Mobile apps are setting new goals for every industry. Technological and scientific advancements have paved the way for artificial intelligence apps. Today, Android application development market is growing significantly with AI.
According to a recent survey, the machine vision market is expected to grow at a CAGR of 7.7% to $18.24 billion by 2025. In the past few years, our AR & VR app development company have seen many new and innovative technologies getting launched into the mainstream industries. AI is one of these technologies that have been influencing almost every industry’s growth rate. Moving on, AI explains the use of human-level intelligence with the help of machine learning concepts.
Artificial intelligence has been affecting our daily lives in several ways, driving up the global value of the technology. Some of the common applications include:
- Image recognition
- Object recognition, Classification, and Detection
- Automated Geophysical Feature Detection
These are only few of the many revenue-generating proportions of AI that has been influencing the enterprise mobile app development market. In the blog, our android app development company in India shall discuss the AI integration into the android app and its impact over the past many years.
The impact of AI programs on Android
Artificial Intelligence (AI) allows machines to learn and communicate in a way human does. Humans had a sigh of relief with AI machines and applications. It helps them complete tasks and achieve desired outcomes.
Another reason of increased popularity of AI-based apps and machines is that they eliminate emotional challenges faced by humans, which further lead to errors. For instance, AI apps are not biased towards a particular situation, so their decisions with AI technology remains flawless.
Every primary industry sector has embraced AI technology. From the tourism industry to healthcare and finance, this cutting-edge technology has become an absolute reality we are living in. Now, let us focus on the AI applications that are seamlessly integrated into the android application.
AI-based applications integrated into Android application
Here is a list of top notable AI innovations incorporated into Android app development:
In the world of Android app development, automated reasoning was the first and most potential AI feature. However, analysing the user’s behaviour is still a challenge task to accomplish. It entails problem-solving feature on the substructure of various automated reasoning algorithms.
When you hire android app developers use logical reasoning to solve an issue like a puzzle or theorem. AI-powered systems and apps excel at stock trading and chess, thanks to AI-rich features. One of the greatest examples of AI and machine learning is Uber that uses automated reasoning. Uber’s android app uses AI to search for the best routes by calculating the shortest path based on real-time traffic conditions.
Researches on the way to find the best way to integrate AI in Android, introduced picture labeling process. Developers can now use an Image Labeller app to interactively label ground data in a collection of images or rectangular ROIs (Region of Interest). It works best for object detection, pixel semantic segmentation, and more such scene image classification.
It is a computer technology that help detect human faces in digital images. In no time, it has become a sensational feature used in a wide range of applications. Also, it can help track people or objects by detecting their faces in real-time.
It is widely used in Android and iOS smartphone cameras to recognize multiple objects in the frame. One of the most popular example of this feature is Facebook – the most popular social networking site. It uses the face detection algorithm to detect the user’s face in their photos.
It refers to the process of detecting texts in images and video formats while recognizing the text extracted from the media files. AI breaks the texts into blocks and segments to reveal the proper form of the text. Android application developers use the text recognition feature as a standalone application or add-on feature in conjunction with multiple tasks.
Boost the productivity of the app
AI can help android apps become more productive. The most common apps that use AI in their operations include Microsoft Office 365 and Google’s G Suite. With the help of AI, these apps can quickly scan through a large amount of data to find a crucial information. Also, it collects the data required from the on-going communication like documents and files.
Personalized content curation
Most apps fail to gain deserving attention from their target audience since they lack the connection with their users. One reason for this lack of connectivity can be the content you create.
Using AI, the developers can track the user’s preferences and incorporate them into the learning algorithm via AI integrates in the android apps. This brilliant AI functionality get used by any app based on a sell-up business to pitch content to the users strategically and gain their attention.
So far, we have discussed the various AI-rich applications launched in the market and how they are changing the world for better prospects. Some of the key takeaways include:
- AI can quickly analyse large amount of data in Android apps
- Email scanning and automated smart reverts are the most practical applications of Android AI technology
- AI is improving our lives indirectly via its integration into various apps like fitness trackers
- The customer service industry is now heavily utilizing AI apps to enhance their customer engagement.
Looking for more AI-based Android app development services? We are here to help. Get in touch with our experts to know more.
How is AI technology used in mobile apps?
AI has accelerated the evolution of mobile apps by transforming them into intelligent pieces of software that are capable of predicting user behaviour and making decisions.
What are some of the apps based on AI?
- Google Assistant
What are the most important aspects of an AI-based mobile app?
- Speech recognition technology
- Machine learning
- Emotion recognition
- Image recognition
- Text recognition
- Natural Language Technology