corresponds to that of a parking facility or not. Since the sensors provide real time overview of parking space occupancy, Law enforcement bodies can use the service to get data on parking violations. They can check if a car is parked on a lane reserved for emergency vehicles or a cycle path.

As mentioned earlier Sensors are a popular choice amongst authorities and stakeholders for smart parking facilities in urban areas. Since the subject is a wide ranging one, where each section can be a blog in itself, we will delve on the gist of the various types of sensors used to mitigate the parking issues just to get an insight.

Types of sensors:

• Vision systems – are based on digital sensors embedded within industrial cameras and optics. They help to acquire images. A sensor capable high definition camera (usually Raspberry Pi V2 camera is preferred) along with the revolutionary OmniBSI technology (high sensitivity in low light, low cross talk (improved image resolution), and low noise), it can identify an automobile’s license plate, when the presence of a vehicle is detected in the parking space.

• Radar Sensors – These sensors generate 2D images with the help of artificial intelligence. In other words, the trained neural network synthesises the images displaying the status of the parking space. These sensors offer the option to use one powerful device to cover multiple vacant parking slots.

• Magnetometers – Use the surrounding magnetic field to detect vehicular movement. It comes fitted with RFID (Radio Frequency Identification) enabling on-street parking reservation.

• Ultrasonic sensors – Emits sounds waves at a particularly frequency to detect whether a particular parking spot is vacant. However, the effectiveness and accuracy of these sensors means that they are being incorporated in many of the smart parking solutions. Ultrasonic sensors have evolved thanks to continuous technological advancements. With LPWAN (low power wide area network) technologies such as LoRa (connects sensors for transmission of parking space status), ultrasonic sensors have high detection accuracy.

• Infrared sensors(IR) – When an object comes closer to the sensor, the infrared light from the LED reflects off the object. This helps to trace it from receiver’s end.

3. Cloud Based Parking Systems:

The sensors detect the location data of automobiles and occupancy of parking spaces. This is transferred to the cloud gateway. From there the network server processes it. Above all, the drivers and automobile rental managers can access the data. This gives them an insight into the parking space status.

How does the system work?

Cloud Based Parking Systems use the web service for reading and sending data to the sensor network using Play Framework. The framework is based on web-friendly architecture. Built on Akka, Play provides predictable and minimal resource consumption (CPU, memory, threads) for highly-scalable applications using Java technology. Moreover, it’s a modular framework with integrated unit testing (it includes support for JUnit and Selenium). It allows static methods, non-blocking asynchronous communication, and simple corrective maintenance.

The registration component consists of a database to store information on registered users, the number of sensor networks deployed, parking spaces available, etc. Due to its multiple usage and versatality PostgreSQL is mostly used to set up the database. PostgreSQL functions include transactions, referential integrity, views and a multitude of features. It also incorporates Multiversion Currency Control—MVCC—which allows other clients to access it without the need for locking. These features are suitable for systems that need to handle large amounts of data and a high number of concurrent users accessing the system simultaneously, as will be required by the proposed system.

Final Thoughts:

Smart parking solutions will have a significant impact on the urban life. It will aid the citizens and the Enforcement authorities in the following way:

1.  Offer real time monitoring of the parking spaces.
2.  Provide better safety and control for businesses and law enforcement authorities.
3.  Optimize space and time in a hectic urban environment.
4.  Predict the flow of vehicles by analysing parking routines at public spaces

Smart Parking Solutions will shape the landscape of the mega cities in the near future. If you too are looking for Smart Parking Solutions, Mindfire Solutions can be your partner of choice. We have significant experience over the years working with sensor and cloud based applications. We have a team of highly skilled and certified software professionals, who have developed many custom solutions for our global clients over the years.

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Java Spring cloud native applications

Why Should Startups Develop Cloud Native Applications Using The JAVA-Spring Framework?

Cloud NativeMindfire Solutions

Introduction:

Ever since the concept of cloud native applications came into the picture, it has become one of the most popular topics in the IT industry. Software developers have mixed opinions on this concept. Some people think it’s just a temporary trend and will fade away with time, whereas others believe that cloud native applications are the future of application development.

Irrespective of what may come tomorrow, cloud native application development has transformed the IT industry in today’s time, and its usage is only increasing day by day. The reason for the popularity of cloud-native applications is its numerous benefits. Prospects of the concept have captured the attention of business owners across the world.

Market Trends:

According to a latest industry report, the cloud native applications market is anticipated to reach a value of 166.8 billion U.S. dollars by 2024, with an expected growth rate of 6.1 % every year. Alibaba Cloud says that with the development of technologies like 5G and IoT in the coming years, most enterprises will adapt to cloud-native for application development and eventually become ubiquitous.

At the moment, many platforms offer cloud native application development. In this article, we will discuss why startups should consider developing apps using Java Spring Framework. However, before we proceed with that, let’s understand what we mean by cloud native applications and how they work.

Key Features Of Cloud Native Applications:

Cloud-native application development is a method of building and running applications for cloud-computing architecture. The cloud-native technology enables enterprises to create and run scalable applications in public, private, and hybrid clouds.

The cloud native applications were designed to take full advantage of cloud computing and are hosted in the cloud. Features of this technology include microservices, containers, APIs, and dynamic orchestrations. Let us understand these features one by one.

Microservices:

Cloud native applications are composed of microservices. Microservices refer to the collections of small services that are operated independently of each other. Each service consists of its unique data and caters to a specific need of the application. In addition, these independent services interact with each other through APIs.

APIs:

All microservices can communicate with each other through APIs and bind all the loosely coupled services. These APIs can also be built, deployed, and managed in a cloud or multi-cloud environment.

Containers:

Containers help to develop all the cloud native applications. Container is an isolated package of software that consist of the code and all of its dependencies. They allow programs to run in different computing environments and prevent microservices from interfering with one another.

Orchestrations:

Container orchestration tools assist in managing the container lifecycle, which can be pretty complex if done manually. Above all, these tools monitor the container, schedule starting up and shutting down of a container, balance load. It also sets relevant parameter and deploys them on the server cluster nodes.

These features of cloud-native applications have enabled enterprises and developers to embrace the latest technologies for developing applications more efficiently.

Some of the benefits of utilizing cloud native applications are:

Cost Effectiveness:

Cloud computing eliminates the need for external hardware and infrastructure required for load balancing. virtual servers help test Cloud-native applications. This allows to improve the applications’ performance. With the help of containers, the number of microservices increases. This saves a lot of resources and money for enterprises.

Scalable Solution:

As microservices are isolated, it is easily scalable, and other services won’t be affected. Above all, enterprises can utilize resources as per their requirements.

Portability:

Containers allow cloud-native applications to run in different physical computing environments.

Reliability:

Containers also prevent microservices from damaging each other. For instance, if one microservice fails, it doesn’t affect the services adjacent to it.

Zero Downtime:

With container orchestration tools such as Kubernetes, it is possible to deploy software updates without any downtime.

Automation:

By adopting cloud-native technology, enterprises can use DevOps automation features to deploy and deliver software updates continuously.

Benefits Of Using The Java-Spring Framework For Developing Cloud Native Applications:

Spring is an open-source framework that was developed by Rod Johnson in 2002 for developing Java-based enterprise applications. The framework offers comprehensive programming and configuration.

Modularity is one of the most impressive features of the Java-Spring framework; it makes the platform easy to use for developers. The framework is lightweight, therefore allowing applications to perform well without any glitches. In addition, Spring also provides containers for the management of the bean lifecycle.

The Java-Spring framework provides solutions to most of the infrastructure facilities within the enterprises. Hence, most of the heavy lifting is done by the platform itself. This helps businesses save money by not maintaining their on-premise infrastructure.

The process cuts down development costs across the board, hence making the Spring framework an ideal choice for cloud-native application development. Startups are always looking for a way to reduce production costs; therefore, the Java-Spring framework is the best way to develop applications.

Additional Benefits Of the Framework:

● The platform solves all the difficulties faced by any kind of business while developing complex applications. After that, to integrate different components of complex applications, it provides Spring Core, Spring IoC, and Spring AOP.

● It simplifies the development process by providing layers of technologies like servlets, JDBC, JNDI, RMI, JMS, Java Mail, etc.

● Developers can develop applications using the POJOs (Plain Old Java Object). It eliminates the process of importing heavy Enterprise containers during development. Therefore, this makes the process of testing easier and provides an option of utilizing a robust servlet container.

● The framework is already integrated with different technologies like the ORM framework, J2EE, JDK Timers, and other frameworks of Java. Hence, it does not have any restrictions on what frameworks to use. Therefore, startups don’t have to waste time and money on training their developers about these frameworks.

● Spring allows the use of XML configuration as well as Java-based annotations, which offers the fluidity to choose with any one of them.

● The lightweight containers of the Spring framework can be activated without any web server or applications server.

● It also offers the development of remote-enabled services via its arrays of APIs. Spring supports Remoting methods like Remote Method Invocation (RMI), Hessian, Burlap, HTTP invoker, JAX-WS, and JAX-RPC, allowing developers to focus on what is more important.

● The transaction management interface provided by the Spring framework is flexible and works in all the environments offered by JAVA. It enables developers to use local transactions in small applications and scale up to JTA for global transactions. This helps make it a relevant solution even when the business has grown.

Final Thoughts:

The benefits of the Java-Spring Framework cater to all the needs of startups for developing a world-class application. Startups  can reduce their workload by outsourcing their IT job to a service provider with a team of talented professionals.

Like other businesses, if you too are looking to develop cloud Native Applications, Mindfire Solutions can be your partner of choice. We have deep expertise in Spring framework. Moreover, we have a team of highly skilled and certified software professionals, who have developed many custom solutions for our global clients over the years.

Here is an interesting project we have done to develop a cloud platform for a retail solutions provider with JavaScript. Click here to know more: Case study on cloud based retail solution.

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Virtual Fitting Room Applications

Virtual Fitting Room Applications Are Developed Best Using JavaScript?

JavaScript, Virtual Fitting Room ApplicationMindfire Solutions
Introduction:

The continuous innovation and development of technology have led to the creation of Virtual Fitting Room Applications. Now customers don’t have to be physically present at a store for trying out any clothing items, beauty products, and accessories. You can do it virtually through Virtual Fitting Room mobile applications.

The virtual fitting room is a technology that has revolutionized the way retailers and E-commerce businesses are offering online shopping experiences. Virtual fitting room applications are based on technologies like Artificial Intelligence (AI) and Augmented Reality (AR). With these new innovative applications, buyers don’t have to leave their homes to check the size, fitting, and style of the products that they want to purchase.

Ever since the pandemic struck, in-store shopping has taken a hit. People are hesitant about going out to retail stores and trying out things themselves. Based on a survey conducted by a leading advisory group, more than half of women and men who visit the store don’t feel safe trying out clothes in the store dressing room.

Market Trends:

As lockdowns were happening globally, clothing products saw a decline of about 43% in sales. But virtual fitting room technology is changing these numbers, and retailers are slowly getting back in the business. After the Covid-19 pandemic, the demand for virtual fitting rooms is increasing drastically.

A report predicted that by 2025, the market for virtual fitting would reach the value of 6.5 Million U.S dollars. According to an industry report by Statista, the global market size for virtual fitting rooms is expected to reach over 12 Billion U.S dollars by 2028.

Many platforms and languages can be used while adopting this technology. In the following article, we will discuss why virtual fitting rooms applications are best developed with JavaScript.

In order to understand why JavaScript (js) is the best way to develop a virtual fitting room application, we need to know how the concept of virtual fitting rooms works.

How Does Virtual Fitting Room Technology Work?

The virtual fitting room works on Artificial Intelligence (AI) or Augmented Reality (AR). In the case of Augmented Reality, a person’s body is scanned with a webcam to create a 360 degree-3D model of the body. The virtual fitting room apps that work on AI utilize machine learning algorithms to create a 360 degree-3D model of a body.

Irrespective of the technology used to scan the body, post scanning, the 3D models are combined with Radio Frequency Identification (RFID). The RFID keeps track of the products that the buyer has added to the virtual fitting room.

Finally, the virtual fitting room technology lays the product of the user’s choice on the 360-degree 3D model of their bodies. It helps shoppers check whether the item has the proper fitting, styling and how well it suits them.

Benefits Of Virtual Fitting Rooms:

Here are benefits that virtual Fitting Room Applications can offer to retailers:

● Support online sales:

Virtual fitting room application provides an enhanced shopping experience for the customers. A research paper shows that 40 % of shoppers are willing to buy more expensive products if they experience shopping through augmented reality features. Thus, virtual fitting room applications are increasing the online sales of enterprises.

● Increase customer Retention:

The virtual fitting room applications increase the target audience’s engagement with the brands and retailers. It allows shoppers to see for themselves how the product will look on them. Therefore, customers keep on trying various items, and the retention time goes on increasing. The businesses that have used virtual fitting room applications witnessed a 5 percent boost in their retention time.

● Decrease in product Return:

One of the reasons for high returns was the wrong fitting of the product. But with virtual fitting room applications, these blunders can be avoided. After opting for this technology, a retail company reported about a 36 percent decrease in the returns rate.

Why Use JavaScript To Develop Virtual Fitting Room Applications?

JavaScript is an object-oriented programming language which helps to develop dynamic web pages and applications.

As virtual fitting room applications are based on AI and AR, JavaScript is one of the best languages you can use to develop them. From the surface, it may seem like a strange choice as most enterprises use programming languages like Python or Scala for their AI/AR-based projects.

But JavaScript has some advantages that can add more value than Python or Scala. Here are some reasons why JavaScript is the best language for developing virtual fitting rooms.

● Excellent Performance:

Millions of dollars are invested in JavaScript so that it can run fast. Modern JavaScript is more advanced and translates machine code as same as Java. This allows AI-based applications to perform better in JavaScript.  Hence virtual fitting rooms can offer a more superior user experience than Python and Scala.

● Less Development Time:

We all already know that Python has less development. The same is the case with JavaScript. But the development time for JavaScript is a little quicker. Synaptic, the neural network library of JavaScript, has various features, which gives js a bit of an edge in AI-based application development.

That doesn’t mean that Python is not good. When it comes to adopting deep learning technology, there is no competition to Python. Both languages have something unique to offer. As development times go down, the production costs also go down. Hence enterprises can save a lot by using JavaScript for developing virtual fitting rooms.

● Improved Security:

JavaScript comes with built-in security. Therefore, JavaScript prevents any attacks to the application by malicious codes.

● JS has separate library for AR Features:

JavaScript offers a library named ‘AR.js’ that can provide Augmented Reality features to any web-based application using a few lines of HTML. It is a free, open-source platform and has been used by many developers. In the GitHub repository, AR.js has more than 13,000 stars.

One of the benefits of using the AR.js framework is its cross-platform and browser compatibility. This means that the web app developed on the platform is compatible with iOS as well as Android.

The AR.js comes with different AR frameworks like A-frame, ARToolKit, and three.js, making this framework very easy for developing AR-based web applications. It offers a high performance of 60fps, even older devices, so there is no need to spend money on external hardware.

That being said, AR falls short in some instances as compared to AI. There are some rendering limitations to AR. The tracking accuracy of the Augmented Reality technology is too low, which can compromise the application’s user experience. Therefore, AI in collaboration with AR helps to avoid these glitches and make the technology more effective. The data rendering done in AI is more accurate than AR technology. It also provides better identification of body parts of the 3D model.

Final Thoughts:

From the benefits listed in the above section, you can see why JavaScript is the best choice for developing AR or AI-based web applications such as virtual fitting rooms. The language is easy to code, offers better performance, provides a framework and library for adding AR features, and is even cost-effective in many aspects

The virtual fitting rooms are not only limited to the clothing industry; they are also relevant for shoes, watches, sunglasses/ spectacles, cosmetics, and jewelry. Anything wearable and used as a styling option can be paired with virtual fitting rooms applications.

Instead of hiring developers to create a virtual fitting room, retailers and E-commerce platforms can outsource this job to a service provider with relevant industry experience and reduce the workload.

Like other businesses, if you too are looking to develop Virtual Fitting Room Applications, Mindfire Solutions can be your partner of choice. We have deep expertise in JavaScript . We have a team of highly skilled and certified software professionals, who have developed many custom solutions for our global clients over the years.

There is an interesting project we have done to develop a virtual fitting room application for an advertising and content management company with JavaScript. Click here to know more: Case study on fashion imagery solution.

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React vs Angular

React vs Angular to develop Single Page Application

Angular JS, ReactMindfire Solutions
Introduction:

Single page application (SPA) is a website or web application that interacts with users by rewriting the current web page dynamically with updated data from the web server, rather than loading complete new pages as is the default approach. The objective is to make the website seem more like a native app with quicker transitions. The page does not reload or transfer control to another page at any time during the process.

Huge companies around the globe are using Angular and React. Companies like Whatsapp, Instagram, Facebook, Netflix, Uber, Airbnb, Dropbox etc use React. Whereas, companies like Google, Nike, Forbes, Sony, HBO use Angular etc.

The market for front-end development frameworks and tools has grown highly competitive. Angular and React are the most popular JavaScript frameworks and libraries among developers which are new. These are well-supported technologies for developing front-end apps. Despite the differences between them, developers use these frameworks to create single page application (SPA).

React:

Facebook and a network of individual developers and communities manage React and it is one of the most popular frameworks. React is a strong, adaptable, and extremely flexible framework that allows its components to be used across various applications.The framework is used by most React development services due to its “learn once, write anywhere” approach and code reusability to create rapid and scalable programmes for all platforms. Its component-based and declarative characteristics make it simple for developers to design interactive and sophisticated user interfaces.

Angular:

Angular is one of the most flexible JavaScript frameworks for web app development, with a wide range of capabilities. It has a lot of features, is quite strong, and gives you greater control over your web application. Angular is a typescript-based programming framework. It’s a component-based framework for building highly scalable web applications. It comes with a number of well-integrated libraries and features, including client-server communication, routing, and more.

Comparision between the two technologies to develop single page application:

Angular and React are inherently different in several ways, therefore we must establish a common ground for comparison

● Document Object Model (DOM):

Angular employs real DOM, which means that if a single section of the tree data structure is changed or modified, the entire tree data structure is updated. In React app development, however Virtual DOM is used, allowing app development companies to track and update changes without affecting other sections of the tree. In the react versus angular race, React wins because Virtual DOM is more fast.

● Data Binding:

Data-binding refers to the connection between the component’s logic and the data it displays. Angular which is bidirectional supports two-way data binding by connecting the Document Object Model (DOM) values to Model data via the Controller. Whereas, React being unidirectional uses one-way data binding, which allows you to direct the flow of data in only one direction. Although two-way data-binding can be implemented with React, by default, a component’s and view’s connection is always one-way. We can add logic to a component to make the connection two-way.

● Performance:

The rivalry between the two frameworks intensifies, with none falling behind in terms of performance. But,the performance of Angular is comparatively slower due to the two-way data binding. The two-way flow of data often causes performance concerns. Server-side rendering becomes faster thanks to React’s virtual Document Object Model. React apps perform better as a result of this.

● Componentization:

Angular has a very fixed and complex structure as it is constructed on three layers: Model, View, and Controller. Developers use Angular to break the app’s code into different files. This enables the reuse of templates or components in various parts of the application. React, on the other hand, opts for a distinct architecture. It provides a straightforward method for creating component trees. The library includes functional programming, including declarative component definitions. React code is easy to read and rationally structured. JavaScript developers can more readily transition to React thanks to reusable components and clear coding.

● Directives:

Angular Directives allow us to organise our code and operate around the DOM. These directives give us access to the DOM when working with Angular. Apart from the directives that come with it, developers can also write their own.The templates are returned with attributes in Angular, and the syntax of Angular’s directives is sophisticated and complex. This makes it confusing to new developers. This distinction between templates and directives does not exist in React. The template logic, or directives, must be written directly in the template. At the end of each component, the logic and templates in React are discussed. It allows readers to comprehend the meaning of the code without having to know the syntax.

● Learning curve:

When compared to React, Angular has a steep learning curve. The Angular framework allows you to tackle a problem in a variety of ways, has a complicated component management system, and necessitates knowledge of various concepts and languages. Furthermore, the framework is constantly evolving, necessitating the need for developers to keep up with what’s new in the Angular ecosystem and to upgrade their skills accordingly. However, React allows you to quickly learn and create an app in the React ecosystem. If you are familiar with JavaScript, React becomes much more easier to learn. It has several valuable tools for newbies to grasp the framework and construct a single page application.

When to use React?

Both Angular and React are excellent choices for developing single page application. The choice between the two is mostly dependent on the project at hand.

● React is a better choice as it has a lower learning curve because existing JavaScript and HTML code may suffice, which allows for faster development. However, as time goes on, developers will need to learn more advanced technologies

● React outperforms Angular, because of its virtual DOM implementation and rendering optimizations. It’s also simple to switch between React versions; unlike Angular, where you have to install updates one by one.

● React has the advantage of allowing segregated debugging, which aids developers in achieving app stability. Furthermore, React’s component-driven architecture allows us to reuse components, reducing development time and expenses.

● Using React, developers have access to a wide range of pre-built solutions. This reduces the number of errors while also speeding up the development process. React’s library can be incorporated into any project (even if it is made with Angular).

So, when to use Angular?

● The team is familiar with Typescript.

● The app’s complexity ranges from low to medium.

● You prefer ready-to-use solutions and want to increase your productivity.

● You wish to use the CLI option Bundle Budgets, which alerts developers when the application bundle size exceeds a predetermined limit. In other words, if you want to control the size of your app, Angular is the way to go.

● You need a feature-rich, large-scale application.

Like other businesses, if you too are looking to develop Single Page Application, Mindfire Solutions can be your partner of choice. We have deep expertise in both React and Angular. We have a team of highly skilled and certified software professionals, who have developed many custom solutions for our global clients over the years.

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Sentiment Analysis

Sentiment Analysis in Healthcare

Healthcare Application Development, Healthcare ITMindfire Solutions
Introduction:

Sentiment Analysis refers to analyzing text data and assigning some kind of sentiment to it. For e.g., we see a movie review on the IMDB website such as – “It was a good movie”. We can understand that the viewer liked the movie and we can go on to say that this review can be assigned a positive sentiment. Similarly, If the review was “It was a bad movie”, we can consider this as negative feedback for the movie and say that it generates a negative sentiment. So how do we go about creating a model that takes in a review/ statement as input and gives out the corresponding sentiment ?

One way to go about it is to create a dictionary of all words that correspond to positive feedback, and another of all words that provide negative feedback. Run a search through the statement and see which words are present. This is a very very simple example of how Sentiment analysis can be done. More on this later, but why would we need a Sentiment Analysis model?

Most companies provide their customers a platform, which could be social media or a company website, to express their feelings about a product or service so that the company can then use this data to improve the quality of their product / services. Since people can post feedback at ease with just their mobile phones, this generates a huge amount of data. Going through all data manually is a labor-intensive process. Hence, sentiment analysis has become an important tool for companies to track and monitor their online feedback and brand value. This is just one example; there are other areas as well where one can use a tool such as sentiment analysis. Let’s look at how it can help to solve some challenges in the Healthcare Industry.

Defining our Input to the model:

Before we discuss the details of the model, we need to find a way to represent sentences for a model to understand. The first approach is bag of words. The way this approach works is we first create a vocabulary of all words we have in our training data. This vocabulary then forms our feature space, or our X’s for the training. Given the number of words in the English language, we could have 10000 words in our vocabulary. We will get to reduce our feature space later.

So now that we have our X’s, we define a way to represent a sentence. We can do so by assigning the count of each word to our feature space. Coming back to our previous example, “It was a good movie”, we will have the following counts or word frequencies- It:1 , was: 1, a: 1, good:1, movie:1. The values for all other words will be 0. Each word will have a fixed position on our feature space, so for all other words, if we substitute zero then we have 0, 0,0,…,1,0,,…1,0…0. Note we have counts only at the position of the words in our current example. This type of encoding is also called one hot encoding.

We can limit the number of words our vocabulary has by using a few tricks, for instance removing words like a, the, this, is, etc. These words do not generally add any meaning to our sentences. These are stop words. Next, to further limit our vocabulary, we can keep only those words that have a frequency above a certain threshold. Doing this, we can reduce our vocabulary to 1/10th of our initial size. Now coming to encoding our target variable. Since this is a good review, we have 1 as our target variable. Note that we are only trying to classify good or bad reviews and having a 1 for good and 0 for bad is sufficient for training our model. All of these can be achieved by a few lines of code using python’s NLTK (Natural Language ToolKit) library and python’s Scikit-learn library.

Defining our model:

Machine learning can broadly be categorized into two parts, supervised and unsupervised learning. Supervised learning is one where we give both input and targets as training data. This is generally used for classification or regression tasks. Unsupervised learning contains just input data, no output is associated with it, and this is used for clustering problems, where the algorithm tries to group the input data into clusters. Since this is a classification problem, we will be classifying the review into one of the good or bad classes, we will rely on either Logistic regression or Random Forest classifier.

We will go into the details of logistic regression or Random Forest in a different article. But for the purpose of this venture, we will pass a python list (arrays) to the model. This is the input list that we get using one hot encoding as defined above, and get a one or zero as an output. Let’s assume the model we build has around 80% chance for classifying a given review accurately. This may not necessarily be difficult to achieve for a task such as this. All of these can be achieved fairly easily using python’s Scikit Learn library.

Problems faced by the service Industry and Solution with Sentiment Analysis:

An insurance company wants to find out whether imparting behavioral training to their service staff has an impact on the overall feedback they receive as reviews.

We start by defining a metric for valuation. Let our performance indicator be the number of positive reviews/ total number of reviews. Assuming there are at least 30 reviews for each staff under consideration. We get the reviews for all staff before and after behavioral training has been imparted. Put them through our model and generate positive and negative outcomes for these reviews. Then do a comparison of percentage positive and negative reviews before and after the training. This will establish a correlation between training and change in reviews. To establish causation, we also need to create treatment and control groups. The treatment group will have the staff that receives the training and control will be the staff that doesn’t. Comparing the change between treatment and control groups will tell us whether the training has an impact.

Like other businesses, if you too are looking for solutions in Sentiment Analysis, Mindfire Solutions can be your partner of choice. We have deep expertise in AI and ML Capabilities. With a team of highly skilled and certified software professionals, that have developed many custom solutions for our global clients over the years.

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