Embedded engineering is developing and testing software used to operate various consumer and commercial devices. It includes everything from your smartphone’s Bluetooth to your cardiac pacemaker. The systems are prevalent in medical science, manufacturing, aviation, automotive technology, and consumer electronics.
IoT and Industrial IoT have played a vital role in the growth of embedded systems and accelerated the development of interconnected ecosystems and smart technologies. The demand for new-age digital services is aggressively rising, expanding the market and bringing in innovations for success. The new trends are expected to drive a value of $173.4 billion by 2032 for the global embedded system market.
Here are the top 5 trends transforming the approach to embedded systems:
1. Edge Computing
Today, the large number of devices connected to the Internet and the massive data volume they produce every minute are growing too quickly for traditional data center infrastructures to handle. According to Gartner’s prediction, by 2025, 75% of enterprise-generated data will be outside the centralized data centers.
IT architects have now shifted focus from conventional data centers to the logical edge of the infrastructure. Edge computing is the presence of intelligent computational resources close to the data generation or consumption source. Companies use edge computing to enhance the response times of their remote devices and get more timely insights from every device’s data. Edge computing reduces bottlenecks on the network and data centers that support edge devices. With this paradigm shift, real-time processing capabilities are enhanced, latency is reduced, and there’s less need for continuous internet access. It’s now a key component of embedded applications due to the demand for faster reaction times and better privacy.
Edge AI is deploying AI models on a device or equipment for AI interference and decision-making. It is shifting intelligent computation away from the cloud and closer to data sources. AI algorithms ensure data is processed on the network edge, with or without internet access. It provides data processing within milliseconds with real-time feedback. Edge AI technologies can be used for self-driving cars, security cameras, wearable devices, and smart home appliances.
2. Cybersecurity Layers
With the rise of IoT in various industries, there’s extra emphasis on embedded systems security. To create a comprehensive defense mechanism, engineers need to implement various layers of cybersecurity in embedded systems. Such layers work together to handle security issues and guarantee a comprehensive strategy to safeguard private information and operations.
Some top cybersecurity layers include a secure boot process, authentication and access control, data encryption, firewall and intrusion defense systems, regular software updates, hardware security modules, and more.
For instance, manufacturers are incorporating on-chip functions in microcontroller designs and software frameworks to secure user data against cyber threats. According to cybersecurity mandates, manufacturers are also required to track software vulnerabilities across the lifecycle of their products and implement timely corrective measures. Since a typical device has hundreds of software components with interconnected dependencies, a proactive approach to cybersecurity is the need of the hour.
Embedded systems are the first line of defense in safeguarding the digital ecosystem.
3. DevOps in Embedded Engineering with CI/CD Pipelines
Continuous Integration (CI) and Continuous Deployment/Delivery (CD) are the backbone of modern software development practices. CI is all about integrating code from various teams frequently or daily. Every integration is automatically built, analyzed and tested for early detection of errors and bugs. The CD helps deploy the code to production and makes it ready for deployment with continuous delivery. As a result, it reduces manual intervention and ensures faster releases.
CI and CD provide developers with speedy system errors, failure detection and quick resolution support. They also promote complete transparency and focus on rapidly getting the product out to users.
Building a CI/CD pipeline involves moving a piece of software from development to production. It includes all steps of continuous building of the application, static code analysis, testing and automated software deployment to end users, simplifying the process from start to end.
4. System on Chip (SoC) Integration
Embedded systems now embrace SoC solutions because they can integrate various parts into one chip, increasing the demand for analog and mixed-signal integrated circuits (ICs). Application-specific ICs are small, cost-effective, and offer great performance with IP protection. They fit perfectly in application systems as per their weight, size, and power requirements.
The core elements of embedded SoCs are processors and components like cache, timers, memory, input and output ports, etc. Compared to traditional CPUs, SoCs use less power and can be a more cost-effective solution. They also take up little space and offer a powerful self-contained processor.
SoC technology has transformed the consumer electronics market with compact form factors and powerful capabilities for smart TVs, wearables, and smartphones. By seamlessly integrating processors, memory, and communication interfaces, it is revolutionizing modern gadgets. It’s also effective in automotive systems, networking equipment, industrial applications, medical devices, and IoT.
5. Sensor Fusion
Positioning systems are now more complex since they must process and merge data from various sensors. Sensor fusion improves the precision and dependability of such modern systems and compensates for individual sensor limitations.
Sensor fusion techniques include data-level fusion that combines raw data from various sensors before processing, feature-level fusion for better interpretations and detections, and decision-level fusion to produce a final result.
Companies that work with embedded systems must invest in knowledge and the capabilities of AI usage in their industry. Integrating new-age innovations and trends can help automate internal processes and make new products relevant to the current market and customer needs.
For instance, the automotive industry has a trend towards developing ADAS (Advanced Driver-Assistance Systems), including emergency steering, adaptive control, and emergency braking. This is done by employing Sensor Fusion, wherein sensors like cameras, radar sensors, and LiDAR are combined into a flow processed by systems equipped with AI and ML. As a result, it enables better technical decisions on car control operations like braking or airbag deployment.
How trends are reforming embedded systems:
1. Real-Time – Time-sensitive systems have improved with new advancements like multicore processors on real-time operating systems for better task scheduling and resource management. By integrating AI and ML technologies, systems are now smarter and able to make decisions faster and better.
2. Standalone—With IoT for embedded systems, standalone gadgets like home appliances and gaming consoles interact more effectively with other machines and cloud services.They can process data closer to the device with edge computing, and ensure efficiency with faster response times even without internet connectivity.
3. Networked—ATM security, home security systems, etc., are experiencing security at an astonishing pace, with monitoring and alerts over networks without delay, leveraging the potential of networked embedded systems.
4. Mobile—Smartphones, fitness trackers, etc., have been transformed with SoC designs, improved performance, and enhanced AR/VR tech for immersive user experiences. This helps conserve space and power consumption, and with advanced AI/ML algorithms, personalized interactions are also possible based on acquired behavioral patterns.
We commonly use electronic devices connected to various embedded systems. Tasks for autopilot and automotive sensors in electrical and mechanical streams exemplify the widespread adoption of industry trends. Embedded is now smart, with AI, ML, sensors, and more to automate internal processes and make products and solutions more relevant to customers’ and markets’ current needs.
As we analyze the trends set to influence 2024 and beyond, the quest for an ecosystem enabler emerges as paramount. At ARi, we offer a wide range of embedded engineering solutions for hardware, software, applications, testing & validation, and even test automation. We can help you leverage the latest trends of 2024 so that the second half of the year is more productive and efficient for your industry and your business.
Contact us today to get a detailed understanding of our embedded engineering solutions.
