uploads///C_Semiconductors_INTC IOT Focus

5G to Accelerate Adoption of Edge Computing in 2019 and 2020


Nov. 20 2020, Updated 5:04 p.m. ET

Edge computing

Previously, we saw that autonomous driving is bringing AI (artificial intelligence) from the cloud to the car with the help of 5G (fifth generation) technology. The edge computing market is working along similar lines, as it brings some degree of computing on edge devices like surveillance cameras, drones, home appliances, and industrial equipment where these devices collect data and do some degree of computing themselves before sending it to the cloud for a higher level of computing.

An IoT (Internet of Things) device needs three components to perform edge computing: microcontroller, memory, and connectivity solutions. The IoT trend picked up in 2017 and is expected to accelerate with 5G deployment. Gartner expects the number of IoT devices to reach 20.4 billion by 2020.


Major semiconductor companies are focusing on fast-growing, high-margin markets of the industrial, retail, and smart city.

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Intel’s IoT focus

At the NASDAQ 39th Investor Conference, Intel’s (INTC) chief engineering officer, Murthy Renduchintala, stated that its IoTG (Internet of Things Group) is focused on certain verticals—industrial, retail, and smart city–and is targeting a particular set of workloads—edge inference, vision, and video. He stated that IoTG leverages the R&D (research and development) of Intel’s other business segments to work in IoT devices. For instance, IoTG uses Intel’s data-center-oriented Xeon processors for edge-computing and mobile-oriented Atom processors for low-power, low-performance computing. IoTG is also making specific R&D efforts in markets where it believes edge computing can prove to be profitable.

NVIDIA’s IoT focus

NVIDIA (NVDA) is looking to expand the reach of AI (artificial intelligence) to applications where it can make a difference. It is using its Metropolis Edge-to-Cloud platform to use AI for city management.

NVIDIA wants to leverage over one billion video cameras around the world by 2020 to solve law enforcement and traffic management problems. It wants to use smart cameras to detect anomalies in real-time videos and alert operators, conduct facial recognition in crowded public places, and perform real-time biometric facial recognition with very high accuracy.

Other chip companies benefiting from the IoT trend are Cypress (CY) and Qualcomm (QCOM). Next, we will look at the visual computing trend.

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