Development of IoT applications based on the MicroPython platform for Industry 4.0 implementation

Gašpar, Gabriel; Fabo, Peter; Kuba, Michal; Flochova, J.; Dudak, Juraj; Florková, Zuzana

doi:10.1109/me49197.2020.9286455

Cited by 10 publications

(8 citation statements)

References 4 publications

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“…Two things are certain: I4.0 requires university graduates and professionals with new knowledge, and the practical expertise and the implementation of digital technologies, which are at the core of the new requests. In the concept of I4.0 concept of smart factories have an essential place, so different authors have been addressing this issue according to different components and perspectives and education and training [7,8]. Since the development of competencies in digital technologies has been in focus, the usage of microcontroller platforms in control education [9] and other fields of education [10] have significant importance.…”

Section: Introductionmentioning

confidence: 99%

A Cloud-Based with Microcontroller Platforms System Designed to Educate Students within Digitalization and the Industry 4.0 Paradigm

et al. 2021

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The primary purpose of this paper is to present a system intended for student education based on a microcontroller platform and a cloud system where data will be stored. Obtained research results will be based on the application of The NodeMcu platform for data collection with sensor systems. MatLab, ThingSpeak cloud system, and the Virtuino platform will be used for data presentation. Quantitative data are applied to determine conditions for agriculture system performance management. By analyzing the literature and the current situation in monitoring and managing in the agriculture and ecology field, it can be concluded that there are no special education courses regarding these issues. This knowledge was a good starting point for the research presented in this paper. Accordingly, the findings include developing a monitoring and management system intended for student education in mentioned fields. In addition, the practical implications of this research includes the acquisition of information related to student satisfaction with this method of education in the courses of engineering, agriculture, and ecology. The presented system may enable benchmarking, simulation, and verification of different scenarios to improve students’ knowledge regarding sensors’ application in natural conditions. The originality of the research lies in the presented software solution that can be made available to educational institutions and other scientific institutions to serve as a basis in the overall monitoring and management of agricultural and ecology parameters.

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Section: Introductionmentioning

confidence: 99%

A Cloud-Based with Microcontroller Platforms System Designed to Educate Students within Digitalization and the Industry 4.0 Paradigm

et al. 2021

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“…It is composed of a full Python runtime and a subset of the Python standard library while able to fit a 256 KB code space and run with 16 kB RAM. Micropython has been proven to be a good option for rapid development of IoT devices with tested and verified libraries [10]. Currently, its main use targets are: device development and testing, sensor design, monitoring and configuration tools in design of complex applications, and education purposes [10].…”

Section: Related Workmentioning

confidence: 99%

“…Micropython has been proven to be a good option for rapid development of IoT devices with tested and verified libraries [10]. Currently, its main use targets are: device development and testing, sensor design, monitoring and configuration tools in design of complex applications, and education purposes [10]. For instance, [11] presents a prototype of an educational mobile robot based on MicroPython.…”

Section: Related Workmentioning

confidence: 99%

Search and rescue with sparsely connected swarms

et al. 2023

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Swarm robotics is an emerging field of research which is increasingly attracting attention thanks to the advances in robotics and its potential applications. However, despite the enthusiasm surrounding this area of research, software development for swarm robotics is still a tedious task. That fact is partly due to the lack of dedicated solutions, in particular for low-cost systems to be produced in large numbers and that can have important resource constraints. To address this issue, we introduce BittyBuzz, a novel runtime platform: it allows Buzz, a domain-specific language, to run on microcontrollers while maintaining dynamic memory management. BittyBuzz is designed to fit a flash memory as small as 32 kB (with usable space for scripts) and work with as little as 2 kB of RAM. In this work, we introduce the BittyBuzz implementation, its differences from the original Buzz virtual machine, and its advantages for swarm robotics systems. We show that BittyBuzz is successfully integrated with three robotic platforms with minimal memory footprint and conduct experiments to show computation performance of BittyBuzz. Results show that BittyBuzz can be effectively used to implement common swarm behaviors on microcontroller-based systems.

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“…Micropython is currently utilized for various purposes, such as device development, testing, sensor design, monitoring and configuration tools in complex application design, as well as education. 36 An educational mobile robot prototype based on Micropython is presented in Khamphroo et al 37 For example, mobile robots are used in diverse environments and require interdisciplinary collaboration from experts in various domains for their successful engineering. While there are many model-driven solutions proposed for the software engineering of mobile robotics systems, there is a lack of a systematic study to guide research and practitioners in this field.…”

Section: Related Workmentioning

confidence: 99%

An integrated Design Methodology for Swarm Robotics using Model-Based Systems Engineering and Robot Operating System

Aloui,

Guizani,

Hammadi

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part C:

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In swarm robotics, robots solve problems using collective behaviors similar to those observed in natural systems, such as birds, bees or fish. They determine their collective behavior through several simple interactions. However, the behavior of swarms emerging from local interactions remains difficult to predict. When trying to design swarm robotic systems for real applications, researchers are confronted with a wide range of software and hardware challenges in the different phases of the design process; problems related to the modeling of swarm systems, related to simulation, related to implementation on software and even on real systems, etc. Despite the increasing popularity of swarm robotics, designing effective and scalable swarm systems remains a challenging task due to the complex interactions between the individual robots and the environment. Therefore, there is a need for a systematic and comprehensive methodology that can guide designers in developing swarm robotics systems that are efficient, reliable, and adaptable to different scenarios. Our main contribution is to propose a new integrated methodology for the development of swarm robot systems. This methodology is based on modeling with Model-Based Systems Engineering method (MBSE) to specify the requirements and the collective behaviors of the swarms, then on the verification of the developed models and finally on the validation of the swarm system by physical prototyping with real robots. Our contribution also focuses on the development of a new SysML profile using the Domain Specific Language (DSL) that we call SwarmML to customize the functional and structural modeling of a swarm system (properties and attributes of the swarm). Two case studies are applied to validate our methodology; a case study of an aggregation of a swarm of robots and a case study of a collaborative simultaneous localization and mapping application (C-SLAM) performed by a swarm of Turtlebots. The novelty of this proposed methodology is the combination of SysML and Robot Operating System (ROS) to address the management of traceability between the different levels of swarm system design, in order to achieve functional, physical and software integration.

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Development of IoT applications based on the MicroPython platform for Industry 4.0 implementation

Cited by 10 publications

References 4 publications

A Cloud-Based with Microcontroller Platforms System Designed to Educate Students within Digitalization and the Industry 4.0 Paradigm

A Cloud-Based with Microcontroller Platforms System Designed to Educate Students within Digitalization and the Industry 4.0 Paradigm

Search and rescue with sparsely connected swarms

An integrated Design Methodology for Swarm Robotics using Model-Based Systems Engineering and Robot Operating System

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