Creating Flutter Application Integrated With Artificial Intelligence
The rapid growth of digitization has successfully paved the way for emerging technologies that lead to better user experience. We are into the fast-paced life cycle where users want everything at the super-fast speed, especially when it comes to accessing the mobile applications.
Some survey reports have discovered that the users uninstall 77% of the apps in just three days after downloading. The studies have revealed that the average speed of apps is not as per the expectation level of the users, and this is one of the major reasons for abandoning the application.
Undoubtedly developing a mobile app has become an urgent need of an hour for businesses. Still, they often overlook the fact that how to succeed in a cut-throat competitive market where already 5 million applications are available in various business domains.
The partial ratio of the businesses still believes in adopting a traditional approach of mobile app development and investing in building native apps. While the rest percentage of companies, who understand the rapidly changing needs of the market and strive to adopt latest technologies are excitedly looking into the world of cross-platform app development solutions as it is more device-agnostic and ensures multiple platform coverage.
And one such well-designed and feature-rich framework to develop cross-platform applications is Flutter.
Google has yet again stolen the show by launching a highly versatile and remarkable concept, FLUTTER!
Flutter is a cross-platform mobile app development framework that provides an advanced software development kit to developers to build a highly beautiful interface for both Android and iOS devices.
Despite being young and newly launched technology, Flutter has quickly paved their way in the leading frameworks and secured its position as the second most used and loved frameworks globally. According to a 2020 developer survey, Flutter is the second most popular cross-platform mobile framework used by 39% of global developers.
While developers are well aware of the effectiveness of this leading frameworK, but now its time to focus on another leading technology that has been widely integrating in mobile applications and that is Artificial Intelligence (AI)!
Now the question is, how to integrate Artificial Intelligence or AI in Flutter Mobile Applications?
This post is all about the detail discussion on how to blend these two wizards and what is the outcome of this collaboration!
Before learning how to integrate the AI technology in Flutter apps, let’s understand why we have chosen to alliance with the Flutter app with Artificial Intelligence…
Artificial Intelligence: Increasing Impact of AI on Mobile App Development
The computer and technology has again taken the momentum with the launch of phenomenal technology that is Artificial Intelligence. While the concept of Artificial Intelligence was launched in 1950, with the significant advancement and innovations, now AI has become a rising star in the mobile app development services.
And this technology is still in a continuous motion of bringing out some of the unique and refurbished methodologies that can add a perfect edge to the business growth.
Some of the most successful AI practices that help in increasing User Experience are:
- Personalised Shopping Recommendations: According to studies, 80% of shoppers are more likely to buy from the brand that offers a personalised experience and businesses have noticed 20% of hike in their sales after using personalised experiences.
- AI-driven Chatbot: The addition of chatbot to your website or mobile application can lead to better customer services. Therefore, the market size of a chatbot is projected to grow from $2.6 billion in 2019 to $9.4 billion by 2024 at an annual growth rate 29.7%.
- Voice Optimization: The impact of voice optimization on modern mobile app development can ensure an excellent level of convenience regarding accessibility and navigation; therefore, approx 20 billion by 2019.
In recent years, AI has become a buzzword in the market of mobile app development and adoption of AI will keep continuing to increase as it is generating tremendous returns, managing business risks, retraining the workforce and scaling impact.
According to the McKinsey survey report, 63% of respondents report AI is delivering meaningful value to companies.
Besides, the global Artificial Intelligence Software market is forecast to grow at the fast-paced in coming years and projected to generate 126 billion dollars by 2025. The wide range of applications included in the overall growth of AI are natural language processing, robotic process automation and machine learning.
As the leading tech companies are rapidly showing their interest in AI investment, more and more users will continue to see the integration of this technology in products and applications.
Till now, AI technology has put their best foot forward in healthcare, education, finance and ecommerce sector, but still, there is an excellent scope of launching mobile applications integrated with AI in the other promising areas.
Early Adopters of Artificial Intelligence in Applications
That’s not all! Many of you are wondering, whether integrating the AI in your mobile app will be a worthy decision or not? So let’s take a quick tour to some early adopters who set the benchmark in the industry by blending their business app with ML and AI.
1. Google
No one doubts the smartness of Google. But what makes it so smart? Have you ever thought of it? Definitely- emerging technologies like Artificial Intelligence and Machine Learning.
It could be surprising to know that Google was the first that sensed and leveraged the power of AI and integrated it in its plethora of products, including Gmail, Google Assistant, Google Translate and others. They served as the announcers in bringing about the popularity of using AI in applications to uplift the performance and deliver the more excellent user experience.
2. Netflix
Netflix has become a leading video streaming app in marketing, generating million dollars of revenue. Right from the interface of the app to infinite treasures in it, this app has so much to keep viewers glued to their screen for hours. But above all, the integration of AI in this app is the primary reason behind the success story of the app.
Today, almost every organization is dealing with customer services and embracing AI technology directly and indirectly to serve better services. Right from adding chatbots to websites and mobile apps to integrating into analytics and CRM platforms, AI technology has a great potential to improve your business performance if it is rightly leveraged.
So adding AI and ML to the mobile app has become one of the most common requests from businesses of all vertical domains these days.
Let’s hope you are convinced of learning how to integrate AI technology in Flutter mobile apps?
Methods of Integrating AI and ML in Flutter Mobile Applications
With the above discussion, you must have realised the benefits of incorporating Artificial Intelligence in their apps. But here we channelize our concern into simple methods of how to make your Flutter app AI enable.
While there are various mobile apps including AI, Flutter app developers top the chart and are keen to know the options available for running ML models in the application.
Here are the few ways to integrate AI and ML to Flutter apps:
Firebase MLKit
ML kit is a part of Firebase that allows mobile app developers to quickly import Google’s machine learning expertise from the firebase console. No matter whether you are a beginner or a skilled Flutter app developer, you can quickly implement the ML functionality to Android and iOS applications by adding the few lines of code. While there is no need of having in-depth knowledge of neural networks or model optimization to get started with ML functionality, if you are an experienced ML developer, then it is worth leveraging the APIs in the mobile app.
Some of the best ready-made state-of-art models available on Firebase are:
- Text Recognition and Face Detection
- Image Labeling
- Object Detection & Tracking
- Language Identification
- Smart Reply
- AutoML Model Interface
- Custom Model Interface
While using this method of integrating ML and AL to Flutter App, make sure your app is using Firebase or either you have a custom model that will be hosted on another server setup. Also, this method is suitable for models which expect regular updates but not so frequent.
2. Models as APIs
It is one of the other popular methods of incorporating machine learning in apps, mostly when you are working with servers and web interfaces and expecting your model to update very frequently.
While using this method, developers wrap the model in API services and host it using web-based servers. Major developers reply on these popular platforms including AWS Lambda, Google App Engine, Heroku or Virtual Machine as it supports running the model and serving as a web-based service.
3. On-Device Model
On-device models are effective methods, in case you want to perform high-speed inference directly on the devices of the users.
The primary way to use this model is to firstly create them as TensorFlow models. To export them as .tflite files, you can use the ML Kit plugin in your flutter app. Before shipping the file, you need to import the stored .tfilte file from the project repository and make it run for the interface.
To make it easier for you to understand, you can download the sample from the Flutter application using the Face Detection model readily available on Firebase and then use it as an on-device model.
This model is an ideal choice of integration when you want your app users to experience super-fast inference and not providing regular updates.
Conclusion
With the end of this blog, you must have learned how AI is revolutionizing digitization and making smartphones smarter in every second. Over the last few years, AI has carved out a remarkable impact in the mobile app development market. Therefore, for quite some time now Flutter mobile app development companies are incorporating AI into their solutions and successfully producing better applications that flawlessly work on cross-platforms.
Sure in these five minutes, you have learnt the available methods of integrating AI and ML on your Flutter app. But stay tuned to go through with methods in detail in the future.
