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Google’s Android N Preview- Developers Perspective

Google released its new operating system Android N preview on 09-03-2016. Google’s unexpected announcement of Android N Developer came that time when several mobile phone manufacturers are struggling to make the Android 6.0 Marshmallow update available to their premium devices.

The launch of Android N developer’s preview saw a good audience and it’s also going to be much, much easier for anybody to try it out. The plan of releasing it in May came little early, as Google wanted to release the preview earlier in order to get more feedback from developers in the process and get the final N release into the hands of device manufacturers this summer. Google’s current plan calls for five preview releases and a final release in Q3 2016.

Google has been working hard on matching Windows and iOS by building a native side-by-side app mode in Android. For Android N, the feature is apparently ready for prime time.

Before you plan of investing in Google’s new OS Android N, here are a few APIs and features we want to highlight which are available as a part of the “Android N Developer Preview”:

Multi-window
A new manifest attribute called android:resizableActivity is available for apps targeting N and beyond. If this attribute is set to true, your activity can be launched in split-screen modes on phones and tablets. You can also specify your activity’s minimum allowable dimensions, preventing users from making the activity window smaller than that size. Lifecycle changes for multi-window are similar to switching from landscape to portrait mode: your activity can handle the configuration change itself, or it can allow the system to stop the activity and recreate it with the new dimensions. In addition, activities can also go into picture-in-picture mode on devices like TVs, and is a great feature for apps that play video; be sure to set android:supportsPictureInPicture to true to take advantage of this.

Screenshot_20160311-121807Screenshot_20160311-121851

 

 

Direct reply notifications
The RemoteInput notification API, which was originally added for Android Wear, now works in N for phones and tablets. Using the RemoteInput API enables users to reply to incoming message notifications quickly and conveniently, without leaving the notification shade.

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Bundled notifications
With N, you can use the Notification.Builder.setGroup() method to group notifications from the same app together – for example individual messages from a messaging app. Grouped notifications can be expanded into individual notifications by using a two-finger gesture or tapping the new expansion button.

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Efficiency
You can launch Doze in Marshmallow to save battery when your device is stationary. In N, Doze additionally saves battery whenever the screen turns off. If you’ve already adapted your app for Doze, e.g. by using the GCM high priority message for urgent notifications, then you’re set; if not, here is how to get started. Also, we’re continuing to invest in Project Svelte, an effort to reduce the memory needs of Android so that it can run on a much broader range of devices, in N by making background work more efficient. If you use JobScheduler for background work, you’re already on the right track. If not, N is a good time to make that switch. And to help you out, we’re making JobScheduler even more capable, so now you can use JobScheduler to react to things like changes to content providers.

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Improved Java 8 language support
We’re excited to bring Java 8 language features to Android. With Android’s Jack compiler, you can now use many popular Java 8 language features, including lambdas and more, on Android versions as far back as Gingerbread. The new features help reduce boilerplate code. For example, lambdas can replace anonymous inner classes when providing event listeners. Some Java 8 language features –like default and static methods, streams, and functional interfaces — are also now available on N and above. With Jack, we’re looking forward to tracking the Java language more closely while maintaining backward compatibility.

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Start-Up Time
If you’ve ever updated software on your Android smartphone or tablet, you’ve almost certainly seen that infuriating ‘Optimizing Apps’ popup up card immediately after installing and booting up your device. Depending on how many apps you have, it can take anytime between a couple of minutes and a bazillion years (slight exaggeration) to get past this stage. One of the less obvious new features is that Android’s ‘Optimizing Apps’ screen during startup barely takes any time at all to work through its process with N (Nutella?). Thankfully, with Android N, we won’t have to wait for very long at all.

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Night Mode
Google has bought Night Mode option back, which user can turn to anytime. The night mode produces less strain to user and is addition option in Android N.

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Get Started
The N Developer Preview includes an updated SDK with system images for testing on the official Android emulator and on Nexus 6, Nexus 5X, Nexus 6P, Nexus Player, Nexus 9, and Pixel C devices.

This initial preview release is for developers only and not intended for daily use or consumer use. Google plans to update the N Developer Preview system images often during the Developer Preview program. As they are getting closer to a final product, Google will be inviting consumers to try it out as well.

There is more to come as Google continue developing the release. Google is also making it easier for you to try out N on your development devices with the new Android Beta Program. Started yesterday, you can update your Android devices to the developer preview of N and receive ongoing updates via OTA by visiting g.co/androidbeta.

We at Mantra Labs keep continuous watch on latest Technology updates by Google, Apple, Microsoft and others to drive next generation of mobile apps.

 

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Manufacturing 4.0: How Augmented Reality is Reshaping the Factory Floor

Augmented reality began in a lab at Harvard back in the 1960s, and over the years, it has been used for defense, sports, entertainment, and gaming applications, among others. Most of us got our first taste of augmented reality while chasing Pikachu through city streets in Pokémon Go. But in factories, AR isn’t about catching ’em all—it’s about keeping production lines running smoothly, minimizing errors, and turning workers into efficiency powerhouses with a simple glance through a headset. 

In manufacturing, AR has evolved beyond simple overlays to become a transformative force, seamlessly integrating with Artificial Intelligence (AI), IoT, and digital twin technologies. We all recognize the value AR brings to manufacturing, but what happens when AI enhances AR? How is AR transforming the industry, and how does it work? That’s exactly what we’ll explore in this blog.

The Next Evolution of AR in Manufacturing

Manufacturing is no longer just about automation, it’s about augmentation. AI is helping AR enable a new level of precision, real-time decision-making, and predictive capabilities that were once considered futuristic. Let’s take a closer look at how AR is elevating factory operations today.

1. AI-powered AR for Adaptive Workflows

Picture this: you’re on a bustling factory floor, working on an intricate assembly task. Traditional AR systems would simply float static instructions in front of you like flipping through a digital manual that doesn’t know if you’re stuck or making a mistake. Helpful? Sure. Dynamic? Not so much.

Now just imagine you are working with AI-powered AR which doesn’t just display instructions, it learns, adapts, and reacts. These intelligent systems analyze your workflow in real-time, adjusting guidance based on how you’re performing, the machine conditions around you, and even environmental factors. Hesitate on a step? The system modifies the instructions instantly. Does a component deviate from standard specifications? AR overlays flag the issue before it snowballs into a costly error.

Companies like PTC and Vuforia are pioneering AI-driven AR solutions, analyzing operator performance to deliver real-time coaching. How Volkswagen has integrated AI-driven AR into its assembly lines, automatically detecting errors and suggesting corrections to workers on the spot, significantly reducing rework time.

2. AR and IoT: The Connected Factory

What if the mere thought of ‘I wish these machines could just communicate’ could be true? AR, when combined with IoT, transforms equipment into interactive entities, providing real-time sensor data directly overlaid onto machinery. Instead of waiting for a malfunction, workers can spot anomalies, take proactive measures, and keep production lines running smoothly.

Siemens has already embraced this technology, equipping workers with AR dashboards that display real-time diagnostics and alerts, significantly reducing unexpected machine failures. According to Deloitte, Factories integrating AR-powered IoT solutions drop machine failure rates, leading to reduced downtime and operational costs.

3. AR-Enabled Remote Collaboration and Assistance

In the past, troubleshooting a complex issue on the factory floor meant waiting for an expert to arrive, causing delays in production. But with AI-powered AR, remote collaboration has become seamless. Experts can now “see” exactly what you see, overlaying real-time annotations, guiding your hands, and helping resolve issues instantly! no waiting, no guesswork.

Airbus has developed AR-based remote assistance solutions where engineers worldwide provide instant support to factory workers, reducing troubleshooting time by 60%. Similarly, Caterpillar’s AR-powered remote support system has led to a 50% reduction in equipment downtime, directly improving operational efficiency.

Source: Belcan.com

4. AR-Driven Digital Twins for Real-Time Decision Making

The virtual replica of your factory floor is not just imagination, it’s a reality with digital twin technology. Imagine standing in your factory and seeing a real-time, interactive model of the entire operation floating in front of you. These AI-powered digital twins mirror every aspect of your machinery and workflow, allowing workers to test processes, predict failures, and optimize operations before making real-world changes.

Instead of relying on outdated reports or delayed diagnostics, workers can access instant, data-driven insights overlaid onto their environment. This helps them tweak operations on the go without shutting down production. Whether optimizing machine performance, identifying bottlenecks, or improving workflow efficiency, digital twins give workers the power to make smarter, faster decisions right on the spot.

GE integrates AR with digital twins, allowing engineers to simulate and optimize workflows before execution, minimizing errors and improving efficiency. Companies leveraging AR-driven digital twins report a 40% boost in operational efficiency, making real-time decision-making more data-driven than ever.

5. AR in Workforce Development: AI-Coached Training and Skill Retention

Forget static manuals and lengthy onboarding sessions, AR is revolutionizing training by offering augmented reality training immersive, AI-assisted learning experiences tailored to individual skill levels. Workers learn by doing, receiving real-time, interactive guidance that accelerates skill acquisition and improves long-term retention.

Lockheed Martin has implemented AR-driven training programs, which have reduced the time required for workers to master complex assembly tasks. AI-integrated AR training systems can even predict potential human errors before they occur, offering instant corrective feedback and creating a more proactive, skilled workforce.

Source: Mantra Research

The Impact of AR on Manufacturing

The adoption of AR in smart manufacturing has not just improved the quality of output but has transformed the entire industry. By enabling real-time decision-making, predictive maintenance, and adaptive learning, AR is creating more agile, efficient, and error-free production environments. Workers are experiencing faster task completion rates, fewer errors, and enhanced safety measures, while companies are seeing increased ROI, reduced downtime, and higher production yields.

According to a PwC report, companies implementing AR in industrial settings have achieved a 32% improvement in productivity and a 25% reduction in errors. These advancements are not just making production lines smarter but also reshaping the role of human workers, empowering them with real-time insights and hands-free operational guidance.

Conclusion:

With AI-powered Augmented Reality on factory floors, the manufacturing industry has evolved in every way possible. AI is not just assisting AR—it’s amplifying its impact. Machine efficiency has soared, processes have become more seamless, and workers are now equipped with real-time insights that make their jobs more engaging and rewarding. Error rates have dropped drastically, and safety concerns are becoming a thing of the past, thanks to AI-driven predictive alerts and color-coded warnings that flag potential issues before they escalate.

But the real game-changer? Precision and quality. AI’s ability to analyze and adapt in real time has led to higher product quality, reduced downtime, and smarter workflows. The result – factories that are not just automated, but intelligently optimized.

At Mantra Labs, we build AI-driven solutions that help businesses scale sustainably, reduce inefficiencies, and streamline operations. From minimizing downtime to optimizing supply chains, we make manufacturing smarter and more resilient.

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