Unleashing the Potential of Smart Technologies in Mobile Apps
Image by irfanak November 10, 2021 Approximate Reading Time: 4 minutes
Propelling Mobile Apps into the Future:
As the era of smart devices—smartphones, smartwatches, and smart speakers—envelopes us, a new wave emerges: smart apps. These applications harness diverse technologies to furnish users with more personalized and captivating experiences. In a fiercely competitive mobile app landscape boasting millions of apps and a steady influx of additions daily, integrating smart features and technologies is instrumental in distinguishing your app and ensuring it garners the spotlight it deserves.
The Relevance of Smart Apps:
Each user is distinct, with unique preferences and needs. While developing individual apps for every user isn’t practical, infusing smart features into apps empowers them to adapt and personalize the experience based on user behavior and preferences.
Unlike conventional apps, smart apps possess the ability to learn from user actions and customize the interface accordingly. Furthermore, they can automate repetitive tasks and integrate conversational AI. As technology evolves, we may witness these apps delivering consistent, precise results, offering users a consistent and tailored journey.
In this article, we’ll explore seven smart technologies poised to elevate the mobile app experience.
- Chatbots: Recent chatbot statistics indicate that by 2021, approximately 85% of customer interactions will be handled without human agents. With the capability to address 80% of queries and cut operational expenses by 30%, it’s evident why businesses are embracing chatbots.
Not only do they alleviate the load on customer support, but they also automate these services. Moreover, chatbots enable continuous customer assistance, augmenting satisfaction by promptly addressing inquiries and contributing to lead conversion and sales.
- Machine Learning: For businesses, developers, and users alike, integrating machine learning into mobile apps is mutually beneficial. Machine learning algorithms streamline programming tasks by anticipating use cases, contingencies, and potentialities. They can discern trends, demands, and patterns.
Apps with machine learning capabilities effectively meet user requirements, translating into enhanced profitability. This technology empowers businesses to integrate new data, products, and information in real-time, perpetually updating the app’s content. The capacity to predict trends and identify patterns facilitates capitalizing on emerging shifts.
- Biometrics: Modern smartphones incorporate fingerprint and facial recognition technologies, and some even utilize iris scanning and other biometric features. Coupled with gesture and voice controls, these technologies diversify interaction modalities. By leveraging existing hardware, app developers can evaluate user behavior, and these technologies have multifaceted applications beyond authentication.
- Emotion Recognition: While some individuals can discern emotions through facial cues, technology also offers an alternative: emotion recognition. Employing advanced image processing and audio-based analysis, emotion recognition deciphers emotional states. Subtle speech signals and vocal tone are scrutinized to gauge mood, although this technology is still in its nascent stages.
- Speech Recognition: Speech recognition is a prominent smart technology embedded in mobile apps through voice assistants like Siri, Google Assistant, and Cortana. This feature affords users a seamless interface to interact with apps and execute tasks.
- Text Recognition: A facet of natural language processing, text recognition is invaluable in extracting pertinent information from voluminous datasets. While its applications span security and fraud detection, it also automates data entry, document indexing, and assists visually impaired individuals.
- Image Recognition: A branch of artificial intelligence, computer vision analyzes visual data, enabling object recognition, geolocation, code analysis, and applications in various fields. Social media platforms like Facebook and Twitter leverage image recognition to enhance user engagement and optimize mobile advertising.
Equipped with image recognition capabilities, apps discern patterns, compare objects, and anticipate object adjustments in three-dimensional space. This data can then be harnessed by advertisers to tailor campaigns to users’ preferences.
A Glimpse into the Image Processing Process:
- Data Collection and Organization
- Creation of Predictive Model for Image Recognition
- Image Recognition
Notably, image recognition algorithms can be resource-intensive, a factor to consider when integrating this technology into apps.
Which of these smart mobile app technologies have you employed in your apps? We’re intrigued to learn from your experiences—feel free to share in the comments below.