• Title/Summary/Keyword: Software Productivity

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Design and Implementation of IoT based Low cost, Effective Learning Mechanism for Empowering STEM Education in India

  • Simmi Chawla;Parul Tomar;Sapna Gambhir
    • International Journal of Computer Science & Network Security
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    • v.24 no.4
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    • pp.163-169
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    • 2024
  • India is a developing nation and has come with comprehensive way in modernizing its reducing poverty, economy and rising living standards for an outsized fragment of its residents. The STEM (Science, Technology, Engineering, and Mathematics) education plays an important role in it. STEM is an educational curriculum that emphasis on the subjects of "science, technology, engineering, and mathematics". In traditional education scenario, these subjects are taught independently, but according to the educational philosophy of STEM that teaches these subjects together in project-based lessons. STEM helps the students in his holistic development. Youth unemployment is the biggest concern due to lack of adequate skills. There is a huge skill gap behind jobless engineers and the question arises how we can prepare engineers for a better tomorrow? Now a day's Industry 4.0 is a new fourth industrial revolution which is an intelligent networking of machines and processes for industry through ICT. It is based upon the usage of cyber-physical systems and Internet of Things (IoT). Industrial revolution does not influence only production but also educational system as well. IoT in academics is a new revolution to the Internet technology, which introduced "Smartness" in the entire IT infrastructure. To improve socio-economic status of the India students must equipped with 21st century digital skills and Universities, colleges must provide individual learning kits to their students which can help them in enhancing their productivity and learning outcomes. The major goal of this paper is to present a low cost, effective learning mechanism for STEM implementation using Raspberry Pi 3+ model (Single board computer) and Node Red open source visual programming tool which is developed by IBM for wiring hardware devices together. These tools are broadly used to provide hands on experience on IoT fundamentals during teaching and learning. This paper elaborates the appropriateness and the practicality of these concepts via an example by implementing a user interface (UI) and Dashboard in Node-RED where dashboard palette is used for demonstration with switch, slider, gauge and Raspberry pi palette is used to connect with GPIO pins present on Raspberry pi board. An LED light is connected with a GPIO pin as an output pin. In this experiment, it is shown that the Node-Red dashboard is accessing on Raspberry pi and via Smartphone as well. In the final step results are shown in an elaborate manner. Conversely, inadequate Programming skills in students are the biggest challenge because without good programming skills there would be no pioneers in engineering, robotics and other areas. Coding plays an important role to increase the level of knowledge on a wide scale and to encourage the interest of students in coding. Today Python language which is Open source and most demanding languages in the industry in order to know data science and algorithms, understanding computer science would not be possible without science, technology, engineering and math. In this paper a small experiment is also done with an LED light via writing source code in python. These tiny experiments are really helpful to encourage the students and give play way to learn these advance technologies. The cost estimation is presented in tabular form for per learning kit provided to the students for Hands on experiments. Some Popular In addition, some Open source tools for experimenting with IoT Technology are described. Students can enrich their knowledge by doing lots of experiments with these freely available software's and this low cost hardware in labs or learning kits provided to them.

A Study on the Factors Influencing Technology Innovation Capability on the Knowledge Management Performance of the Company: Focused on Government Small and Medium Venture Business R&D Business (기술혁신역량이 기업의 지식경영성과에 미치는 요인에 관한 연구: 정부 중소벤처기업 R&D사업을 중심으로)

  • Seol, Dong-Cheol;Park, Cheol-Woo
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.15 no.4
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    • pp.193-216
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    • 2020
  • Due to the recent mid- to long-term slump and falling growth rates in the global economy, interest in organizational structures that create new products or services as a new alternative to survive and develop in an opaque environment both internally and externally, and enhance organizational sustainability through changes in production methods and business innovation is increasing day by day. In this atmosphere, we agree that the growth of small and medium-sized venture companies has a significant impact on the national economy, and various efforts are being made to enhance the technological innovation capabilities of the members so that these small and medium-sized venture companies can enhance and sustain their performance. The purpose of this study is also to investigate how the technological innovation capabilities of small and medium-sized venture companies correlate with the performance of knowledge management and to analyze the role of network capabilities to organize the strategic activities of enterprise to obtain the resources and organizational capabilities to be used for value creation from external networks. In other words, research was conducted on the impact of technological innovation capabilities of small and medium venture companies on knowledge management performance by using network capabilities as parameters. Therefore, in this study, we would like to verify the hypothesis that innovation capabilities will have a positive impact on knowledge management performance by using network capabilities of small and medium venture companies. Economic activities based on technological innovation capabilities should respond quickly to new changes in an environment where uncertainty has increased, and lead to macro-economic growth and development as well as overcoming long-term economic downturns so that they can become the nation's new growth engine as well as sustainable growth and survival of the organization. In addition, this study was conducted by setting the most important knowledge management performance within the organization as a dependent variable. As a result, R&D and learning capabilities among technological innovation capabilities have no impact on financial performance. In contrast, it was shown that corporate innovation activities have a positive impact on both financial and non-financial performance. The fact that non-financial factors such as quality and productivity improvement are identified in the management of small and medium-sized venture companies utilizing their technological innovation capabilities is contrary to a number of studies by those corporate innovation activities affect financial performance during prior research. The reason for this result is that research companies have been out of start-up companies for more than seven years, but sales are less than 10 billion won, and unlike start-up companies, R&D and learning capabilities have more positive effects on intangible non-financial performance than financial performance. Corporate innovation activities have been shown to have a positive (+) impact on both financial and non-financial performance, while R&D and learning capabilities have a positive (+) impact on financial performance by parameters of network capability. Corporate innovation activities have been shown to have no impact on both financial and non-financial performance, and R&D and learning capabilities have no impact on non-financial performance. It could be seen that the parameter effects of network competency are limited to when R&D and learning competencies are derived from quantitative financial performance. It could be seen that the parameter effects of network competency are limited to when R&D and learning competencies are derived from quantitative financial performance.