AI4IoT

AI4IoT is an AI enabler for standard IoT platforms

Server

Intelligence

v2.0.0
September 5, 2023

kimyj.sejong@gmail.com
Yujin Kim

Git Hub Project Link
AI4IoT

 

Gub Hub Release Direct DownLoad Link
Direct Link Revision Release Date
v2.0 Get Zip v2.0.0 August 2023
v1.1 Get Zip v1.1.0 December 2022
v0.7 Get Zip v0.7.0 November 2021

BSD 3-Clause License

Copyright (c) 2021, Sejong University All rights reserved Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

* Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

* Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

* Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS” AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Documentation

Runtime Environment

WE RECOMMEND USERS TO INSTALL RUNTIME ENVIRONMENT IN LINUX OPERATION SYSTEM. THE GUIDE FOR SETTING RUNTIME ENVIRONMENT ARE APPLIED FOR LINUX OPERATION SYSTEM FOR THE MOMENT!!

 

♦ Hardware

–      Server

Mobius server operated by KETI.

–      Client

Raspberry Pi 4 (ARM Cortex-A72 1.5GHz)

Raspberry Pi Camera (RPI CAMERA BOARD)

 

♦ Software

–      Server

oneM2M Golden Sample server (Mobius)

URL: http://203.253.128.161:7579

–      Client

Linux (version: 2.4.0)

 

 Other environments

–      Network

Connect to the Internet through WI-FI

–      Postman

Version: v8.11.1

–      oneM2M Resource Browser (http://203.253.128.161:7575/#!/monitor)

 

 Installation and configuration

  1. Pip

⇒  python get-pip.py

 

    Module installation

  1. Tensorflow-io

⇒  pip install tensorflow-io

  1. Kafka-python

⇒   pip install kafka-python

  1. Kafka

⇒  wget https://www.apache.org/dist/kafka/2.7.1/kafka_2.13-2.7.1/kafka_2.13-2.7.1.tgz

⇒  sudo tar xzf kafka_2.13-2.7.1.tgz

⇒  sudo mv kafka_2.13-2.7.1 /opt/kafka

  1. Zookeeper

⇒  https://zookeeper.apache.org/releases.html

  1. JDK

⇒  sudo apt install openjdk-11-jdk

⇒  apt install default-jre

 

Get Started

 

  1. Access to root

⇒  su – root

  1. Add a user and change permission

⇒  adduser kafka

⇒  usermod -aG sudo kafka

⇒  su – kafka

  1. Check Java version (openjdk 11)

⇒  java-version

  1. Reflect the edited settings file

⇒  sudo systemctl daemon-reload

  1. Confirm status of the Zookeeper and Kafka server

⇒  sudo systemctl start zookeeper

⇒  sudo systemctl start kafka

⇒  sudo systemctl status zookeeper

⇒  sudo systemctl status kafka

  1. Run file

⇒  python producer.py (example)

⇒  python consumer.py (example)

⇒  python deeplearning.py (example)

AI4IoT

Description

 

Ai4iot is an AI enabler for standard IoT platforms. Our goal is to develop open sources to support AI functions on standard IoT platforms such as Mobius, an open source platform of oneM2M, and EdgeX. We also develop various Use Cases using the AI4IoT framework.

 

 

<AI4IoT Framework>

<AI4IoT Framework>

 

Use case: Metaverse-based virtual store

A metaverse-based online store where stores in the real world are created as digital twins in the metaverse virtual space, and users visit a virtual store in the metaverse space to purchase preferred products. Various smart sensors are used to sense real-world products intelligently for real-time synchronization between the real world and the virtual stores in the metaverse. The edge node at the real-world store loads a trained AI/ML model and infers products’ information. The retrieved product data is then transferred to the IoT platform for real-time synchronization.

A user can now purchase products from a virtual store in the metaverse. The purchase info in the metaverse is notified to the administrator and the purchased product is delivered to the user.

 

<Metaverse-based virtual store>