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Create IOT products and solutions – Part 1

It’s very interesting to see and understand how things are really working at the level of bytes and bits. In software, we rarely think about those details, as most of these things are abstracted so a software programmer can focus on just his piece while the hardware engineers and embedded programmers take care of making those intricate and complex circuit boards.

 

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Sometime back when we decided to do something in the space of IOT, we were complete newbies with absolutely no background, academic, or professional. But we learnt many things the hard way by trying, failing, and correcting. But perhaps as many people say, that may also be the best approach towards learning anything new.

Today with an experience of building an actual physical thing that listens, I feel more confident about the space, and our ability to replicate our success story for our clients as well. But what is that we build, and now a question of great debate, and subjectivity. I can perhaps think of some rules that an IOT product or initiative should bear in mind.

Before going forward, give it a thought

Does the device really help its customer? This is a very basic and moot question that every innovator and maker should ask themselves.

Does the product makes our life more safer, convenient, healthier, and happier? If the answer is yes for these questions, the product may find takers in the market.

A product must have a clear cut value proposition for its intended buyers. If the product is just a cool gadget, it will find utility only with a handful of users who will be very quick to move onto something more cooler as and when it’s available in market.

internet-of-things

Just having built something and pushing it off to the supply chain may not be of great help in building a sustainable business that will have a long term impact. One should think of constantly reinventing the product to make it better & more useful for its customers. Timely service, and a great customer support will go a long way in winning the confidence of the current active users, and the word of mouth publicity will help in winning more users till the product reaches a critical mass.

There are some challenges too

The challenge that we face today in IOT, especially industrial IOT is that existing chips that help the sensors transmit the data directly into cloud, consume a lot more power than what would be practical for widespread adoption in industries. But recent advancements in technology with the Qualcomm Cat M1 modules, and Verizon’s upgrading its infrastructure to allow ultra low band transmission at really affordable rates can be the right steps in the direction of making IOT really ubiquitous.

Security is another big challenge for mass adoption of IOT. Seeds of doubt about the device being sufficiently protected against hacking is one big reason why customers are still not able to fully give in to the idea of leaving their critical functions to a device. What if my smart locking system is hacked, and an intruder is able to hack his way inside my house?

An intrusion into house, or the smart lighting solution being hacked are still something not as much threatening as a possibility of a smart glucometer or a pacemaker being hacked. Risk of this nature can have life threatening consequences, and cannot be taken lightly.

These are valid questions which the IOT community will have to tackle head on. But I believe these questions or challenges are always there with any new technology. It takes time for ecosystem to mature to a level where issues of security are addressed, questions of viability, feasibility, and usability are addressed, and then mass adoption follows. The stage in which the current IOT development possibly is where developers and engineers worldwide are working in the direction of making IOT safer, and more useful for everyone. Soon it will be IOT for everyone.

Stay tuned for next article about some specific steps and questions to create an IOT Product.

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Smart Machines & Smarter Humans: AI in the Manufacturing Industry

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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