How Machine Learning Changing the Landscape of Mobile App

Machine Learning For Mobile App

How Machine Learning Changing the Landscape of Mobile App

The technology that promises to bring massive changes in the world in coming years is Machine Learning (ML). Machine Learning is a subfield of Computer science’s Artificial Intelligence research and got the highest attention in business.

Machine Learning and Artificial Intelligence represent a new era in software development where computers, gadgets, and other devices don’t need special programming to accomplish task anymore. Instead, they can be gathered and analyze that information that is needed to draw appropriate conclusions and learn during program performance for the App Development. Now machines can be going to perform these tasks on behalf of human beings. Indeed, the process of learning requires special algorithms that would “teach” machines. That is why, at the App solutions, we have to include machine learning in Mobile App Development.

How to use Machine Learning for Mobile App

The primary purpose of Machine Learning for Mobile App is to produce computer algorithms for automatic processing. Instead of writing code, developers just need to include the data into the algorithm which automatically improves itself by finding patterns in the data, put the necessary logic along with this for solving the task and produce the outcome.

There are two main ways within machine learning, Multimedia content analysis and Data Mining, which is a trend prediction based on Big Data. Each of these has the ultimate objective is to construct different models that become a base for App Development Solutions.

As an outcome, we have Mobile Apps with built-in Machine Learning algorithms can implement highly intellectual tasks that were previously accessible only to a human brain.

Machine Learning brings new opportunities for Apps

Machine Learning opens a way to perform various intellectual tasks along with normal Mobile Applications. Let’s take a look at opportunities which is explored by Machine Learning for Mobile Apps.

  1. Image and Video Recognition

Image and Video Recognition use in Mobile Apps very often. As an epitome, face recognition works perfectly for user identification within chat Apps, Dating and meting Apps, Photo editing Apps, and many others. Besides, with Machine Learning Developers create Models for age and gender determination. Moreover, you can find some models have biometric Recognition including fingerprints and eye retina recognition. Such detailed data can apply to entry pass and Security systems.

  1. Optical Character Recognition (OCR)

OCR use in other tasks of multimedia content Recognition. It is hardly a secret that automatic character recognition can save a lot of time for people. With this feature of Mobile Apps, users can easily recognize documents or credit cards and translate foreign words on different images. This task doesn’t seem so easy to solve because a text has many characteristics, from fonts style to a word length. Each Machine Learning model should be created with respect to these features. We learned this while developing a solution for receipt recognition and extracting meaning from receipts.

  1. Audio Recognition

We all are using Smartphones and we have used so-called Mobile Digital Assistant like Apple’s Siri or Google’s google now, then you probably know that all these programs use voice recognition algorithms. Currently, these tools don’t always interpret you perfectly, but they can improve in the future with the help of machine learning methods. Now the problem of audio recognition is very crucial and urgent. Initially, the solution would allow you to create texts by simply speaking.

Moreover, Voice recognition has highlighted the IT industry in many ways. Today Giant companies have launched their separate devices for audio recognition such as Amazon’s Alexa. That can be integrated with dedicated Mobile Apps. So, we can say that speech recognition through Machine Learning will going to the boom Mobile app Market.

  1. Analysis of Sensory Data

The Mobile App Market has a variety of fascinating Apps for encouraging a healthy lifestyle and tracking those sports events of the user. Current Apps are able to track heart rate or count steps. With the advanced Machine Learning models, the fitness tracker can be upgraded via continuous monitoring of the user’s physical activity without any additional instruction from the user side. In other words, users do not have to change the settings when they are going for a run or a bike ride. It can implement using sensors integrated with the App.

As an epitome, an app for patients suffering from strokes, epilepsy, and migraines solves a similar tracking task. The solution is designed to let people monitor their health conditions, process them with a machine learning algorithmic methods, and save from critical situations by sending alert to the emergency contacts or caregivers. When Users shake their smartphones, the app departed from emergency shakes and everyday jostling and sends an SMS to designed recipients who can help.

Industries which implement Machine Learning for Mobile App

  1. Retail industry

Mobile Applications for retailers can be customize using Big Data Analysis. Moreover, it is possible to add the function of receipt recognition with additional opportunities to make shopping lists that can help to increase customer reliability.

  1. Smart Houses

Smart Technologies for managing your own house continue to in progress at the same rapid pace as machine learning models. ML methods can apply to create apps for remote monitoring of smart houses.

  1. Healthcare organizations

Using health tracking apps, healthcare facilities can automate the process of tracking their patients when they are outside the hospital. Additionally, it is possible to recognize tomographic images for more precise indicators of human health. As an example, a well-trained system might determine tumors at the early stages with high accuracy.

  1. Financial Institutes

Financial institutions can use the identification of customers during financial operations in mobile Apps. Also, data mining algorithms would be useful for revealing customer history.

Conclusion

Machine Learning opens up a new window towards Mobile App Development. The implementation of this technology in the mobile app gives a really good outcome for various industries. It will increase the entertainment and reliability of app users. Ultimately, by adapting Machine Learning for Mobile Apps, your business will grow and it will help to generate Revenue.

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Vidhi
vidhi.pansuriya@tecocraft.com
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