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Real-Time System Monitoring and Control of Automation Industry Using IoT-Based Cloud Platform

  • G. N. L. Ravi Teja
  • S. Sukumar
  • Surya Kompella
  • Raga Sudha
  • G. Pallavi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 624)

Abstract

Industrial manufacturing involves large calibrations of data and process. Security, optimal response time, and control are major constraints while describing a process in industry. Various technologies were in research to enhance the functional capabilities for better responses. IoRT is one such promising technology to provide a better solution in most advanced way. The architectural design of communication through IoT is one of the open challenges facing, and there is a futuristic viability in achieving a solution for such issues. This paper depicts an approach, implementation of a conveyor model of a simple assembly line to separate metal from nonmetal using a Python-controlled 2-axis robotic arm. The entire process can be monitored using a Web server, designed for real-time process application.

Keywords

IoRT/IoT Optimal response Assembly line Web server Assembly line Control 

1 Introduction

Everything around us is getting smarter and changing. The change is taking step toward a better and smart future. The major role of engineering focus to play a pivotal role in bringing those changes to make a point-breaking understanding of the technologies around us in a better way. A smart home can make a smart city, likewise a smart industry can revolutionize the process for a smarter maintenance. It is a small step in making smart industries by reducing the complexity of wired communication with replaceable—connecting devices and cloud platform for analysis and control [1]. This also solves the problem of complex hardware architecture by replacing structural complexity with logical devices and advanced communication devices.

This paper aims to deploy computing techniques in creating a barrier to integration, complexity, to provide more financial gains and energy savings. Sustainability of resources in many small- and medium-scale industries is a current dominant issue. Automated process is a very efficient and effective process on installing very-high-configured equipment, which is a possible constraint in small and medium industries. Consistent growth in market defines targets, but lack of resources has become a possible challenge in many ways.

A simple consideration of a mushroom harvesting plant, where the production process takes minimum of 14 weeks for the yield and most of the approach, is manual. A conveyor system would possibly reduce time of transporting yield; maintain the same environment and easy handling [2, 3]. But yet most of the process is manual and all the information is recorded by a person. This has a possible disadvantage of failure in certain conditions.

The problem persists in many other companies, where the process is dependent on manpower. To avoid problems of human error and to utilize all the manpower for a better production, this paper provides a brief insight of possible advantages of IoT in automation industry.

Initiating the process, identifying metal from nonmetal, handling the part as per requirement are the general insights briefed in this paper with real-time deployment. Usage of IoT concepts helps to monitor the process from any part of the world. One needs not to possibly be live at the moment to see the process. All the processes can be recorded, sorted, and are ready for analytics at an instance.

2 Internet of Things: A Case Study

The way of communication, life style, work culture, and ease of data extraction has changed with Internet. Connecting people bought revolution in once livelihood and next era of modernization is connecting various devices through Internet and cloud, by which smart and intelligent devices revolutionize once working methodology. A survey report stating the number of estimated connecting devices will be 50 billion at least by 2020 which are connected to cloud platform [4, 5]. A better and sophisticated way to connect with other devices is by machine-to-machine (M2M) applications. With IoT, the maximum allowance of physical devices connected to cloud platform would lead to mobile revolution. Comfort, safety, and efficiency are the driving factors for IoT, connecting physical objects to cloud Internet platform. The abbreviation IoT is not yet well defined; Cisco calls it Internet of Everything. Generally, it is Industrial Internet and IBM calls this as the same Internet. But all agree that IoT will make our physical systems much smarter.

2.1 Different Layers of IoT Protocols

The layer of hierarchy is given below. It is not possible to discuss all the available protocols so the protocol stack below will be confined to most common and useful protocols in the current trends [5] (Fig. 1).
Fig. 1

Different layers to understand the protocol stack

2.2 Networking Protocols and Standards for IoT

IoT got a lot of importance from recent past from both academic researches an industrial approach. Due its vast application, support a lot of funding for research is encouraged. Lot of financial aid is being supported and spent to IoT-related technologies and on research, yet a lot of research is being expected in the following years [5, 6, 7].

Considering the protocols related to IoT which are operating at various layers in the networking stack, which includes: MAC—medium access control layer, network and session layer. Representing IoT, the standards and protocols were supported by Internet Engineering Task Force (IETF), IEEE—Institute of Electrical and Electronics Engineers, ITU—International Telecommunication Union (ITU), and other standard organizations. A consistent research of half decade proposed a lot of standards for current and future necessity.

2.3 IoT Ecosystem

The IoT ecosystem defined the layer-level application support. The bottom layer defines the market domain and application domain, which is a smart grid-connected home, or smart health monitoring system, etc.; preceding second layer is sensors to enable the application. Sensors like temperature, humidity, gas, electrical utility meters, cameras [8] were considered as few examples supporting the second layer. The ecosystem is supported with third layer that will interconnect different other layers which allows the generated data or values from the sensors to the communication interference like cloud/Internet or data process center or a computational facility [9]. The entire data is summarized with other previously collected values or data sets representing geographical data or population growth or economic expansion and so on. Machine learning, data mining, artificial intelligence, and other advanced adaptive techniques were used to combine the data and analyze the results. Huge distributed data banks were to be enabled, so that the collaboration approach at application level with communication software like SDN—software-defined networking, SOA—service-oriented architecture. The top or prior layer is all about services that enable the market including health, education, logistics, energy (Fig. 2).
Fig. 2

IoT ecosystem with hierarchy

Developing a successful IoT application is still not an easy task due to multiple challenges [10, 11]. These challenges include mobility, reliability, scalability, management, availability, interoperability, and security and privacy.

3 Basic Concept

Industrial conveyor monitoring and handling control system involve parts which are aggregated into our proposed system. The system designed is represented into our proposed block diagram (Figs. 3 and 4).
Fig. 3

Basic concept of cloud integration of a conveyor system

Fig. 4

Process describing the handling unit

3.1 Working Principle

Arduino Uno: Intelligent devices play a very crucial role in embedded systems. Most common MCU device by ATMEL is being used in Arduino Uno [12]. Being an open-source platform, it is preferably used in various projects on electronics and embedded systems. A physical circuit with MCU will be driven by the software program through IDE that runs from computer to the board (Fig. 5).
Fig. 5

Physical model of Arduino Uno

ESP8266. Esp8266 is an open-source IoT platform. It includes firmware which runs on Wi-Fi (Fig. 6).
Fig. 6

Physical model of ESP8266 Wi-Fi module

A command from user will initiate the process; the part on the conveyor system is identified by a metal sensor integrated over the system. An ultrasonic sensor will identify the exact position of the part over conveyor and stop the sequence; every piece of working can be monitored by a custom-designed Webpage 1tuch.in.

Once the conveyor sequence is performed based on the results depicted by metal sensor and ultrasonic sensors, the robotic arm is given command to collect the part and place it in respective locations as per guidelines. To perform this action, the command center is designed using processing tool (Fig. 7).
Fig. 7

Working principle of the defined hardware algorithm

4 Design and Implementation

Initial setup for the design is as follows: a metal sensor is interfaced to sense the metal objects or parts with better accuracy. MCU (Arduino Uno) is being used for automatic control of entire system which reduces the complexity of design and control. Entire input from sensor unit is provided to MCU for processing, the input from the sensor unit which senses the metal, the data is transmitted to user through Wi-Fi which is connected to cloud/Internet. Acceptance information is being monitored and maintained the server, which will send a message to the user, and the response from the user will decide the action to be performed by the robotic arm with respect to the status of metal sensor.

Later stages implementing the ultrasonic sensor for measuring exact location of part on conveyor reduced the complexity for robotic arm to take necessary action.

4.1 Programming Steps for Programming Arduino Uno Board

  1. (i)

    Connect Arduino Uno to USB port of computer.

     
  2. (ii)

    Initialize the board by selecting type of board being used and also with virtual port assigned to the board in the tools menu.

     
  3. (iii)

    An Arduino Uno sketch usually has five parts: declaring the variables; enabling the setup routine, which will initialize the variables and conditions to run the preliminary code; looping, is the place you add the main algorithm which will be executed repeatedly till an external reset is actively pressed or the sequence is terminated by the user; final section will be for other important functions to activate during the setup enablement and for loop routines.

     
  4. (iv)

    To test the device, upload a preloaded program. This will ensure the device functioning.

     
  5. (v)

    Once after testing, the board is ready for any purpose deployment. Once disconnecting from computer and integrating it with proposed projects directly.

     
  6. (vi)

    Once the program is executed and compiled the project is converted into hex format and can be downloaded into device.

     
  7. (vii)
    Thus, the project life cycle is accustomed with the project implementation (Fig. 8).
    Fig. 8

    Algorithm for the proposed system

     

4.2 Processing Programming Environment

This is a tool to learn how to program using flexible software sketchbook and within the context of visual arts. This open-source tool is more compatible for integrating with external devices like Arduino Uno.

4.3 Real-Time Model

See Fig. 9.
Fig. 9

Real-time system deploying conveyor model, robotic arm, circuitry interface

5 Results, Conclusion, and Future Scope

Through this approach, a lot of calibrations were recorded with few IoT protocols. Considering only one parameter like metal to provide results, being a repetitive process it needs better algorithms and advanced communication protocols to integrate more sensoric data into the cloud platform.

Among 15 iteration cycles, 2 cycles were out of the algorithm. This is a constraint to focus on. A general loop governing the system yields such a result. Further progress is achieved with control algorithms creating a feedback loop using PID tuning filter.

TCP protocol is being implemented for regular communication, with this algorithm, and by using open-source hardware equipment, the designed node could not resist the high-flow buffer rate and the timing function plays a vital role. Little iteration was satisfactory with a time lag of 3–4 s, while few took a time gap of above 10 s. This has a severe effect at the process and outcome. A server-to-server communication way is being implemented for further understanding. Considering packet ratio, durability, timing functions, the approach has given some satisfactory results. Despite this, a lot of research, implementation, and understanding is necessary.

Advanced protocols like MQTT have a benefit compared to TCP and UDP. Few other protocols should also be revised in this case.

This research review paper portrays the importance of IoT in manufacturing and assembly units, its current growth, protocols defining the rules, and further expansion in large scale.

References

  1. 1.
    Condie, S. J. T.: Distributed computing, tomorrow’s panacea-an introduction to current technology, BT Technol. J. 17(2) (1999), pp. 13–23.Google Scholar
  2. 2.
  3. 3.
    Saucy, P., and Mondada, F.: Open access to a mobile robot on the Internet, IEEE Robotics and Automation Magazine 7(1) (2000), pp. 41–47.Google Scholar
  4. 4.
    Goldberg, K., Gentner, S., Sutter, C. et al.: The Mercury project: A feasibility study for Internet robotics, IEEE Robotics and Automation Magazine 7(1) (2000), pp. 35–40.Google Scholar
  5. 5.
    Jia, S., and Takase, K.: Network-based human assist robotic system using CORBA, in: The Sixth International Symposium on Artificial Life and Robotics, Tokyo, Japan, 2001, pp. 105–109.Google Scholar
  6. 6.
    Siegwart, R., Wannaz, C., Garcia, P. et al.: Guiding mobile robots through the Web, in: Proc. of 1998 IEEE/RSJ Conference on Intelligent Robots and Systems; Workshop on Web Robots, Victoria, B.C. Canada, October 12–17, 1998, pp. 1–7.Google Scholar
  7. 7.
    Stein, M.: Painting on the Web, The PumaPaint Project, in: Proc. of 1998 IEEE/RSJ Conference on Intelligent Robots and Systems; Workshop on Web Robots, Victoria, B.C. Canada, October 12–17, 1998, pp. 37–43.Google Scholar
  8. 8.
    Jesus M. Corres, Carlos Ruiz, “Competition oriented learning experience in electronics: Robot fabrication from scratch”, Global Engineering Education Conference (EDUCON) 2016 IEEE, pp. 62–65, 2016, ISSN 2165-9567.Google Scholar
  9. 9.
    Ashraf Suyyagh, Benjamin Nahill, Alexandre Courtemanche, Evgeny Kirshin, Zeljko Zilic, Boris Karajica, “Managing the microprocessor course scope expansion”, Microelectronic Systems Education (MSE) 2013 IEEE International Conference on, pp. 36–39, 2013.Google Scholar
  10. 10.
    Peter Ferschin, Monika Di Angelo, Gerhard Brunner, “Rapid prototyping for kinetic architecture”, Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics Automation and Mechatronics (RAM) 2015 IEEE 7th International Conference on, pp. 118–123, 2015, ISSN 2326-8239.Google Scholar
  11. 11.
    Dalton, B., and Taylor, K.: A framework for Internet robotics, in: Proc. of 1998 IEEE/RSJ, Conference on Intelligent Robots and Systems; Workshop on Web Robots, Victoria, B.C. Canada, October, 1998, pp. 15–23.Google Scholar
  12. 12.
    Arduino Uno official source: www.arduino.cc.

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • G. N. L. Ravi Teja
    • 1
  • S. Sukumar
    • 1
  • Surya Kompella
    • 1
  • Raga Sudha
    • 1
  • G. Pallavi
    • 1
  1. 1.Kriyative Edge Technology Services (P) Ltd.HyderabadIndia

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