#embedded hardware design

[rapidise]

The Evolution of Embedded Hardware: From Simple Circuits to Smart Devices

Embedded systems are all around us in today's hyperconnected world, from the sophisticated electronics controlling your car's engine to the smart thermostat that regulates the temperature in your house. One of the most amazing changes in technology is the progression from simple circuits to the advanced smart devices of today. This evolution, which has been fuelled by necessity and creativity, has been an intriguing one that has taken place over many decades. Understanding this history is essential for developers and businesses traversing this terrain, particularly when thinking about an embedded hardware design service that could help them realise their next big idea.

The Pioneer Days: Early Embedded Systems

The 1960s and 1970s marked the dawn of embedded computing, though it looked nothing like what we recognize today:

The Apollo Guidance Computer, which helped navigate astronauts to the moon, represented one of the first mission-critical embedded systems

Early embedded systems relied on discrete components rather than integrated circuits

These systems were enormous by today’s standards—filling entire cabinets

Programming was done through hard-wired logic or assembly language

Each system was custom-designed for a specific purpose with little flexibility

These primitive beginnings laid groundwork for what would become a technological revolution, yet the limitations were substantial. Memory was measured in kilobytes, processing power was minimal, and development required specialized expertise that few possessed.

The Microprocessor Revolution

Everything changed in the early 1970s with the introduction of the microprocessor:

Intel’s 4004, introduced in 1971, became the first commercially available microprocessor

For the first time, computing power could fit on a single chip

Development costs dropped dramatically, making embedded systems accessible to more industries

Early applications included calculators, cash registers, and industrial controllers

The 8-bit microcontroller era began, with chips like the Intel 8051 becoming industry standards

This miniaturization represented the first major leap toward modern embedded systems. Suddenly, intelligence could be added to previously “dumb” devices, creating new possibilities across industries from manufacturing to consumer electronics.

From Industrial to Consumer Applications

The 1980s and 1990s witnessed embedded systems transitioning from purely industrial uses to consumer products:

Video game consoles like the Nintendo Entertainment System introduced millions to embedded technology

Household appliances began incorporating microcontrollers for improved functionality

Automotive applications expanded rapidly, with engine control units becoming standard

Personal digital assistants (PDAs) showcased the potential for portable computing

Cell phones emerged as perhaps the most transformative embedded systems of the era

At this time, there started to appear specialized embedded hardware design service providers which assists businesses with intricate hardware designs. These services helped translate creative concepts into functioning products, allowing companies without internal capabilities to join the growing competition in the electronics industry.

The Networking Revolution and Embedded Connectivity

By the late 1990s and early 2000s, embedded systems gained a critical new capability—connectivity:

First-generation embedded networks often used proprietary protocols

Industry standards like CAN bus revolutionized automotive electronics

TCP/IP implementation in embedded devices paved the way for Internet connectivity

Wireless technologies like Bluetooth and later Wi-Fi liberated devices from physical connections

Remote monitoring and management became possible, changing service models forever

This networking capability transformed embedded systems from standalone devices to interconnected nodes, creating new possibilities for data collection and device management. Industries from healthcare to manufacturing began reimagining their processes around these newly connected devices.

The Rise of the Internet of Things (IoT)

The 2010s saw embedded systems become truly ubiquitous through the Internet of Things:

Consumer IoT products like smart thermostats, lighting, and speakers entered millions of homes

Industrial IoT revolutionized manufacturing through predictive maintenance and asset tracking

Agriculture embraced precision farming techniques using embedded sensor networks

Healthcare innovations included remote patient monitoring and smart medical devices

Urban infrastructure began incorporating embedded systems for “smart city” initiatives

With this explosion in applications came increasing complexity. An embedded hardware design service became essential for many companies looking to enter the IoT market, providing expertise in not just hardware but the integration of sensors, connectivity, and power management that modern IoT devices require.

Read Also: The Role of Embedded Hardware in IoT Devices

The Miniaturization Miracle

Throughout this evolution, one trend has remained constant—the drive toward smaller, more efficient devices:

Component sizes shrank from through-hole to surface-mount to microscopic

Power consumption decreased dramatically, enabling battery-operated portable devices

Wearable technology emerged as components became small enough to integrate into clothing and accessories

Medical implants shrank to minimize invasiveness while increasing capability

Sensors became small and inexpensive enough to deploy in massive numbers

This miniaturization has opened new frontiers in what’s possible with embedded systems. Today’s embedded hardware design services often specialize in extreme miniaturization, developing sophisticated systems that fit into spaces previously thought impossible.

The Processing Power Explosion

Modern embedded systems bear little resemblance to their ancestors in processing capability:

32-bit and 64-bit processors have replaced 8-bit chips in many applications

Multi-core processors enable complex real-time processing

Specialized hardware accelerators handle tasks like AI inference and video processing

For specific applications, field-programmable gate arrays (FPGAs) offer hardware that can be reconfigured.

 System-on-Chip (SoC) designs combine peripherals, memory, and CPUs into one unit.

With this processing capability, embedded systems can now perform tasks like computer vision and natural language processing that were previously only possible with general-purpose computers, all while retaining the dependability and deterministic behaviour that embedded systems need.

The Future: AI at the Edge and Beyond

Looking ahead, embedded systems continue evolving at a breathtaking pace:

Edge AI is pushing intelligence to embedded devices rather than relying on cloud processing

New materials and manufacturing techniques are enabling flexible and biodegradable electronics

Energy harvesting is reducing or eliminating battery dependencies

Quantum computing principles may eventually transform embedded processing

Neuromorphic computing aims to make embedded systems think more like biological brains

These frontiers represent both challenge and opportunity. Companies seeking to navigate this complexity increasingly turn to specialized embedded hardware design services that can transform cutting-edge concepts into viable products.

The evolution of embedded hardware marks one of the most remarkable journeys of technology, progressing from circuits to devices that think for us and are a part of our lives. This journey continues to accelerate as we enter the following decades which promise even more astonishing innovations. For companies that want to take part in the ongoing revolution, collaborating with specialized embedded hardware design services is crucial for changing futuristic concepts into reality.

[takeoffproject]

Embedded Systems: Driving Innovation in Technology

Embedded systems are specialized computing systems designed to perform dedicated functions within larger devices or applications. These systems integrate hardware and software components to execute tasks with precision, reliability, and efficiency. They are embedded in devices ranging from household appliances like washing machines and microwaves to complex industrial machines, medical equipment, and automotive systems.

An embedded system's core lies a microcontroller or microprocessor, which controls and processes data. Sensors, actuators, and communication interfaces are often part of the system, enabling it to interact with the physical environment. For instance, in a smart thermostat, an embedded system monitors temperature, processes user inputs, and adjusts heating or cooling accordingly.

Embedded systems are valued for their compact size, low power consumption, and cost-effectiveness. They are tailored for real-time operations, ensuring quick and accurate responses to specific tasks. Industries such as automotive, healthcare, telecommunications, and consumer electronics heavily rely on these systems to innovate and improve product functionality.

As technology advances, embedded systems are becoming more sophisticated, incorporating artificial intelligence (AI), Internet of Things (IoT) connectivity, and advanced sensors. These developments are paving the way for smarter devices and systems, transforming how we live and work.

In a world increasingly driven by automation and smart technology, embedded systems play a crucial role in shaping the future of innovation.

[boschsds]

Expert Embedded Hardware Design Services by Bosch

Bosch offers specialized embedded hardware design services to create robust and efficient systems for various applications. Our team utilizes cutting-edge technologies to deliver solutions that meet your specific requirements and enhance product performance. With a focus on best practices and extensive industry experience, we ensure that our designs are not only innovative but also cost-effective and scalable.

[industrydesignservices]

Hardware Design Services | Electronic Design, Prototyping, and R&D Services

Teksun offers Hardware Design Services including designs based on a microprocessor, microcontroller, DSP, and all programmable modules. To know more about browse: https://teksun.com/ Contact us ID: marketing@teksun.com

[watchmorecinema]

Normally I just post about movies but I'm a software engineer by trade so I've got opinions on programming too.

Apparently it's a month of code or something because my dash is filled with people trying to learn Python. And that's great, because Python is a good language with a lot of support and job opportunities. I've just got some scattered thoughts that I thought I'd write down.

Python abstracts a number of useful concepts. It makes it easier to use, but it also means that if you don't understand the concepts then things might go wrong in ways you didn't expect. Memory management and pointer logic is so damn annoying, but you need to understand them. I learned these concepts by learning C++, hopefully there's an easier way these days.

Data structures and algorithms are the bread and butter of any real work (and they're pretty much all that come up in interviews) and they're language agnostic. If you don't know how to traverse a linked list, how to use recursion, what a hash map is for, etc. then you don't really know how to program. You'll pretty much never need to implement any of them from scratch, but you should know when to use them; think of them like building blocks in a Lego set.

Learning a new language is a hell of a lot easier after your first one. Going from Python to Java is mostly just syntax differences. Even "harder" languages like C++ mostly just mean more boilerplate while doing the same things. Learning a new spoken language in is hard, but learning a new programming language is generally closer to learning some new slang or a new accent. Lists in Python are called Vectors in C++, just like how french fries are called chips in London. If you know all the underlying concepts that are common to most programming languages then it's not a huge jump to a new one, at least if you're only doing all the most common stuff. (You will get tripped up by some of the minor differences though. Popping an item off of a stack in Python returns the element, but in Java it returns nothing. You have to read it with Top first. Definitely had a program fail due to that issue).

The above is not true for new paradigms. Python, C++ and Java are all iterative languages. You move to something functional like Haskell and you need a completely different way of thinking. Javascript (not in any way related to Java) has callbacks and I still don't quite have a good handle on them. Hardware languages like VHDL are all synchronous; every line of code in a program runs at the same time! That's a new way of thinking.

Python is stereotyped as a scripting language good only for glue programming or prototypes. It's excellent at those, but I've worked at a number of (successful) startups that all were Python on the backend. Python is robust enough and fast enough to be used for basically anything at this point, except maybe for embedded programming. If you do need the fastest speed possible then you can still drop in some raw C++ for the places you need it (one place I worked at had one very important piece of code in C++ because even milliseconds mattered there, but everything else was Python). The speed differences between Python and C++ are so much smaller these days that you only need them at the scale of the really big companies. It makes sense for Google to use C++ (and they use their own version of it to boot), but any company with less than 100 engineers is probably better off with Python in almost all cases. Honestly thought the best programming language is the one you like, and the one that you're good at.

Design patterns mostly don't matter. They really were only created to make up for language failures of C++; in the original design patterns book 17 of the 23 patterns were just core features of other contemporary languages like LISP. C++ was just really popular while also being kinda bad, so they were necessary. I don't think I've ever once thought about consciously using a design pattern since even before I graduated. Object oriented design is mostly in the same place. You'll use classes because it's a useful way to structure things but multiple inheritance and polymorphism and all the other terms you've learned really don't come into play too often and when they do you use the simplest possible form of them. Code should be simple and easy to understand so make it as simple as possible. As far as inheritance the most I'm willing to do is to have a class with abstract functions (i.e. classes where some functions are empty but are expected to be filled out by the child class) but even then there are usually good alternatives to this.

Related to the above: simple is best. Simple is elegant. If you solve a problem with 4000 lines of code using a bunch of esoteric data structures and language quirks, but someone else did it in 10 then I'll pick the 10. On the other hand a one liner function that requires a lot of unpacking, like a Python function with a bunch of nested lambdas, might be easier to read if you split it up a bit more. Time to read and understand the code is the most important metric, more important than runtime or memory use. You can optimize for the other two later if you have to, but simple has to prevail for the first pass otherwise it's going to be hard for other people to understand. In fact, it'll be hard for you to understand too when you come back to it 3 months later without any context.

Note that I've cut a few things for simplicity. For example: VHDL doesn't quite require every line to run at the same time, but it's still a major paradigm of the language that isn't present in most other languages.

Ok that was a lot to read. I guess I have more to say about programming than I thought. But the core ideas are: Python is pretty good, other languages don't need to be scary, learn your data structures and algorithms and above all keep your code simple and clean.

[gqattech]

https://gqattech.com/compatibility-testing/

https://gqattech.com/firmware-testing/

[surfytech]

Edge computing is revolutionizing embedded systems by enabling real-time data processing without relying on the cloud. Instead of sending every piece of information to remote servers, smart devices now process data locally, leading to:

- Faster response times

- Enhanced security & privacy

- Lower bandwidth & cloud costs

- More reliable performance in remote areas

Where is Edge Computing Used?

- Smart Homes & IoT Devices

- Healthcare Wearables & Patient Monitoring

- Autonomous Vehicles & Robotics

- Industrial Automation & Predictive Maintenance

As AI, 5G, and IoT evolve, Edge Computing in Embedded Systems is shaping the future of technology. Are you ready to embrace it?

#EdgeComputing #EmbeddedSystems #SmartTech #IoT #AI #Innovation #TechTrends #FutureTech #DigitalTransformation

[avenchsystem]

Turn key model

Unconventional Approaches in Embedded Hardware Design: What’s Really Changing?

The field of embedded hardware design has long been seen as highly specialized, with a focus on optimizing performance, reducing power consumption, and ensuring reliability. Traditionally, engineers followed well-established patterns, adhering to industry standards for board layout, component selection, and interfacing with software. However, in recent years, unconventional approaches are emerging, driven by new technology requirements and the need for more efficient, scalable, and adaptive systems. These shifts are not only reshaping the way we think about embedded systems but also pushing embedded hardware design companies to rethink their development strategies.

Rethinking Form Factors and Materials

One of the key areas where embedded hardware is evolving is in its physical form. Conventional designs have often been constrained by the standard dimensions of printed circuit boards (PCBs) and the limitations of traditional materials. However, advances in flexible and stretchable electronics are enabling entirely new possibilities for embedded hardware design projects.

These developments involve materials such as flexible substrates, which allow circuits to bend, twist, or fold without breaking. This can be crucial for applications in wearables, medical devices, and even certain aerospace technologies, where space and adaptability are critical. With these new form factors, embedded hardware becomes more versatile, accommodating designs that fit seamlessly into the human body, vehicles, or cramped industrial environments.

For embedded hardware design services, this shift means thinking beyond the rigidity of conventional components and adapting to a world where hardware needs to conform to increasingly demanding applications.

Open Hardware Platforms: A New Path Forward

Another significant trend shaping the embedded hardware design & development process is the adoption of open-source hardware platforms. While software development has seen a surge in open-source projects, hardware has been slower to embrace this trend. However, the growing interest in platforms like Arduino, Raspberry Pi, and BeagleBone is changing that landscape.

Open hardware platforms provide pre-designed, modular systems that can be customized for specific applications. This shift is lowering the barrier to entry for startups and smaller embedded hardware design companies, which may not have the resources to develop systems from scratch. By using open hardware, developers can quickly prototype ideas, reducing time to market while ensuring flexibility.

AI and Machine Learning at the Hardware Level

Artificial intelligence (AI) and machine learning (ML) are usually discussed in the context of software, but they are starting to play a role in embedded system hardware design as well. Traditionally, embedded systems relied on predefined algorithms for data processing. But with the integration of AI, hardware is becoming more adaptive, capable of adjusting itself in real-time based on environmental conditions or operational feedback.

Edge computing is a perfect example of where this trend is having a significant impact. Instead of sending all data to the cloud for processing, embedded systems can now handle complex AI tasks locally, thanks to more intelligent hardware architectures. These architectures are optimized to run AI models efficiently, without the need for heavy computational resources.

Power Efficiency Through Energy Harvesting

Embedded systems have always been designed with power efficiency in mind, particularly for applications where changing batteries frequently isn’t practical, such as remote sensing, medical implants, or IoT devices. Traditional power optimization strategies focus on minimizing energy consumption through low-power states or more efficient algorithms.

However, energy harvesting is emerging as a game-changer for embedded hardware design. By capturing energy from ambient sources like light, heat, or motion, devices can potentially operate indefinitely without external power sources. This capability drastically reduces maintenance costs and extends the operational life of embedded systems in remote or inaccessible locations.

Energy harvesting technology is still evolving, but it holds great promise. As more embedded hardware design companies integrate this technology into their designs, it could fundamentally change the way we think about powering devices in the future.

The Rise of Custom Silicon

Custom silicon, particularly application-specific integrated circuits (ASICs), is gaining traction in the embedded hardware design & development world. Instead of relying on general-purpose processors or microcontrollers, more companies are designing custom chips tailored to their specific needs. This approach allows for greater optimization, both in terms of performance and power efficiency, as the chip is designed precisely for the intended use case.

This trend is particularly evident in high-performance applications such as cryptocurrency mining, AI acceleration, and telecommunications, where standard off-the-shelf components can’t deliver the required performance. Custom silicon can also improve security, as companies can integrate hardware-level protections directly into the chip.

Cross-Disciplinary Collaboration

As embedded systems become more complex, embedded hardware design projects are increasingly benefiting from collaboration across multiple disciplines. Mechanical engineers, material scientists, software developers, and electrical engineers are working together more closely than ever before. This interdisciplinary approach allows teams to tackle problems holistically, considering all aspects of the system, from the physical constraints of the hardware to the software that drives it.

Cross-disciplinary collaboration also opens the door to more innovative solutions, as professionals from different fields bring unique perspectives and expertise to the table. This trend will continue to drive forward the capabilities of embedded hardware design, enabling more sophisticated and integrated systems.

Conclusion,

The embedded hardware design industry is undergoing a transformation as new materials, open platforms, AI integration, energy harvesting, custom silicon, and cross-disciplinary collaboration reshape the field. These unconventional approaches are pushing the boundaries of what embedded systems can achieve, offering more efficiency, adaptability, and intelligence. For companies involved in embedded hardware design services, staying ahead means embracing these changes and rethinking traditional approaches to meet the demands of future applications.

For more information on embedded product design companies in usa subscribe to our blog. For sales queries, contact us at +1 (775) 404-5757 or email sales@avench.com. We are here to assist you.

[creativeera]

Embedded Computing Marled is Anticipated to Witness High Growth Owing to Wide Adoption Across End-use Industries

Embedded computing refers to a computer system that is part of a larger mechanical or electrical system designed to perform a dedicated function. Embedded systems are designed for specific control functions within embedded products and machines and operate under the direct control of an embedded program. Some key features of embedded systems include rugged construction, low power usage, real-time operating capabilities and compact size. Embedded devices are commonly found in industrial equipment, automobiles, consumer electronics, home appliances and medical devices to control electronic systems. Their key advantage is the ability to control electronic processes in a precise, flexible and cost-effective manner.

The global embedded computing market is estimated to be valued at US$ 112.45 Bn in 2024 and is expected to reach US$ 174.38 Bn by 2031, exhibiting a compound annual growth rate (CAGR) of 6.5% from 2024 to 2031.

Wide adoption across industries such as industrial automation, transportation, healthcare, telecommunication and consumer electronics is fueling market growth. Embedded systems allow streamlining of electronic processes, reducing downtimes and operation costs for end-use industries. Key Takeaways Key players operating in the embedded computing market are Advanced Micro Devices (AMD), Inc., Advantech Co., Ltd., Avalue Technology Inc., Curtiss-Wright Corporation, Dell Technologies Inc., Emerson Electric Co., Fujitsu Limited, General Electric Company, Hewlett Packard Enterprise Company, Honeywell International Inc., Intel Corporation, Kontron ST AG, Mitsubishi Electric Corporation, Rockwell Automation, Inc., and Texas Instruments Incorporated. The Embedded Computing Market Demand offers significant opportunities for system integrators and solution providers through new product development and capability expansion. Growing digitization trends across industry verticals will continue to generate strong demand for embedded systems with advanced computing and connectivity features. Leading embedded computing companies are focusing on global expansion strategies through partnerships, joint ventures and acquisitions to solidify their presence in emerging economies of Asia Pacific, Latin America, Middle East and Africa. These regions offer high growth potential driven by ongoing modernization of infrastructure and growing electronics manufacturing activities. Market Drivers Wide adoption across industrial automation applications is a key driver for the embedded computing market. Use of embedded systems allows streamlining of electronic processes, reducing downtimes and operation costs for industrial equipment manufacturers. Growing connectivity trends through Industrial Internet of Things (IIoT) will further propel demand. Rising electronics content in automobiles is positively impacting the market. Advanced driver assistance systems, infotainment systems and vehicle networking require powerful embedded computing solutions. Strict fuel efficiency and vehicle emissions norms will accelerate integration of embedded computing hardware. Market Restrain Design complexity of developing embedded system on a chip (SoC) poses challenges, especially for integrating advanced Embedded Computing Companies capabilities with low power requirements. This increases new product development timelines and costs. Limited standardization across various embedded system platforms inhibits seamless interoperability, data exchange and application portability. This poses difficulties for globally distributed product development activities.

Segment Analysis Automotive industrial and transportation is dominating the embedded computing market due to increasing implementation of advanced driver-assistance systems, connected vehicles solutions, electric vehicles, and autonomous vehicles. According to recent surveys over 65% of all new light vehicles shipped will have features like adaptive cruise control, automatic emergency braking, and blind spot monitoring by 2030. All these emerging technologies are driving the growth of embedded systems in automotive applications. Security and defense is another major sub segment in the embedded computing market owing to rising implementation of thermal weapon sights, combat management systems, imaging payloads and guidance systems in warships, aircraft carriers and fighter jets. Real-time information, enhanced situational awareness and integrated mission capabilities are some key priorities for embedded systems in defense applications. Various nations are also focusing on developing autonomous weapons which will further augment demand in coming years. Global Analysis North America dominates the global embedded computing market with a share of over 35% due to substantial research funding and presence of major OEMs in the region. US and Canada are hub for embedded technology development owing to advancement in networking infrastructure, IoT penetration and adoption of Industry 4.0 concepts. Asia Pacific shows fastest growth momentum led by China, India, Japan and South Korea. Low manufacturing cost and government initiatives to digitize industries are driving Asia Pacific market. Intensifying Sino-US trade war may impact supply chain dynamics in long run. Europe captures around 25% market share led by Germany, United Kingdom and France.

Get more insights on Embedded Computing Market

About Author:

Money Singh is a seasoned content writer with over four years of experience in the market research sector. Her expertise spans various industries, including food and beverages, biotechnology, chemical and materials, defense and aerospace, consumer goods, etc. (https://www.linkedin.com/in/money-singh-590844163)

[rupasriymts]

Embedded system designs & Software development

Embedded System Designs are made up of hardware and software components that are specifically designed to do certain tasks within larger systems. The main goal in designing these systems is to make sure they work well, are reliable, and keep costs low. Key parts of embedded systems include microcontrollers or microprocessors, which act like the brain of the system, and peripheral devices like sensors and actuators that interact with the outside world.

The software for these systems is usually written in programming languages like C or C++ and often needs to work in real-time, meaning it responds quickly and predictably to events. For a business like Youngmind, understanding embedded system designs is very important. These systems help make sure that electronic products are efficient, reliable, and cost-effective, leading to better customer satisfaction and lower production costs. Whether Youngmind is developing new gadgets or improving existing ones, focusing on strong embedded system designs can be a key to success.

[blockverse-infotech]

Navigating Through the Depths of Embedded Software: Testing and Verification Strategies

In the complex realm of technology, Embedded Systems serve as the quiet foundation, driving a variety of devices from intelligent gadgets to automotive systems. At the core of these systems lies the embedded software, the unseen power coordinating smooth operation. However, ensuring the dependability and strength of this software is not a simple task. Step into the domain of Embedded Systems Testing and Verification, where BlockVerse Infotech Solutions emerges as a beacon of expertise and ingenuity.

In a time where flawless performance is a must, the importance of thorough testing and verification strategies cannot be overstressed. BlockVerse Infotech Solutions acknowledges this necessity and offers a comprehensive method tailored to tackle the distinctive challenges presented by embedded software.

Initially, understanding the complexities of the embedded environment holds great importance. BlockVerse utilizes a combination of white-box and black-box testing methods to explore deep within the software’s internal operations while replicating real-world situations. This detailed approach ensures not only functional accuracy but also deals with performance, reliability, and security concerns.

Moreover, Blockverse utilizes cutting-edge tools and techniques to simplify the testing process. From automated test frameworks to model-based testing, each tool is utilized with precision to optimize efficiency without compromising quality. By utilizing virtual platforms and emulation, BlockVerse enables thorough testing across various hardware configurations, preventing compatibility issues proactively.

However, testing alone does not guarantee the integrity of embedded software. Verification, the process of confirming that the software meets predefined requirements, is equally crucial. BlockVerse adopts a varied verification approach covering code reviews, static analysis, and formal methods. By scrutinizing every line of code and adhering to industry standards, BlockVerse guarantees compliance with strict quality benchmarks.

To wrap up, embedded software plays a crucial role in modern technology, and its reliability is crucial. With BlockVerse Infotech Solutions leading the way, navigating the intricacies of Embedded Systems Testing and Verification becomes more than just a challenge; it transforms into an opportunity to enhance performance, improve reliability, and propel innovation forward.

[uniquejobs]

Embedded Engineer Jobs in Leading MNC Company | Best Jobs 2023

Introduction Embedded Engineer Jobs: Bosch has Published a notification for the vacancy of Embedded Test Engineer The educational qualification required to apply for this  Bosch is B.E, B.Tech Engineers Interested and eligible candidates can apply for Embedded Engineer Jobs. There is enough time to apply for any job. Read the Bosch Company Jobs’s date, last date to use, and full details of…

[c1qfxugcgy0]

At my last job, we sold lots of hobbyist electronics stuff, including microcontrollers.

This turned out to be a little more complicated than selling, like, light bulbs. Oh how I yearned for the simplicity of a product you could plug in and have work.

Background: A microcontroller is the smallest useful computer. An ATtiny10 has a kilobyte of program memory. If you buy a thousand at a time, they cost 44 cents each.

As you'd imagine, the smallest computer has not great specs. The RAM is 32 bytes. Not gigabytes, not megabytes, not kilobytes. Individual bytes. Microcontrollers have the absolute minimum amount of hardware needed to accomplish their task, and nothing more.

This includes programming the thing. Any given MCU is programmed once, at the start of its life, and then spends the next 30 years blinking an LED on a refrigerator. Since they aren’t meant to be reflashed in the field, and modern PCs no longer expose the fast, bit-bangable ports hobbyists once used, MCUs usually need a third-party programming tool.

But you could just use that tool to install a bootloader, which then listens for a magic number on the serial bus. Then you can reprogram the chip as many times as you want without the expensive programming hardware.

There is an immediate bifurcation here. Only hobbyists will use the bootloader version. With 1024 bytes of program memory, there is, even more than usual, nothing to spare.

Consumer electronics development is a funny gig. It, more than many other businesses, requires you to be good at everything. A startup making the next Furby requires a rare omniexpertise. Your company has to write software, design hardware, create a production plan, craft a marketing scheme, and still do the boring logistics tasks of putting products in boxes and mailing them out. If you want to turn a profit, you do this the absolute minimum number of people. Ideally, one.

Proving out a brand new product requires cutting corners. You make the prototype using off the shelf hobbyist electronics. You make the next ten units with the same stuff, because there's no point in rewriting the entire codebase just for low rate initial production. You use the legacy code for the next thousand units because you're desperately busy putting out a hundred fires and hiring dozens of people to handle the tsunami of new customers. For the next ten thousand customers...

Rather by accident, my former employer found itself fulfilling the needs of the missing middle. We were an official distributor of PICAXE chips for North America. Our target market was schools, but as a sideline, we sold individual PICAXE chips, which were literally PIC chips flashed with a bootloader and a BASIC interpreter at a 200% markup. As a gag, we offered volume discounts on the chips up to a thousand units. Shortly after, we found ourselves filling multi-thousand unit orders.

We had blundered into a market niche too stupid for anyone else to fill. Our customers were tiny companies who sold prototypes hacked together from dev boards. And every time I cashed a ten thousand dollar check from these guys, I was consumed with guilt. We were selling to willing buyers at the current fair market price, but they shouldn't have been buying these products at all! Since they were using bootloaders, they had to hand program each chip individually, all while PIC would sell you programmed chips at the volume we were selling them for just ten cents extra per unit! We shouldn't have been involved at all!

But they were stuck. Translating a program from the soft and cuddly memory-managed education-oriented languages to the hardcore embedded byte counting low level languages was a rather esoteric skill. If everyone in-house is just barely keeping their heads above water responding to customer emails, and there's no budget to spend $50,000 on a consultant to rewrite your program, what do you do? Well, you keep buying hobbyist chips, that's what you do.

And I talked to these guys. All the time! They were real, functional, profitable businesses, who were giving thousands of dollars to us for no real reason. And the worst thing. The worst thing was... they didn't really care? Once every few months they would talk to their chip guy, who would make vague noises about "bootloaders" and "programming services", while they were busy solving actual problems. (How to more accurately detect deer using a trail camera with 44 cents of onboard compute) What I considered the scandal of the century was barely even perceived by my customers.

In the end my employer was killed by the pandemic, and my customers seamlessly switched to buying overpriced chips straight from the source. The end! No moral.

[ottopilot-wrote-this]

Generational Trauma

Once more unto the breach of @subliminalbo's Romero Literary Universe. This story references characters from the Obedience by Fleur series. This is also a prequel to Backend Support, though both stories (hopefully) stand on their own.

Thanks again to my friend @subliminalbo (also at @subliminalboarchive) for the art trade and collaboration.

Bailey Castillo set the clippers on the sink counter and rubbed the base of her skull. She was a queer woman, it certainly wasn't her first time getting an undercut. But it was the first time she'd done it to herself.

It made her smirk to herself. Given the grim nature of what she had talked herself into, Bailey could use all the levity she could muster.

She had an undercut when she met Ed. It was a good metaphor, she thought. Under that big head of dark curls, there was an edge. Her fresh face and polite smile were a mask, disguising survival instincts and a pragmatism you could only get by growing up Black, asexual, and female in Romero, Washington.

Bailey rubbed the shaving gel in her wet fingers until it foamed up. Smelling of peaches, she rubbed it on her shaved hair. After rinsing her hands, she rinsed the razor's blade, new and sharp, in the cold water of the faucet.

It seemed a strange offer. What did a lingerie company need with an embedded systems designer? Software devs for e-commerce, sure. But she specialized in hardware, in writing firmware, in the arcane art of assembly code.

Beggars couldn't be choosers, though. Not beggars who had a degree from the local party school, because Mamá got a discount on tuition, and it was what they could afford. Certainly not beggars who would take the first offer they could get that would get them away from this cesspool. Bailey shaved her neck and the undercut area with smooth, careful strokes.

Her first mistake was trusting. Trusting that if she did a good job - and her control array for Obedience by Fleur was, objectively, goddamn genius - she'd be recognized for it.

Bailey rinsed the razor of shaving cream and tiny black hairs. Won't make that mistake again.

She had overestimated Ed King. She bought his Silicon Valley rep, and failed to see he wasn't any different from Romero's traditional power brokers. He was a carnival barker, not a visionary like he thought he was. She was a commodity to him, not a person. If Obedience failed, she would've taken the blame; but since it succeeded, he was more than happy to take all the credit.

Bailey rubbed the smooth wet skin on her neck, checking for missed spots. Elena wasn't any better. She got what she wanted from Bailey, and that made her disposable. It was a blessing, really. Bailey was a natural beauty, but her curvy hips and thighs meant she wasn't model thin, and it also meant she was back at her mother's house in Romero, and not mindlessly, dutifully, licking Elena's designer boots.

Toweling off her neck, Bailey shifted away from the sink toward the 3D printer. She triple-checked her work.

When she first read about needleless tattoos in Wired, at all just clicked into place. A silicon ink payload in dissolvable microneedles. Putting the Obedience tech inside the subject. Permanently. Forget the sensors, pair the array with a fitness tracker or smartwatch. An AI sidecar to increase subject safety. No more brain damage.

Stealing the base software from Ed King? Bailey had no qualms about stealing from a thief. But she needed stake money. It was surprisingly easy to talk the Chinese triads into financing her. But they wanted proof before they pumped more yuan into her operation.

The 3D printer hummed to life as it printed the dissolvable needles, loaded with silicon ink, onto the dermal patch. This was, of course, a fork, custom firmware modified from the base model. Unfortunately, you can't just print a tiny one of these and slap it on a lab rat.

And experimenting on an unwilling human subject… That was something they would do. Bailey wasn't a monster. Not yet.

The array was done. It was a rectangle about the size of deck of cards. The trick had been spacing, making sure the crudely printed lines wouldn't bleed or touch accidentally when applied. Bailey's array was, of course, unique. She'd created a hyperfocus routine that, when enabled, could drown out stimulation and increase cognitive ability temporarily. More importantly, the mind control protocols were blunted, and she wrote an additional protection against mesmerism: the ability to mentally control her hormone levels.

But at the end of the day, this was modified Obedience by Fleur firmware. Bailey knew there was an unknown period where she would have to take Obedience's best punch, enduring and outlasting it, before the AI sidecar would read her biofeedback and adjust the indoctrination protocols lower. She was prepared for it, with a physical anchor.

She took the black choker, her mother's, in her left hand. When Mamá died, shortly after Bailey came back to Romero with her tail between her legs, it was in her jewelry box.

Bailey didn't know how to reconcile that. Mamá never said anything. She didn't have to. When she left the house wearing this choker, all painted up when she should have been in bed, the vacant look told young Bailey everything. But to keep this in an intimate place, where she likely saw it every day - before the early-onset Alzheimer's rotted her from the inside out - what did that mean?

That she missed it?

Bailey gripped the choker tightly, feeling the satin in her delicate fingers. She couldn't guess what went through her mother's mind. Bailey only knew what it meant to her: anger. Abandonment issues. A keepsake of a life she would never, ever lead.

One last check. One last chance to bitch out.

Bailey sat upright in her work stool. She prepared the tattoo array patch, removing it from the printing tray. She looked again at the choker in her left hand, her anchor to reality. She took the patch, and affixed it to the base of her skull.

At first, there was a cold, wet feeling. Like ultrasound gel. And it itched, probably from the microneedles penetrating her skin. Bailey's research indicated there wouldn't be any pain from the actual absorption of the silicon ink into her dermis, just a slight delay.

Immediately, she realized she'd miscalculated.

Bailey had set the weights on the Obedience protocol to fifty percent. She barely had time to process that was too high before she was inundated with sensation. "Oh… Fuck," she moaned breathlessly. It was so hard to think from the pleasure. Warm and comforting, like a blanket. Like a hug, but not a hug from just anyone. From someone precious. From a lover.

Then she felt something new. A flicker, at first. Then a slow burning heat. Then an intense raging inferno, burning between her legs, deep inside her, in her very soul. Bailey instinctively put her hand there, but it was a huge mistake. Immediately she rubbed her engorged clit through her panties, wetness spreading through the dainty cotton fabric.

Lust? But I'm fucking ace, Bailey thought, before the first orgasm hit.

Wave after wave of euphoric gratification pounded her senses like a tempestuous ocean.

Shit! this is- Then another.

Tides of pleasure washed over her.

The choker. Have to- Another.

The powerful undertow eroded her reason and resistance.

Mamá, I-

The blissful sensations overwhelmed Bailey, preventing the formulation of new thoughts, until she just simply stopped trying.

And then she was under. Submerged. Sounds fading. The world oh, so far away.

She was better this way, she saw that. It was better to stop resisting, stop trying to think, and just accept it. As she enthusiastically fingered her soggy cunt, mouth open, her body rewarding her for her compliance, Bailey thought she heard something. It was her own voice, moaning and panting and… giggling. Being dumb, and sexy, and available - it made her happy?

When was the last time she could say that, that she was legitimately happy?

She understood. She could feel like this for the rest of her life, and she only had to do one thing. Let go. Let go of the past, let go of the trauma, let go of the hurt. Let go of herself. The fingers on Bailey's left hand loosened their grip. The choker threatened to fall to the floor. No, not fall. To sink. To sink and drop, deeper and deeper. Her mind was still. Vacant. Empty, except for one thing creeping into her consciousness.

No. Not today.

Bailey's fingers tightened. She could feel the smooth satin, once cold, now hot with her own emanating warmth. She thought of Mamá, looking more like a movie starlet than her tireless, caring mother. Bailey saw her walk out the door, not even turning back to her crying daughter. And she remembered her pledge, to Mamá, to herself: it ain't gonna be me. Not today. Not ever.

Bailey held the choker with a steel grip, as if her life depended on it. It did. The choker was a life preserver in the choppy ocean of arousal flooding her mind and body. She had no idea how anyone could take twice as much of this. It was no wonder Obedience's control was absolute and immediate.

Slowly, she felt it. The constant bombardment of pleasure losing its steam. Waters receding. Her thoughts forming more easily, coherently. Her breathing stabilizing, and the hot flush of her arousal lowering to a simmer. "Set dopamine levels to zero," she gasped. She didn't need to say the words out loud for it to work, but in her disheveled state she needed to hear it. To remind herself she was in control.

She looked in a nearby mirror. Her eyes were a milky solid white, all sclera, no pupils. Her body was flushed with desire. She looked every bit the fucktoy she despised. Bailey knew she was lucky. If she had looked into this mirror a few minutes ago, she would've been lost.

Her hormone levels stabilizing, Bailey blinked, and her eyes returned to an intense chestnut brown. She was still in shock from the ordeal. She opened her palm and looked at the choker, and she placed it on her workbench. Slowly, she took her cell phone in her right hand and sent a message.

"Live test successful. Production is GO."

-------------------

The dream again. The same one. Fuck, I hate this, Bailey thought. And turning off the dopamine wasn't helping.

Bailey got out of bed and turned on a bedside lamp. She drowsily stood up, stumbled to the kitchen for a drink of cold water. It was a hot July night, so she was only wearing panties. Which, of course, were soaked through. Again.

On her back to bed, she stopped at her nightstand. She looked at herself in the vanity mirror. Running a prostitution empire based on mind control hadn't been kind to her, she thought.

Bailey wasn't sure what possessed her. But she reached into her top drawer, and retrieved Rosa's - Mamá's - choker. She hadn't looked at it since she turned on the Obedience array. She'd been too afraid. But here, in the dark, she fastened the choker around her neck. She activated her hormonal controls and raised them - not too much - to maybe 120% of normal. And she looked in the mirror.

Her eyes clouded over until the pupils were gone again, just solid white spheres. Like two blank canvases. She let her mind dull - again, not too much. Just enough to let her thoughts drift. Her full lips parted, on their own, as she watched with interest and arousal. She had always been beautiful, but now? She was a bombshell. All tits and ass and thighs, with a pretty fuckable face. She didn't have a sexual bone in her 29-year-old body, but she would fuck this braindead slut in the mirror.

Bailey's mind cleared as she regained control. She again dampened her pleasure center, and her eyes returned to normal. She took the choker off, and put it back, reverently, in her dresser drawer.

She now understood why Mamá had kept it.

[sarkos]

Bill Atkinson, the Apple Computer designer who created the software that enabled the transformative visual approach pioneered by the company’s Lisa and Macintosh computers, making the machines accessible to millions of users without specialized skills, died on Thursday night at his home in Portola Valley, Calif., in the San Francisco Bay Area. He was 74.It was Mr. Atkinson who programmed QuickDraw, a foundational software layer used for both the Lisa and Macintosh computers; composed of a library of small programs, it made it possible to display shapes, text and images on the screen efficiently. The QuickDraw programs were embedded in the computers’ hardware, providing a distinctive graphical user interface that presented a simulated “desktop,” displaying icons of folders, files and application programs. Mr. Atkinson is credited with inventing many of the key aspects of graphical computing, such as “pull down” menus and the “double-click” gesture, which allows users to open files, folders and applications by clicking a mouse button twice in succession.

Bill Atkinson, Who Made Computers Easier to Use, Is Dead at 74 - The New York Times