Many new updates happened for Android developers lately after Google I/O. Initially there was no restriction on some features but now they have updated them with some restrictions.

We have covered new features and the old features as well with new restrictions.

Here are the old features with new restrictions:

• Background Execution Limits

Whenever an app runs in the background, it consumes some of the device’s limited resources, like RAM. This can result in an impaired user experience, especially if the user is using a resource-intensive app, such as playing a game or watching a video.
To lower the chance of these problems, Android O places limitations on what apps can do while users aren’t directly interacting with them. Apps are restricted in two ways:

Background Service Limitations: When an app’s service is running in the background might consume device resources which may lead to bad user experience, to avoid these type of issues Android system applies a number of limitations on background services, this does not apply to foreground services, which are more noticeable to the user.
Broadcast Limitations: Apps targeted Android O can not use their manifest to register for implicit broadcasts. They can still register for these broadcasts at runtime, and they can use the manifest to register for explicit broadcasts targeted specifically at their app.

Note: The restrictions are applied by default applied to apps which are targeting Android O and in terms of other applications users can enable these restrictions from the Settings screen even if the app has not targeted Android O.

• Android Background Location Limits

Considering battery usage and user experience , background apps which are using Android locations APIs to fetch the user’s location will receive location updates less frequently when the app is being used in a device running Android O, developers who are using Fused Location Provider (FLP), Geofencing, GNSS Measurements, Location Manager, Wi-Fi Manager will get affected by this change.

• Notifications

Notification Badges

Notification Badges are the new way of notifying users regarding the new notifications arrived for a particular app, this will display badges on app icons in supported launchers which show notifications associated with one or more notification channels in an app, which the user has not yet dismissed or acted on.
Notification Channels

Using Notification channels developers can group their application’s notifications by category so that the user can apply few characteristics basing on the notification category. When you target Android O, you must implement one or more notification channels to display notifications to your users. If you don’t target Android O, your apps behave the same as they do on Android 7.0 when running on Android O devices.

Google says that the following characteristics can be applied to notification channels and that when the user assigns one of these, it will be applied channel- wide and they are as follows

Importance
Sound
Lights
Vibration
Show on lock screen
Override do not disturb

Here are some new features:

• New in UI and Styling

There are bunch of new features of UI and Styling are introduced in Android O and are as follows

1. Fonts

Android introduced fonts in XML through which we can use custom fonts as resources, You can add your custom font file in res/font/ folder to bundle fonts as resources and can access as a normal resource file and Android Support Library 26 introduce support for APIs to request fonts from a provider application instead of bundling files into your project which helps in reducing your application size
To use these font features on devices running Android API version 14 and higher, a developer needs to use the Support Library 26.

2. Auto Sizing Textviews

By using Support Library 26 Beta developers can now instruct to their app’s Textview to automatically increase or decrease the size to fit perfectly within the boundaries of the Textview.

3. Adaptive Icons

Adaptive icons can display app’s launcher icons in a variety of shapes across different devices for instance in Google Nexus the launcher icon might be in circular and in some Samsung device it might be squircle. Google says that with Android O, each device can provide a mask for the icon, which the OS can use to render all icons with the same shape. This will likely be embraced by OEMs(Original Equipment Manufacturer) who would like to have some unique looking home screens.

4. Autofill Framework

This framework will help the user by pre-filling the user information and user can save time as Filling out forms is a time-consuming and error-prone task. Users can easily get frustrated with apps that require these type of tasks. The Autofill Framework improves the user experience by providing the following benefits:

Less time spent in filling fields Autofill saves users from re-typing information.
Minimize user input errors Typing is prone to errors, especially on mobile devices. Removing the necessity of typing information also removes the errors that come with it.

• Picture in Picture Mode

In Android 7.0, Android TV users can now watch a video in a pinned window in a corner of the screen when navigating within or between apps whereas it was not available to other devices whereas from Android O Picture in Picture is available to all the devices, not just the Android TV.

• Kotlin For Android

Java is the mostly used programming language for the development of Android, When you run a Java application, the app is compiled into a set of instructions called Bytecode and runs in a virtual machine. Many alternative Languages has been introduced to also run on the JVM through which the resulting app looks the same for the JVM
JetBrains, known for IntelliJ IDEA (Android Studio is based on IntelliJ), has introduced the Kotlin language.Kotlin is a statically-typed programming language that runs on the JVM. It can also be compiled to JavaScript source code.

Why Kotlin For Android?

Interoperability with Java
Intuitive and easy to read
Good Android Studio Support
Safe to avoid entire classes of errors such as null pointer exceptions.
Less to write compared to Java
Safe to avoid entire classes of errors such as null pointer exceptions.
Versatile for building server-side applications, Android apps or frontend code running in the browser.

Stay tuned for more new updates on Android.

Check out these articles to catch the latest trends in mobile apps:

Smart Machines & Smarter Humans: AI in the Manufacturing Industry

By : Sampada S M

Published on Feb 19, 2025

AI Artificial Intelligence Manufacturing

We have all witnessed Industrial Revolutions reshape manufacturing, not just once, but multiple times throughout history. Yet perhaps “revolution” isn’t quite the right word. These were transitions, careful orchestrations of human adaptation, and technological advancement. From hand production to machine tools, from steam power to assembly lines, each transition proved something remarkable: as machines evolved, human capabilities expanded rather than diminished.

Take the First Industrial Revolution, where the shift from manual production to machinery didn’t replace craftsmen, it transformed them into skilled machine operators. The steam engine didn’t eliminate jobs; it created entirely new categories of work. When chemical manufacturing processes emerged, they didn’t displace workers; they birthed manufacturing job roles. With each advancement, the workforce didn’t shrink—it evolved, adapted, and ultimately thrived.

Today, we’re witnessing another manufacturing transformation on factory floors worldwide. But unlike the mechanical transformations of the past, this one is digital, driven by artificial intelligence(AI) working alongside human expertise. Just as our predecessors didn’t simply survive the mechanical revolution but mastered it, today’s workforce isn’t being replaced by AI in manufacturing, they’re becoming AI conductors, orchestrating a symphony of smart machines, industrial IoT (IIoT), and intelligent automation that amplify human productivity in ways the steam engine’s inventors could never have imagined.

Let’s explore how this new breed of human-AI collaboration is reshaping manufacturing, making work not just smarter, but fundamentally more human.

Tools and Techniques Enhancing Workforce Productivity

1. Augmented Reality: Bringing Instructions to Life

AI-powered augmented reality (AR) is revolutionizing assembly lines, equipment, and maintenance on factory floors. Imagine a technician troubleshooting complex machinery while wearing AR glasses that overlay real-time instructions. Microsoft HoloLens merges physical environments with AI-driven digital overlays, providing immersive step-by-step guidance. Meanwhile, PTC Vuforia’s AR solutions offer comprehensive real-time guidance and expert support by visualizing machine components and manufacturing processes. Ford’s AI-driven AR applications of HoloLens have cut design errors and improved assembly efficiency, making smart manufacturing more precise and faster.

2. Vision-Based Quality Control: Flawless Production Lines

Identifying minute defects on fast-moving production lines is nearly impossible for the human eye, but AI-driven computer vision systems are revolutionizing quality control in manufacturing. Landing AI customizes AI defect detection models to identify irregularities unique to a factory’s production environment, while Cognex’s high-speed image recognition solutions achieve up to 99.9% defect detection accuracy. With these AI-powered quality control tools, manufacturers have reduced inspection time by 70%, improving the overall product quality without halting production lines.

3. Digital Twins: Simulating the Factory in Real Time

Digital twins—virtual replicas of physical assets are transforming real-time monitoring and operational efficiency. Siemens MindSphere provides a cloud-based AI platform that connects factory equipment for real-time data analytics and actionable insights. GE Digital’s Predix enables predictive maintenance by simulating different scenarios to identify potential failures before they happen. By leveraging AI-driven digital twins, industries have reported a 20% reduction in downtime, with the global digital twin market projected to grow at a CAGR of 61.3% by 2028

4. Human-Machine Interfaces: Intuitive Control Panels

Traditional control panels are being replaced by intuitive AI-powered human-machine interfaces (HMIs) which simplify machine operations and predictive maintenance. Rockwell Automation’s FactoryTalk uses AI analytics to provide real-time performance analytics, allowing operators to anticipate machine malfunctions and optimize operations. Schneider Electric’s EcoStruxure incorporates predictive analytics to simplify maintenance schedules and improve decision-making.

5. Generative AI: Crafting Smarter Factory Layouts

Generative AI is transforming factory layout planning by turning it into a data-driven process. Autodesk Fusion 360 Generative Design evaluates thousands of layout configurations to determine the best possible arrangement based on production constraints. This allows manufacturers to visualize and select the most efficient setup, which has led to a 40% improvement in space utilization and a 25% reduction in material waste. By simulating layouts, manufacturers can boost productivity, efficiency and worker safety.

6. Wearable AI Devices: Hands-Free Assistance

Wearable AI devices are becoming essential tools for enhancing worker safety and efficiency on the factory floor. DAQRI smart helmets provide workers with real-time information and alerts, while RealWear HMT-1 offers voice-controlled access to data and maintenance instructions. These AI-integrated wearable devices are transforming the way workers interact with machinery, boosting productivity by 20% and reducing machine downtime by 25%.

7. Conversational AI: Simplifying Operations with Voice Commands

Conversational AI is simplifying factory operations with natural language processing (NLP), allowing workers to request updates, check machine status, and adjust schedules using voice commands. IBM Watson Assistant and AWS AI services make these interactions seamless by providing real-time insights. Factories have seen a reduction in response time for operational queries thanks to these tools, with IBM Watson helping streamline machine monitoring and decision-making processes.

Conclusion: The Future of Manufacturing Is Here

Every industrial revolution has sparked the same fear, machines will take over. But history tells a different story. With every technological leap, humans haven’t been replaced; they’ve adapted, evolved, and found new ways to work smarter. AI is no different. It’s not here to take over; it’s here to assist, making factories faster, safer, and more productive than ever.

From AR-powered guidance to AI-driven quality control, the factory floor is no longer just about machinery, it’s about collaboration between human expertise and intelligent systems. And at Mantra Labs, we’re diving deep into this transformation, helping businesses unlock the true potential of AI in manufacturing.

Want to see how AI-powered Augmented Reality is revolutionizing the manufacturing industry? Stay tuned for our next blog, where we’ll explore how AI in AR is reshaping assembly, troubleshooting, and worker training—one digital overlay at a time.

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