Recent Trends in Embedded Computing

 

Recent Trends in Embedded Computing

An embedded system is an application-specific system designed with a combination of hardware and software to meet real-time constraints. 

The key characteristics of embedded industrial systems include speed, security, size, and power. 

The industry for embedded systems is growing and there are still several barriers that must be overcome. Below are notable trends of the embedded systems.

Improved Security for Embedded Devices

• With the rise of the Internet of Things (IoT), the primary focus of developers and manufacturers is on security. 

• Advanced technologies for embedded security will emerge as key generators for identifying devices in an IoT network.

Cloud Connectivity and Mesh Networking

• Connecting embedded industrial systems to the internet and cloud can take weeks and months in the traditional development cycle. Consequently, cloud connectivity tools will be an important future market for embedded systems. These tools are designed to simplify the process of connecting embedded systems with cloud-based services by reducing the underlying hardware complexities.

• A the similar yet innovative market for low-energy IoT device developers is Bluetooth mesh networks. These solutions can be used for the seamless connectivity of nearby devices while reducing energy consumption and costs.

Reduced Energy Consumption

• A key challenge for developers is the optimization of battery-powered devices for low power consumption and maximum uptime. 

• Several solutions are under development for monitoring and reducing the energy consumption of embedded devices. These include energy monitors and visualizations that can help developers fine-tune their embedded systems, and advanced Bluetooth and Wi-Fi modules that consume less power at the hardware layer.

Real-Time Visualization 

• Developers currently lack tools for monitoring and visualizing their embedded industrial systems in real-time. 

• The industry is working on real-time visualization tools that will give software engineers the ability to review embedded software execution. These tools will enable developers to keep a check on key metrics such as raw or processed sensor data & event-based context switches for tracking the performance of embedded systems.

Deep Learning Applications

• Deep learning represents a rich, yet unexplored embedded systems market that has a range of applications from image processing to audio analysis. 

• Even though developers are primarily focused on security and cloud connectivity right now, deep learning and artificial intelligence concepts will soon emerge as a trend in embedded systems.