Intelligent Automation System on a Single-Board Computer Platform for the Agro-Industrial Sector
Abstract
:1. Introduction
- the widespread introduction of new intensive agricultural technologies;
- global climate change;
- an increase in international trade and exchange of crop products; and,
- a decrease in the biodiversity of plant communities (cenoses), etc.
- to define the key principles running the system of automated equipment control being developed to monitor and manage business processes in the enterprise;
- to determine the set of microcontrollers, the basic components of the monitoring hardware;
- to identify sensors, modules and expansion cards compatible with the selected microcontrollers;
- to consider using a computing server designed to process the data transmitted from the microcontroller;
- to identify the main electronic and electrical processes supporting the enterprise’s activities; and,
- to specify the shortcomings of the developed system and offer ways to tackle them.
2. Materials and Methods
- statistical processing and regulation (stabilization) of the controlled parameters of a technological process;
- management of operations or devices;
- software logical control;
- optimization of control over transient modes or individual stages of the process;
- general adaptive process control;
- immediate correction of daily and shift targets to achieve strategic goals;
- direct and indirect measurement (collection, primary processing and storage of information);
- control, warning about, and registration of deviations in the parameters of the technological process;
- calculation of technical, economic and operational indicators of the technological process and equipment;
- analysis of the processing units’ safety/failure lock operation; and,
- prompt display of the requested information on the technological process.
- automatic dispatching of technological equipment parameters (levels, pressures, phase separation levels, temperatures and costs of technological devices);
- comparison of the measured values of the technological parameters with the set values and generation of control, warning and alarm signals;
- display of the process flow in the form of indicators;
- timing of the main technological parameters; and,
- automated operational control of gate and globe valves from the remote control of the automated workplace of the operator or technologist.
3. Results
3.1. System Structure
3.2. Connecting Sensors and Modules to the Arduino Microcontroller
4. Discussion
- The first limitation consists in a small amount of memory. 32 and 64 KB of memory is enough for writing small programs. For a significant number of operations, an external memory module is required.
- Poor computational performance of the microcontroller. This microcontroller incorrectly processes real numbers, as shown by the analysis of its operation as an automatic reader of the electricity meter. It may lose the remainder of the quotient or reset the variables when dividing them. To avoid this, in some cases it is necessary to send the data to an external server for processing, or use additional processing devices, such as, for example, the Raspberry Pi 2 Model B. It has a processing unit, RAM, HDMI, USB, Ethernet, analog audio and video outputs. It also has 40 general-purpose I/O pins that can be used to connect peripherals to interact with actuators, such as contact relays, servomotors, and any sensors.
- Unlogged failures during the program operation. A failure can only be detected if something stops working. However, even if the failure is detected, the system will not report how many times it happened before. In order to record the number of program crashes, you can use EEPROM (Electrically Erasable Programmable Read-Only Memory) special memory cells. These will prevent overloading the microcontroller.
5. Conclusions
- The system operates on the platform of single-board computers based on the Arduino microcontroller.
- The system represents a simple and convenient tool for managing the enterprise’s business processes.
- The use of the developed software for intelligent systems in agriculture significantly reduces labor costs, eliminates human errors, and speeds up the processing of information, even in large agricultural enterprises.
Author Contributions
Funding
Conflicts of Interest
References
- UN DESA. International Migration Report. Department of Economic and Social Affairs. 2019, p. 38. Available online: https://www.un.org/en/development/desa/population/migration/publications/migrationreport/docs/MigrationReport2019_Highlights.pdf (accessed on 20 March 2020).
- OECD. Organisation for Economic Co-operation and Development. 2019. Available online: https://www.oecd-ilibrary.org/agriculture-and-food/agricultural-policy-monitoring-and-evaluation_22217371 (accessed on 20 March 2020).
- Lowder, S.K.; Skoet, J.; Raney, T. The Number, Size, and Distribution of Farms, Smallholder Farms, and Family Farms Worldwide; Food and Agriculture Organization of the United Nations: Rome, Italy, 2016. [Google Scholar] [CrossRef] [Green Version]
- ILOSTAT. Free and Open Access to Labour Statistics. 2019. Available online: https://ilostat.ilo.org/data/ (accessed on 20 March 2020).
- FAO. Food and Agriculture Organization of the United Nations Publications Catalogue. 2019, p. 140. Available online: http://www.fao.org/home/digital-reports/en/ (accessed on 20 March 2020).
- USAID. United States Agency International Development Fiscal Year 2018 Agency Financial Report. 2018; p. 184. Available online: https://www.usaid.gov/sites/default/files/documents/1868/USAIDFY2018AFR_508R.pdf (accessed on 20 March 2020).
- Trendov, N.M.; Varas, S.; Zeng, M. Digital Technologies in Agriculture and Rural Areas–Briefing Paper. 2019. Available online: http://www.fao.org/3/ca4887en/ca4887en.pdf (accessed on 2 September 2019).
- Oliver, S.T.; González-Pérez, A.; Guijarro, J.H. An IoT proposal for monitoring vineyards called SEnviro for agriculture. In Proceedings of the ACM 8th International Conference on the Internet of Things (IOT ’18), Santa Barbara, CA, USA, 15–18 October 2018; pp. 1–4. [Google Scholar]
- Oliver, S.T.; González-Pérez, A.; Guijarro, J.H. A Comprehensive IoT Node Proposal Using Open Hardware. A Smart Farming Use Case to Monitor Vineyards. Electronics 2018, 7, 419. [Google Scholar]
- Oliver, S.T.; González-Pérez, A.; Guijarro, J.H. Adapting Models to Warn Fungal Diseases in Vineyards Using In-Field Internet of Things (IoT) Nodes. Sustainability 2019, 11, 416. [Google Scholar] [CrossRef] [Green Version]
- Oliver, S.T.; González-Pérez, A.; Guijarro, J.H. An IoT Platform Based on Microservices and Serverless Paradigms for Smart Farming Purposes. Sensors 2020, 20, 2418. [Google Scholar]
- Oliver, S.T.; Torres-Sospedra, J.; Belmonte, Ó.; Zarazaga-Soria, F.J.; González-Pérez, A.; Guijarro, J.H. Development of an open sensorized platform in a smart agriculture context: A vineyard support system for monitoring mildew disease. Sustain. Comput. Inform. Syst. 2019. [Google Scholar] [CrossRef]
- Bacco, M.; Barsocchi, P.; Ferro, E.; Gotta, A.; Ruggeri, M. The Digitisation of Agriculture: A Survey of Research Activities on Smart Farming. Array 2019, 3–4, 100009. [Google Scholar] [CrossRef]
- Morais, R.; Silva, N.; Mendes, J.; Adao, T.; Padua, L.; Lopez-Riquelme, J.; Pavon-Pulido, N.; Sousa, J.J.; Peresmy, E. Sense: A comprehensive data management environment to improve precision agriculture practices. Comput. Electron. Agric. 2019, 162, 882–894. [Google Scholar] [CrossRef]
- Krintz, C.; Wolski, R.; Golubovic, N.; Bakir, F. Estimating outdoor temperature from CPU temperature for IoT applications in agriculture. In Proceedings of the 8th International Conference on the Internet of Things (IOT’18), ACM, Santa Barbara, CA, USA, 15–18 October 2018; p. 11. [Google Scholar]
- Kamilaris, A.; Fonts, A.; Prenafeta-Boldύ, F.X. The rise of blockchain technology in agriculture and food supply chains. Trends Food Sci. Technol. 2019, 91, 640–652. [Google Scholar] [CrossRef] [Green Version]
- Zhao, G.; Liu, S.; Lopez, C.; Lu, H.; Elgueta, S.; Chen, H.; Boshkoska, B.M. Blockchain technology in agri-food value chain management: A synthesis of applications, challenges and future research directions. Comput. Ind. 2019, 109, 83–99. [Google Scholar] [CrossRef]
- Fedorenko, V.F.; Goltyapin, V.Y.; Kolchin, L.M. Intellectual Systems in Agriculture: Scientific-Analytic Review; Federal State Scientific Institution, Rosinformagrotekh Publisher: Moscow, Russia, 2017; 156p. [Google Scholar]
- Leea, W.S.; Alchanatisb, V.; Yangc, C.; Hirafuji, M.; Moshoue, D.; Lif, C. Sensing Technologies for Precision Specialty Crop Production Computers and Electronics in Agriculture. Comput. Electron. Agric. 2010, 74, 2–33. [Google Scholar] [CrossRef]
- Shamshiri, R.R.; Weltzien, C.; Hameed, I.A.; Yule, I.J.; Grift, T.E.; Balasundram, S.K.; Pitonakova, L.; Ahmad, D.; Chowdhary, G. Research and development in agricultural robotics: A perspective of digital farming. Int. J. Agric. Biol. Eng. 2018, 11, 1–14. [Google Scholar] [CrossRef]
- Charania, I. Smart Farming: Agriculture’s Shift from a Labor Intensive to Technology Native Industry; Elsevier: Amsterdam, The Netherlands, 2020. [Google Scholar]
- Maslakov, V.; Butsenko, E.; Kurdyumov, A. Developing an IoT system for an agricultural enterprise on a single-board computer platform. In Proceedings of the International Scientific and Practical Conference “Digitization of Agriculture-Development Strategy” (ISPC 2019), June 2019; pp. 174–178. [Google Scholar] [CrossRef] [Green Version]
- Butsenko, E.; Kurdyumov, A. Smart farming on a single-board computer platform. Models Syst. Netw. Econ. Technol. Eng. Soc. 2019, 1, 29. Available online: https://cyberleninka.ru/article/n/umnoe-zemledelie-na-platforme-odnoplatnyh-kompyuterov (accessed on 20 January 2020).
- Kaewmard, N.; Saiyod, S. Sensor data collection and irrigation control on vegetable crop using smart phone and wireless sensor networks for smart farm. In Proceedings of the 2014 IEEE Conference on Wireless Sensors (ICWiSE), Subang, Malaysia, 26–28 October 2014; pp. 106–112. [Google Scholar] [CrossRef]
- Li, D.; Zheng, Y.; Zhao, W. Fault Analysis System for Agricultural Machinery Based on Big Data. IEEE Access 2019, 7, 99136–99151. [Google Scholar] [CrossRef]
- Wang, P. Introduction: Advances in IoT research and applications. Inf. Syst. Front. 2015, 17, 239–241. [Google Scholar] [CrossRef] [Green Version]
- Dachyar, M. Knowledge growth and development: Internet of things (IoT) research, 2006–2018. Helion 2019, 5, 1–14. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ashifuddin Mondal, M.; Rehena, Z. IoT Based Intelligent Agriculture Field Monitoring System. In Proceedings of the 2018 8th International Conference on Cloud Computing, Data Science & Engineering (Confluence), Noida, India, 11–12 January 2018; pp. 625–629. [Google Scholar] [CrossRef]
- Mesquita, J.; Guimarães, D.; Pereira, C.; Santos, F.; Almeida, L. Assessing the ESP8266 WiFi module for the Internet of Things. In Proceedings of the 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA), Turin, Italy, 4–7 September 2018; pp. 784–791. [Google Scholar] [CrossRef]
- Wu, G.; Tao, J.; Xu, X. Application and Design of Wireless Community Alarm System Based on nRF24L01 Module. In Proceedings of the 2019 Chinese Control and Decision Conference (CCDC), Nanchang, China, 3–5 June 2019; pp. 1991–1995. [Google Scholar] [CrossRef]
- Rose, D.C.; Sutherland, W.J.; Parker, C.; Lobley, M.; Winter, M.; Morris, C.; Twining, S.; Ffoulkes, C.; Amano, T.; Dicks, L.V. Decision support tools for agriculture: Towards effective design and delivery. Agric. Syst. 2016, 149, 165–174. [Google Scholar] [CrossRef] [Green Version]
- Granell, C.; Kamilaris, A.; Kotsev, A.; Ostermann, F.O.; Trilles, S. Internet of Things. In Manual of Digital Earth; Springer: Singapore, 2020; pp. 387–423. [Google Scholar]
- El-kadi, H.; Samir, H.; Rezki, Z. Modelling and Reliability Analysis of Multi-source Renewable Energy Systems Using Deterministic and Stochastic Petri Net. Open Autom. Control Syst. J. 2018, 10, 25–40. [Google Scholar] [CrossRef]
- Iliushko, V.; Retha, E.; Dierks, S.; Marques, P. Automatic Control Systems; Marques Aviation: London, UK, 2016; 275p. [Google Scholar]
- Singh, S. Agri-Info: Cloud Based Autonomic System for Delivering Agriculture as a Service; Elsevier: Amsterdam, The Netherlands, 2020. [Google Scholar]
- Zhou, Y. Design of Miniature Unmanned Helicopter Attitude Monitoring System Based on nRF24L01+. In Proceedings of the 2013 Third International Conference on Instrumentation, Measurement, Computer, Communication and Control, Shenyang, China, 21–23 September 2014. [Google Scholar]
- Semin, A.; Kibirov, A.; Rassukhanov, U. Problems and Main Mechanisms to Increase Investment Attractiveness of Agricultural Production. Eur. Res. Stud. J. 2018, 21, 378–400. [Google Scholar] [CrossRef]
- Martino, B.D. Internet of Things Reference Architectures, Security and Interoperability: A Survey; Elsevier: Amsterdam, The Netherlands, 2018; pp. 99–112. [Google Scholar]
- Coquin, D. Assistance via IoT Networking Cameras and Evidence Theory for 3D Object Instance Recognition: Application for the NAO Humanoid Robot; Elsevier: Amsterdam, The Netherlands, 2020. [Google Scholar]
- Kamath, R. Raspberry Pi as Visual Sensor Nodes in Precision Agriculture: A Study. IEEE Access 2019, 7, 45110–45122. [Google Scholar] [CrossRef]
- Chaber, P. Fast Analytical Model Predictive Controllers and Their Implementation for STM32 ARM Microcontroller. IEEE Trans. Ind. Inform. 2019, 15, 4580–4590. [Google Scholar] [CrossRef]
No. | Object | Description of Operation |
---|---|---|
1 | Microcontrollers | Are programmed on the board using a development environment and programming language based on C/C ++ |
2 | Sensors | Measure the necessary physical quantities or react to physical phenomena and transmit this information via electrical signals |
2.1 | Pyroelectric sensor | It captures the movement of warm objects. The output from the sensor is a binary digital signal. If there is no movement, the signal contact = 0. When the motion is detected, the signal contact = 1 |
2.2 | Infrared rangefinder | Is used for navigation and avoiding obstacles |
2.3 | Ultrasonic rangefinder | Is used to determine the distance to the object by generating sound pulses propagated by the sound wave to and from the object |
3 | Function modules | Perform designated functions |
3.1 | MT-16S2H LCD display | Is used to display text messages |
3.2 | Reed switch module | The reed switch contains flexible metal ferromagnetic contacts. They overlap in length, but are a small distance from each other. These are used for switching (closing or opening the circuit). When the magnet is brought near to the reed switch, the contacts close (or open). It can trigger a siren if used as a position control sensor or after lifting an object |
3.3 | Load control module | The maximum switching voltage is AC 250 V or DC 30 V. The rated switching current is 10 A. The relay contact group consists of three contacts, which makes it possible not only to close the circuit, but also to break it. The LED indicator used to control the operation of the module is connected to the system without any additional strapping. It has galvanic isolation and, therefore, is well protected from high-voltage power supplies |
3.4 | Data transfer modules | Establish wired and wireless connection between microcontrollers. Wireless communication modules (nRF24L01 + transceivers) [36] wirelessly scan the sensors and send commands to the executive devices of the system. These are the basic components of a radio control system for devices and other modules |
4 | Ethernet Shield Expansion Card | Acts as a networking device to access other devices. It is based on the Wiznet W5100 chip, which supports both the TCP and UDP protocols |
5 | Web server | Is designed to remotely monitor and control microcontrollers of the system with connected sensors and modules. It is responsible for receiving and processing website requests from clients. The most widespread web servers include Apache, IIS and iPlanet server. They support a large number of modules, utilities, and add-ons. For a small agricultural enterprise intranet, the Internet Information Server (IIS) is the best option. It can be easily deployed and configured, integrated with access controls, uses Performance Monitor (a performance monitoring tool for system settings control), etc. IIS is noted for its high-speed performance. Its components support the HTTP, HTTPS, FTP, NNTP, SMTP, and POP3 protocols |
6 | Resistors | Are used to change the resistance of the electric current. Their resistance varies within 10% depending on the temperature coefficient of resistance |
7 | Capacitor | Is a device that stores electrical energy in electrical circuits. In the AAIS, capacitors are used as isolation elements, where it is necessary to block the flow of direct current, but let the alternating current pass |
8 | Transistor | Several transistors are connected in series to obtain increased power (the Darlington configuration) |
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Butsenko, E.; Kurdyumov, A.; Semin, A. Intelligent Automation System on a Single-Board Computer Platform for the Agro-Industrial Sector. Mathematics 2020, 8, 1480. https://doi.org/10.3390/math8091480
Butsenko E, Kurdyumov A, Semin A. Intelligent Automation System on a Single-Board Computer Platform for the Agro-Industrial Sector. Mathematics. 2020; 8(9):1480. https://doi.org/10.3390/math8091480
Chicago/Turabian StyleButsenko, Elena, Aleksandr Kurdyumov, and Aleksandr Semin. 2020. "Intelligent Automation System on a Single-Board Computer Platform for the Agro-Industrial Sector" Mathematics 8, no. 9: 1480. https://doi.org/10.3390/math8091480
APA StyleButsenko, E., Kurdyumov, A., & Semin, A. (2020). Intelligent Automation System on a Single-Board Computer Platform for the Agro-Industrial Sector. Mathematics, 8(9), 1480. https://doi.org/10.3390/math8091480