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RICE'24
2nd Research, Innovation & Creativity Exhibition 2024
Project ID:
ITCS104
IoT Smart Factory
Project Title:
Category:
Information Technology/ Computer Science
Inventors:
Ashraveen Kumar, Ho Weng Yin, Edmond Coh Rui En, Shaffika bte Mohd Suhaimi, Chan Ler-kuan
Institution/Company:
Southern University College
Invention Description/ Abstract:
Artificial Intelligence, Smart Factory, IoT, Big Data, Microservice, Frontend backend development, software engineering, electrical engineering, automation engineering, cybersecurity engineering, mechanical engineering. IoT Smart factory is a project proposed for the industry for automation and industrial revolution 4th. Of course, automation engineering is a cross-discipline industry. Therefore, it will involve other expertise such as electrical engineering, software engineering, networking engineering, cybersecurity engineering. Automation pyramid: ERP, MES, SCADA, PLC, Sensor and Actuator. These are commonly seen in the industry such as LRT infrastructure, power generator plant, wastewater treatment plant (Chemical engineering), nuclear plant, oil industry, medical industry etc. Therefore, there are huge demands for automation engineers.
What solution we are going proposing?
ERP. We propose a cloud storage which the feature could be extendable and scalable since it is a well design backend system and adopting the popular framework Java Spring adopted by big tech, Netflix, Alibaba etc.MES. We do not propose any.
SCADA. Java Spring with logging monitoring and service registry could serve as ERP or SCADA. ESP32, Raspberry Pi 4 could be served as the server and HMI to the factory operators.
PLC. ESP32, ESP8266 and ESP01.
Sensor. We have the camera AI module.
Actuator. Servo motor. Power relay with AC current with Light Bulb (Could be adopted in real life).
ReactJS and Flutter (Frontend)
Our backend uses Java Spring Cloud microservice has the API gateway, microservice, logging monitoring， ELK stack (Elastic Search, Log Stash, Kibana) with Grafana.
Why is Spring Cloud adopted? It is because it can be well-integrated with Big Data framework. Apache Hadoop.
Distributed File System. We created single node mode and 3 nodes mode. Distributed computing is not common taught in university. However, it is needed by industrial desperately.
3 Nodes= 3 Virtual Machines and 1 physical machine.
Besides, we are roughly doing 3D modelling for elevator by using Fusion360 and PCB design we are using Easy PCB. Nothing's fancy here. Since we are software-background, we do this just to demonstrate how the entire workflow from the software to hardware.
We also do the virtual exhibition by using Blender and ThreeJS hosted by Microsoft Azure and Vercel.
Invention Technical Description
ESP32 Robot Arm.
ESP8266 with Hydraulic Lift
AI camera with Raspberry Pi
Elevator (3D modelling only in Fusion 360）
Radar created by Arduino UNO
ESP01 linked to Java Spring
ESP32 with Power relay to control AC current light bulb (applicable to Smart Home or Smart Factory)
PCB design uses Easy PCB. Easy schematic diagram and PCB board.
ERP. (Storage as a Service) STaaS. Java Thymeleaf, Java Security, MySQL (optional ELK)
SCADA. Interface for ESP32 or ESP01 or ESP8266 or Raspberry Pi.
Robot Arm has the web interface.
Hydraulic Lift also has the web interface.
AI camera with Raspberry Pi. VNC or SSH login.
RADAR. Proccessing programming language to create RADAR interface by using COM communication.
ESP01 has interface.
ESP32 with power relay with AC bulb also has its own interface.
ReactJS, Flutter
Spring Cloud, Microservice, Eureka Server, ELK, Grafana.
This is API gateway. Eureka registry server registers every microservice. Therefore, Spring Cloud could find the PATH to the microservice.
API gateway is common backend design in the industry.
API gateway is the place allowing the frontend to communicate by using HTTP protocol.
Frontend could be mobile, desktop, IoT. Therefore, our IoT devices send HTTP requests to backend Spring to serve. Log file will be generated for tracking, monitoring and cybersecurity handling.
Eureka service can monitor microservice.
As a result, even Flutter, JS framework can call the API from Spring Cloud. Therefore, the huge giant system is done.
However, the large distributed microservice cannot without a good, distributed database. Therefore, we introduce Apache Hadoop. Big Data solution and fundamental data engineering. A lot of people just focus on AL, Deep Learning and Machine Learning but they ignore the fundamental of the data engineering. Where is data from? Data engineering, Apache Hadoop solves the fundamental. Once you have created Apache Hadoop, HDFS, YARN and MapReduce. Then, other Apache could build on its such as Apache Spark, Apache HBase, Apache Cassandra, Hive, Zookeeper, Sqoop. Therefore, without data engineering then ML model does not even have the chance to be deployed in the production environment. Furthermore, distributed HDFS solves distributed computing problem and limited computing power in one computer. This skill is significant for becoming data engineer.
We not just purpose solutions and also bring the big picture on the table. Thank you, you are reading and hope you are getting benefit
Demostration/ Presentation Video
Poster/ Broucher/ Invention Photo
Video Link
Poster Link
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