SORACOM and Preferred Networks carry out Co-demonstration of "Edge Heavy Computing" using machine learning technology on IoT equipment at "CeBIT 2017" in Hannover Germany

Tokyo, Japan – 15 March 2017 –

SORACOM,Inc (Headquarters: Setagaya Ward, Tokyo; President and CEO: Ken Tamagawa), and , Preferred Networks, Inc. (Headquarters: Chiyoda-ku, Tokyo; President and CEO: Toru Nishikawa, hereinafter PFN), announce that at the CeBIT 2017 International Information and Communication Technology Trade Fair, to be held in Hanover Germany from 20th to 24th March, we will carry out a joint demonstration using the deep learning technology developed by PFN on IoT equipment connected to Soracom’s network to showcase the concept of “Edge-Heavy Computing.”

The “SORACOM” IoT communications platform delivers secure, scalable over-the-air connectivity purpose-built for IoT, and supports rapid deployment and operation of IoT systems. With the cloud-native “SORACOM” platform, IoT connectivity can be effectively secured from end to end, integrated natively with leading cloud services, and managed directly via Web console or API.

PFN has strengths in machine learning technologies, including IoT and deep learning. PFN develops and provides software platform products that enable data analytics in distributed and collaborative manner to realize advanced intelligence in the fields of manufacturing, transportation, and bio-healthcare.

With wireless technology such as cellular line provided by Soracom, it is becoming easier to send data directly from the IoT devices to the cloud. However, considering bandwidth and data volume, there is still a challenge to continuously transmit large-scale data such as video and audio in real time.

The demonstration of this time is to make it possible to solve these problems by executing deep learning technology and analyze the data directly on the IoT device, transmitting only the truly valuable data to the cloud. PFN calls this technology “edge heavy computing.” By delivering real-time analysis at the edge, it is possible to solve challenges related to privacy and bandwidth, minimizing data volume required for transmission and discarding video data immediately after analysis.

Co-demo of “Edge Heavy Computing” Details:

1. Content of the demo

We will demonstrate PFN’s deep learning platform “DIMo (Deep Intelligence in-Motion)” operating on “NVIDIA® Jetson™ TX 1”, a high-performance embedded GPU module. Then, we will analyze the demographics of individuals observed by a camera connected to “NVIDIA Jetson TX 1” on the spot. After that, we will forward only the summarized information to the cloud using “SORACOM Air,” and visualize it using “SORACOM Harvest”.

2. Benefits of “Edge Heavy Computing”

The merits obtained by transferring only rough information such as age and gender of the person captured by the camera and position information in the image to the cloud are as follows:

  • When sending images to the cloud directly, resolution and quality have to be dropped, increasing the difficulty of analysis
  • Compared to the typical case of sending images directly to the cloud for analysis, it is only necessary to send very small amounts of data
  • Analysis of high quality and high resolution video without can be conducted without concern for data size
  • Since images are not accumulated in the cloud, they are easily discarded on the camera side after analysis and privacy can be easily maintained


3. Exhibit of joint demonstration Details

  • Time: 20th – 24th March 2017
  • Venue: Hannover, Germany “CeBIT 2017 (International Information and Communication Technology Trade Show)”


Booth number : Hall 12, Stand B 37

* Soracom will also exhibit in Japan Pavillion, Hall 4, Stand A 38, but the above demo exhibition will be Hall 12 only.

NVIDIA offered edge devices for this demonstration exhibition of “Edge Heavy Computing”
Mr. Masataka Osaki, NV representative, Japan representative and vice president of US head office

“As an AI computing company, NVIDIA offers end-to-end solutions from learning server side to deep learning to edge side inference.” The demonstration of this “edge heavy computing” will embody the deep learning solution and will continue to support the efforts of both companies.”

SORACOM is the market-leading platform for cloud-native IoT connectivity. SORACOM provides customers and partners across industries with the tools they need to connect, protect, control and coordinate their IoT deployments at speed and at scale. More than 5,000 customers worldwide now use SORACOM solutions to bring their most advanced use cases from concept to market.

About Preferred Networks, Inc.
Founded in March 2014 with the aim of business utilization of deep learning technology focused on IoT. Edge Heavy Computing handles the enormous amount of data generated by devices in a distributed and collaborative manner at the edge of the network and realizes innovation in the three priority business areas of the transportation system, manufacturing industry, and bio- healthcare.
PFN develops and provides solutions based on the Deep Intelligence in-Motion (DIMo, Daimo) platform that provides state-of-the-art deep learning technology. Collaborating with world leading organizations, such as Toyota Motor Corporation, Fanuc Inc., National Cancer Research Center, we are promoting advanced initiatives.

About NVIDIA Jetson TX 1
Jetson TX 1 is a supercomputer installed in a credit card size module. NVIDIA Maxwell ™ architecture, 256 NVIDIA CUDA® core, 64-bit CPU with very efficient processing power. It also has the latest technology of deep learning, computer vision, GPU computing and graphics, making it the most suitable module for embedded visual computing.

Company Outline
Company Name: SORACOM, INC.
CEO: Ken Tamagawa
Headquarters: Oshima Bldg. 3F, Tamagawa 4-5-6,
Setagaya-ku, Tokyo

Inquiries regarding this news item
Spokesperson: Jake Martin

Preferred Networks Co., Ltd. /