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Post Covid-19, the biggest bet for the revival of the industry is on 5G proliferation across the world. It is widely expected that 5G’s Enhanced Mobile broadband (eMBB) with speeds as high as 20X of 4G speed, Ultra-reliable and Low Latency Communication ( URLLC), and massive Machine type connectivity (mMTC) will transform the world. One of the most important use cases for 5G is its use in the Medical field, covering diverse applications like remote Surgery, remote patient monitoring, etc with immense business potential. For example, the Telemedicine market is expected to grow at a compound annual growth rate of 16.5% from 2017 to 2023, parallel with the emergence and roll-out of 5G.


Faststream Technologies’s Super Edge Medical SoC helps research management and conduct clinical research through its purpose-built software.


The healthcare industry itself has technologically got transformed over the years and now generates massive amounts of data each day. A single patient can generate hundreds of gigabytes of data each day, from patient medical records to the large image files generated by MRI, CAT, or PET scans. For example, depending on detector area and pixel size, digital mammograms may have an image matrix of up to 4,800 × 6,000 pixels with a file size of more than 50 MBytes. In parallel, Artificial Intelligence and Machine Learning (AI/ML) are transforming completely the medical diagnostic field. Medical imaging is poised to be used heavily in the early diagnosis, detection, and treatment of diseases.


For example, early detection of pancreatic cancer is challenging because cancer-specific symptoms occur only at an advanced stage, and a reliable screening tool to identify high-risk patients is lacking. Researchers are trying to find a solution by developing an artificial neural network (ANN), training it, and testing it with existing health data. We are certainly seeing the emergence of AI-assisted workflows in the health industry heavily relying on Medical Imaging and AI.


The Super Edge Medical SoC (SEMC) being designed by Faststream Technologies, India is to cater to this specific requirement of the Healthcare industry. OEMs and System Designers will be able to leverage this fully integrated Edge SoC to create solutions that are not possible today. One of the major differentiators for this SoC solution is that it can operate with full 5G connectivity and if needed, it can operate in full-fledged Edge Mode with Edge Computing, Edge Inference, Edge Storage, and even private Edge Cloud.




8 X Cortex-A78 CPU cores, running up to 3.0 GHz – Medical equipment has a life of 8-10 years and we have incorporated enough compute power to take care of present and future needs. This is also needed for running large machine learning models of the future.


RAM- 32GB, Four 72-bit (64-bit + ECC) 3.2 GT/s LP DDR4 SDRAM memory controllers with ECC.


4 X 8 GB 2666 MHz- Module Support.

4K/8K Video Processing


Real-Time processing of 4K/8K Video (up to 7680X4320) to be rendered on huge 98-inch multiple displays is made possible by 4 X Mali-G78 Second-generation premiums GPU based on the Mali Valhall architecture.



1 X ARM NPU ETHOS-N78 Highly Scalable and Efficient Second Generation ML Inference processor.



32 SerDes lanes, PCIe Gen4 supporting data rates up to 16 Gbps. Four PCIe Gen 4.0 8-lane controllers. Using this PCIe Gen4 connectivity, the motherboard will have 2 connectors for 2 X 8TB NVMe PCIe Gen 4 2 2280 Internal High-Performance Solid State Drive (SSD). Till the availability of SSD drives in this configuration, lower capacity SSD up to 2TB can be used.

SUPPORT FOR 96 inch UHD (Ultra High Definition) Monitors


Remote surgeries will need high definition real-time videos to be projected on large UHD monitors through 4X HDMI 2.0 ports at 120 Hz

5G – 5G connectivity will be achieved by using external 3rd party modems like Quectel RM500Q-GL. It is a 5G module optimized for Edge applications.



Trust Zone technology within Cortex A-78 is used to run a trusted boot and trusted OS to create a Trusted Execution Environment (TEE). Typical use cases include the protection of Authentication, cryptography, payment, key material, and Digital Rights Management (DRM). Edge cloud security is in-built into SSDs. HW: AES 128/256 bit (XTS, CTR, CBC, ECB mode), SHA 160/256/512, RSA 2048


SW: TCG Support & Opal 2.0, Pyrite, Sanitize, and Crypto Erase.

Other Interfaces


2 X MIPI CSI-2,SD/ eMMC , 2X USB 3.0 controllers with integrated PHY, 4 X I2C , 4 X UART , 24X GPIO,3 X HDMI , Wi-Fi , BT-5.0 ( Medical Device direct connectivity).


Operating System- Linux

5G – 5G connectivity

5G – 5G connectivity will be achieved by using external 3rd party modems like Quectel RM500Q-GL. It is a 5G module optimized for Edge applications.

Super Edge Medical SoC

Remote Surgery Use Model envisaged being used with Super Edge Medical SoC:


5G makes this possible by cutting latency to almost instantaneous, 2 ms between devices, allowing surgeons to conduct procedures from thousands of miles away as if they were right next to the patient. All medical records of the patient are stored in the local Edge Cloud of the Surgeon in 16TB storage provided by SSDs. They are retrieved instantly by PCIe Gen 4 connectivity of SSDs and displayed on a large 98-inch screen. Real-time data of all the medical procedure monitoring devices at the patient’s end are displayed on UHD 98-inch monitors of the surgeon.

  • In the future, Mixed Reality (MR) and Robotics surgery will also be feasible through the same platform with the entire procedure to be done by the remote surgeon only.
  • During medical procedures, the high-resolution medical images obtained can be fed to the already trained Machine Learning models stored in Edge Cloud, and inference is drawn quickly using powerful  ETHOS.