UTILIZING INTERNET OF THINGS (IOT), ARTIFICIAL INTELLIGENCE, AND VEHICLE TELEMATICS FOR SUSTAINABLE GROWTH IN SMALL, AND MEDIUM FIRMS (SMES)
Keywords:
Internet Of Things, Artificial Intelligence, Vehicle Telematics, Sustainable Growth, Small, And Medium Firms (SMEs)Abstract
The Internet of Things (IoT), artificial intelligence (AI), and vehicle telematics are widely discussed subjects in the context of Industry 4.0. A plethora of publications have been released on these subjects; however, their primary emphasis lies on bigger corporations. Nevertheless, small, and medium firms (SMEs) arise widely recognized as fundamental pillar of many nations' economies. Consequently, it is becoming more crucial to ensure that smaller organizations have convenient access to these technologies and can effectively use them. This study provides a thorough examination and exploration of the prevalence of AI, IoT, and telematic technologies in small and medium-sized manufacturing enterprises (SMEs). It also addresses the existing constraints and potential for facilitating analytical analysis. Initially, a comprehensive examination of the factors that facilitate artificial intelligence (AI), the Internet of Things (IoT), and telematics is presented, along with the four distinct talents related to data analysis. In this document, a thorough examination of existing literature is done, and the resulting discoveries are presented. Lastly, this paper provides a summary of the latest areas of research and development, which aim to make AI, IoT, and telematic technologies more accessible to SMEs. It also discusses new distinct ways to mix the three technologies to achieve better results in SMEs.
References
Mittal S, Khan MA, Romero D, Wuest T. A critical review of smart manufacturing & Industry 4.0 maturity models: implications for small and medium-sized enterprises (SMEs). J Manuf Syst 2018;49:194–214. https://doi.org/10.1016/j.jmsy.2018.10.005.
Colotla I, Fæste A, Heidemann A, Winther A, Andersen PH, Duvold T, et al. Winning the Industry 4.0 race, Innovation Fund Denmark. 2016. Available from: https://innovationsfonden.dk/sites/default/files/2018-07/bcg-winning-the-industry-40-race-dec-2016.pdf.
Moeuf A, Lamouri S, Pellerin R, Tamayo-Giraldo S, Tobon-Valencia E, Eburdy R. Identification of critical success factors, risks and opportunities of Industry 4.0 in SMEs Int J Prod Res 2020;58(5):1384–400. https://doi.org/10.1080/00207543.2019.1636323.
Chiang Y, Lee D. Smart manufacturing with the internet of makers. J Chin Inst Eng 2017;40(7):585–92. https://doi.org/10.1080/02533839.2017.1362324.
EC. What is an SME? 2009 Available from: https://ec.europa.eu/growth/smes/business-friendly-environment/sme-definition.
EC. Statistics on small and medium-sized enterprises. 2019. Available from: https://ec.europa.eu/eurostat/statistics-explained/index.php/Statistics_on_small_and_medium-sized_enterprises#Context.
Spithoven A, Vanhaverbeke W, Roijakkers N. Open innovation practices in SMEs and large enterprises. Small Bus Econ 2013;41(3):537–62. https://doi.org/10.1007/s11187-012-9453-9.
Moeuf A, Pellerin R, Lamouri S, Tamayo-Giraldo S, Barbaray R. The industrial management of SMEs in the era of
Industry 4.0. Int J Prod Res 2018;56(3):1118–36. https://doi.org/10.1080/00207543.2017.1372647.
Quinton S, Canhoto A, Molinillo S, Pera R, Budhathoki T. Conceptualising a digital orientation: antecedents of supporting sme performance in the digital economy. J Strateg Mark 2018;26(5):427–39. https://doi.org/10.1080/0965254X.2016.1258004.
Laforet S, Tann J. Innovative characteristics of small manufacturing firms. J Small Bus Enterp Dev 2006. https://doi.org/10.1108/14626000610680253.
Afaqui MS, Garcia-Villegas E, Lopez-Aguilera E. IEEE 802.11 ax: challenges and requirements for future high efficiency WiFi. IEEE Wirel Commun 2017;24(3):130–7. https://doi.org/10.1109/MWC.2016.1600089WC.
Li S, Xu LD, Zhao S. 5G internet of things: a survey. J Ind Inf Integr 2018;10:1–9. https://doi.org/10.1016/j.jii.2018.01.005.
Mnih V, Kavukcuoglu K, Silver D, Rusu AA, Veness J, Bellemare MG, et al. Human-level control through deep reinforcement learning. Nature 2015;518 (7540):529. https://doi.org/10.1038/nature14236.
Luxhøj JT, Riis JO, Thorsteinsson U. Trends and perspectives in industrial maintenance management. J Manuf Syst 1997;16(6):437–53. https://doi.org/10.1016/S0278-6125(97)81701-3.
Wang J, Ma Y, Zhang L, Gao RX, Wu D. Deep learning for smart manufacturing: methods and applications. J Manuf Syst 2018; 48: 144–56.
Kim H-K, So W-H, Je S-M. A big data framework for network security of small and medium enterprises for future computing. J Supercomput 2019;75(6):3334–67. https://doi.org/10.1007/s11227-019-02815-8.
Chen Y-C, Ting K-C, Chen Y-M, Yang D-L, Chen H-M, Ying JJ-C. A low-cost add-on sensor and algorithm to help small- and medium-sized enterprises monitor machinery and schedule processes. Appl Sci 2019;9(8). https://doi.org/10.3390/app9081549.
Park KT, Im SJ, Kang Y-S, Noh SD, Kang YT, Yang SG. Service-oriented platform for smart operation of dyeing and finishing industry. Int J Comput Integr Manuf 2019;32(3):307–26. https://doi.org/10.1080/0951192X.2019.1572225.
Mourtzis D, Milas N, Vlachou A. An internet of things-based monitoring system for shop-floor control. J Comput Inf Sci Eng 2018 03;18(2):021005. https://doi.org/10.1115/1.4039429.
Mohammed WM, Ferrer BR, Martinez JL, Sanchis R, Andres B, Agostinho C. A multi-agent approach for processing industrial enterprise data. 2017 international conference on engineering, technology and innovation (ICE/ITMC) 2017:1209–15. https://doi.org/10.1109/ICE.2017.8280018.
Varani¯ut˙ e V, Vitkauskait˙ e E, Tarut˙ e A. Peculiarities of IoT-based business model transformations in SMEs. 2018.
