Embedded Intelligence
Smarter, Faster, More Reliable Automated extraction and analysis of vast amounts of actionable information
Devices are now expected to think, adapt and act autonomously.
Embedded software is the intelligence behind modern smart devices—controlling everything from washing machines and mobile phones to industrial automation and implantable medical devices.
Why Embedded Intelligence Matters
Traditional cloud-based approaches struggle with latency, security risks, and power constraints. The future belongs to intelligent edge devices that can process complex signals in real-time, ensuring:
Real-World Application: Real-Time Detection and Classification
- Precise real-time target detection, tracking & classification.
- Optimised signal-processing chains ensure speed, accuracy, and adaptability to environmental changes.
- Advanced ML classification algorithms enable real-time operation within embedded platforms.
Plextek’s PLX-U16 radar performs precise and real-time target detection, location, velocity, and classification. Making use of advanced signal-processing chains optimised to be fast, efficient and accurate, with added intelligence to allow the system to adapt to environmental changes.
One of the challenges of performing classification in real-time is the size of the neural networks. Our ML Classification algorithms were optimised for embedded, real-time operation, specific to the platform.
Talk to our experts
Explore cutting-edge technologies, real-world applications, and business benefits of embedding intelligence into devices, ensuring they can think, adapt, and act—wherever they are needed.
Our Expertise
Plextek’s engineering capabilities set us apart in the field of embedded intelligence. Our key competencies include:
- Real-time system design – Ensuring seamless 24/7 operation for critical applications like radar and autonomous systems.
- Edge intelligence – Maximising the potential of your platform for autonomous operation, even with limited or no connectivity.
- Low size, weight and power (SWaP) – Obtaining optimal processing performance when power budgets are highly constrained.
- Predictive maintenance – Reducing downtime with advanced signal analysis that detects failures before they occur.
- Reliability engineering – Ensuring high system reliability for critical applications.
- Cost-optimised – Delivering complex signal processing solutions within strict budgetary limits, optimising expenditure without sacrificing performance.
- Signal interpretation – Translating complex raw data into actionable insights.
- Advanced noise filtering – Ensuring high-quality data by minimising unwanted clutter.
In embedded systems, the challenge isn’t just developing high-performing AI models but optimising them for real-time execution with strict power and memory constraints. Techniques like quantisation, pruning, and knowledge distillation help bridge this gap.
Freddy Saunders
Senior Data Scientist
Project: Dismounted Position & Navigation Sensor (DPNS)
Please accept cookies in order to enable video functionality.
- A GNSS-free navigation solution, ideal for military and industrial applications.
- Boot-mounted inertial sensors and microprocessors estimate motion and provide precise location data.
- Intelligent signal processing filters out noise and enhances accuracy, all within low SWaP design.
To address the challenge of how to navigate when Global Navigation satellite System (GNSS) signals, such as GPS, are unavailable, Plextek developed a boot-mounted inertial navigation system. This device contains inertial sensors and a microprocessor containing signal processing algorithms to processes the sensor signals to estimate the motion of the boot. This in turn is used to provide accurate position estimation in the absence of GNSS.
The signal processing algorithms filter out unwanted noise, estimate biases, and automatically detect different phases of the user’s gait to derive an accurate measurement – all within the meagre resources of a small microprocessor.
Contact Us
Enhancing network efficiency with ML & RL
Enhancing Mobile Ad-Hoc Network Routing with GNN-Driven DRL Agent: Improving Packet Delivery and Adaptability in Dynamic Environments
Read More
Optimising Radar Training with Machine-Assisted Machine Learning
See how Plextek is optimising radar training using automating data labelling & machine-assisted machine learning
Read More
Semantic Segmentation in Visual Scene Matching
Learn how we boost accuracy in Visual Scene Matching with Semantic Segmentation, aiding navigation and tracking in dynamic environments.
Read More
Machine Learning for Rapid Propagation Assessment
Developing a groundbreaking ML model for swift and efficient coverage prediction in complex urban environments, enabling rapid optimisation of transmitter locations on standard computing hardware.
Read More
Future Sensing: Improving Mobile Ad-hoc Networks
Leading a transformative four-year research initiative to improve mobile ad-hoc networks through advanced directional antenna systems and cross-layer processing, significantly enhancing military communication capabilities.
Read More
Armour Integrity Monitoring System (AIMS)
Innovating a new Armour Integrity Monitoring System (AIMS) for the UK MoD, delivering a low SWaP-C solution that dramatically streamlines logistics and enhances protection through in-field armour integrity checks.
Read More
mmWave Radar for Foreign Object Debris Detection
Collaborating with WaveTech to develop an advanced mmWave radar system, enabling the rapid and automated detection of foreign object debris on runways, enhancing safety and operational efficiency at a South Korean airport.
Read More
Surveillance Radar for Comprehensive Threat Detection
Advancing a perimeter surveillance solution with long-range detection and low false-alarm rates, using state-of-the-art Passive Electronically Scanned Array technology for robust and maintenance-free operation in a range of demanding environments.
Read More
Immersive Technology for Complex Systems Training
Using the latest immersive technologies to deliver realistic and engaging training solutions for complex systems, ensuring specialist procedures are effectively imparted and measured within any environment.
Read More
Distributed Real Time Spectrum Monitoring
Developing an innovative distributed spectrum monitoring system, using low-cost software-defined radio platforms, to provide superior interference detection and larger coverage for high-value sites.
Read More
Intelligent Mobility
Advancing intelligent mobility by integrating cutting-edge electronic-scanning radar technology to ensure the safe and efficient operation of autonomous vehicles in complex real-world environments.
Read More
Telehealth Innovation – Connecting Patients to their Carers
Revolutionising telehealth with the MonitorMe phone, seamlessly connecting patients to healthcare providers for vital signs monitoring.
Read More
Related Technical Papers
View All
Non-Invasive Auditory Sensing with Affordable Headphones
This paper presents a sensor for measuring auditory brainstem responses to help diagnose hearing problems away from specialist clinical settings using non-invasive electrodes and commercially available headphones. The challenge of reliably measuring low level electronic signals in the presence of significant noise is addressed via a precision analog processing circuit which includes a novel impedance measurement approach to verify good electrode contact. Results are presented showing that the new sensor was able to reliably sense auditory brainstem responses using noninvasive electrodes, even at lower stimuli levels.
GPU Computing
Power limits restrict CPU speeds, but GPUs offer a solution for faster computing. Initially designed for graphics, GPUs now handle general computing, thanks to advancements by NVIDIA, AMD, and Intel. With hundreds of cores, GPUs significantly outperform CPUs in parallel processing tasks. Modern supercomputers, like Titan, utilize thousands of GPU cores for immense speed. NVIDIA’s CUDA platform simplifies GPU programming, making it accessible for parallel tasks. While GPUs excel in parallelizable problems, they can be limited by data transfer rates and algorithm design. NVIDIA’s Tesla GPUs provide high performance in both single and double precision calculations. Additionally, embedded GPUs like the NVIDIA Jetson TX2 deliver powerful, low-power computing for specialized applications. Overall, GPUs offer superior speed and efficiency for parallel tasks compared to CPUs.