Análisis y revisión documental de los algoritmos de IA en el AIoT: Una breve revisión

datacite.rightshttp://purl.org/coar/access_right/c_16eceng
dc.contributor.advisorMéndez Torrenegra, Fernando Miguel
dc.contributor.authorOliveros Altamar, Emanuel
dc.contributor.authorObredor Arévalo, Sergio Andrés
dc.date.accessioned2023-12-04T21:43:00Z
dc.date.available2023-12-04T21:43:00Z
dc.date.issued2023
dc.description.abstractEl artículo aborda la problemática principal de la convergencia entre Internet de las cosas (IoT) y la Inteligencia Artificial de las cosas (AIoT) y cómo estas tecnologías pueden colaborar para mejorar la eficiencia, la seguridad y la calidad de vida en diversos sectores. Su objetivo principal es analizar las teorías y metodologías relacionadas con la convergencia de IoT y AIoT, al mismo tiempo que se exploran las oportunidades y desafíos que surgen de esta combinación. Para lograr este objetivo, se emplea una metodología basada principalmente en una revisión bibliográfica exhaustiva de la literatura académica relacionada con IoT, IA y AIoT. Se llevaron a cabo búsquedas avanzadas en bases de datos reconocidas, como IEEE y Google Acholar, con el fin de identificar bibliografía relevante que proporcionara información amplia y actualizada sobre cada uno de estos términos. Además, se examinaron minuciosamente las concepciones, definiciones y enfoques de los diferentes autores que trataban el tema en cuestión. Se prestó especial atención a los resúmenes, las introducciones y las conclusiones de los trabajos seleccionados para obtener una visión general de los temas tratados. El artículo presenta una revisión bibliográfica que destaca la convergencia entre IoT y AIoT y cómo estas tecnologías pueden ser utilizadas en conjunto para mejorar la eficiencia, la seguridad y la calidad de vida en diversos sectores. Se identificaron las áreas de aplicación más significativas de IoT y AIoT, y se evaluaron los desafíos y oportunidades que surgen de esta convergencia. Los resultados obtenidos proporcionan una visión clara de cómo la combinación de IoT y AIoT puede transformar aspectos clave de la vida cotidiana y la industria. Las conclusiones del artículo subrayan la importancia de la convergencia de IoT y AIoT, resaltando su potencial para transformar muchos aspectos de la vida cotidiana y la industria. La sinergia entre estas tecnologías puede impulsar soluciones creativas y mejorar la eficiencia en áreas como la salud, la movilidad, la energía y la gestión de ciudades inteligentes, entre otros sectores. Además, se plantean desafíos que deben abordarse, como la privacidad y la seguridad de los datos, la interoperabilidad de los dispositivos y los modelos de negocio sostenibles. Se proporciona una visión integral de la convergencia entre IoT y AIoT, basada en una revisión bibliográfica exhaustiva. Se destacan las áreas de aplicación más relevantes y se evalúan los desafíos y oportunidades que surgen de esta convergencia. Estos hallazgos contribuyen a la comprensión de cómo la combinación de estas tecnologías puede mejorar la eficiencia, la seguridad y la calidad de vida en diversos sectores, y enfatizan su potencial transformador en la vida cotidiana y la industria.spa
dc.description.abstractThe article addresses the main issue of the convergence between the Internet of Things (IoT) and Artificial Intelligence of Things (AIoT) and how these technologies can collaborate to improve efficiency, safety and quality of life in various sectors. Its main objective is to analyze the theories and methodologies related to the convergence of IoT and AIoT, while exploring the opportunities and challenges arising from this combination. To achieve this objective, a methodology based primarily on a comprehensive literature review of the academic literature related to IoT, AI and AIoT is employed. Advanced searches were conducted in recognized databases, such as IEEE and Google Scholar, in order to identify relevant literature providing comprehensive and up-to-date information on each of these terms. In addition, the conceptions, definitions and approaches of the different authors dealing with the topic in question were thoroughly examined. Special attention was paid to the abstracts, introductions and conclusions of the selected works in order to obtain an overview of the topics covered. The article presents a literature review highlighting the convergence between IoT and AIoTand how these technologies can be used together to improve efficiency, safety and quality of life in various sectors. The most significant application areas of IoT and AIoT were identified, and the challenges and opportunities arising from this convergence were assessed. The results obtained provide a clear picture of how the combination of IoT and AIoT can transform key aspects of everyday life and industry. The article's conclusions underline the importance of the convergence of IoT and AIoT, highlighting their potential to transform many aspects of everyday life and industry. The synergy between these technologies can drive creative solutions and improve efficiency in areas such as healthcare, mobility, energy and smart city management, among other sectors. In addition, there are challenges that need to be addressed, such as data privacy and security, device interoperability and sustainable business models. A comprehensive view of the convergence between IoT and AIoT is provided, based on a comprehensive literature review. The most relevant application areas are highlighted and the challenges and opportunities arising from this convergence are assessed. These findings contribute to the understanding of how the combination of these technologies can improve efficiency, safety and quality of life in various sectors, and emphasize their transformative potential in everyday life and industry.eng
dc.format.mimetypepdfspa
dc.identifier.urihttps://hdl.handle.net/20.500.12442/13535
dc.language.isospaspa
dc.publisherEdiciones Universidad Simón Bolívarspa
dc.publisherFacultad de Ingenieríasspa
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccesseng
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectIoTeng
dc.subjectAIeng
dc.subjectIoMTeng
dc.titleAnálisis y revisión documental de los algoritmos de IA en el AIoT: Una breve revisiónspa
dc.type.driverinfo:eu-repo/semantics/bachelorThesiseng
dc.type.spaTrabajo de grado - pregradospa
dcterms.referencesAl-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., & Ayyash, M. (2015). Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications. IEEE Communications Surveys and Tutorials, 17(4), 2347–2376. https://doi.org/10.1109/COMST.2015.2444095eng
dcterms.referencesAtzori, L., Iera, A., & Morabito, G. (2010). The Internet of Things: A survey. Computer Networks, 54(15), 2787–2805. https://doi.org/10.1016/j.comnet.2010.05.010eng
dcterms.referencesDong, B., Shi, Q., Yang, Y., Wen, F., Zhang, Z., & Lee, C. (2021). Technology evolution from self-powered sensors to AIoT enabled smart homes. In Nano Energy (Vol. 79). Elsevier Ltd. https://doi.org/10.1016/j.nanoen.2020.105414eng
dcterms.referencesGhosh, A., Chakraborty, D., & Law, A. (2018). Artificial intelligence in Internet of things. In CAAI Transactions on Intelligence Technology (Vol. 3, Issue 4, pp. 208–218). Institution of Engineering and Technology. https://doi.org/10.1049/trit.2018.1008eng
dcterms.referencesGonzález García, C., Núñez-Valdez, E., García-Díaz, V., Pelayo G-Bustelo, C., & Cueva-Lovelle, J. M. (2019). A Review of Artificial Intelligence in the Internet of Things. International Journal of Interactive Multimedia and Artificial Intelligence, 5(4), 9. https://doi.org/10.9781/ijimai.2018.03.004eng
dcterms.referencesZhang, J., & Tao, D. (2021). Empowering Things with Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things. In IEEE Internet of Things Journal (Vol. 8, Issue 10, pp. 7789–7817). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/JIOT.2020.3039359eng
dcterms.referencesY. -J. Lin, C. -W. Chuang, C. -Y. Yen, S. -H. Huang, J. -Y. Chen and S. -Y. Lee, "An AIoT Wearable ECG Patch with Decision Tree for Arrhythmia Analysis," 2019 IEEE Biomedical Circuits and Systems Conference (BioCAS), Nara, Japan, 2019, pp. 1-4, doi: 10.1109/BIOCAS.2019.8919141.eng
dcterms.referencesH. Zhu, P. Tiwari, A. Ghoneim y M. S. Hossain, "Collaborative AI-Enabled Pretrained Language Model for AIoT Domain Question Answering", IEEE Transactions on Industrial Informatics, vol. 18, no. 5, pp. 3389-3398, mayo 2022, Paper no. TII-21-2392. DOI: 10.1109/TII.2021.3097183.eng
dcterms.referencesChang, R. C.-H., Institute of Electrical and Electronics Engineers, & IEEE Circuits and Systems Society. (n.d.). 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems AICAS 2019 : March 18-20, 2019, Hsinchu, Taiwan : proceedings.eng
dcterms.referencesHu, X., Li, Y., Jia, L., & Qiu, M. (2022). Novel Two-Stage Unsupervised Fault Recognition Framework for Industrial Big Data. IEEE Transactions on Industrial Informatics, 18(2), 1293-1301. doi: 10.1109/TII.2021.3061749eng
dcterms.referencesY. Ma et al., “LungBRN: A Smart Digital Stethoscope for Detecting Respiratory Disease Using bi-ResNet Deep Learning Algorithm,” in 2019 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2019, pp. 1–4. doi: 10.1109/BIOCAS.2019.8919021.eng
dcterms.referencesB. Sai Yaswanth, N. P. Raj, B. P. Rahul, V. M. Moger, and B. T. V. Murthy, “Solar Power Based Agriculture Robot for Pesticide Spraying, Grass Cutting and Seed Sowing,” 2022, pp. 795–805. doi: 10.1007/978-981-19-2281-7_73.eng
dcterms.referencesF.-L. Huang, Z.-Z. Liao, T.-H. Wang, Q. Chen, T. Wu, y C.-H. Chang, Intelligent and Disaster Prevention Hard Hat Based on AIOT and Speeches Recognition. 2019. doi: 10.1109/icmlc48188.2019.8949271.eng
dcterms.referencesD. C. Kulkarni y R. Soni, Smart AIOT based Woman Security system. 2021. doi: 10.1109/mticti53925.2021.9664760.eng
dcterms.referencesK. Jivrajani et al., "AIoT-Based Smart Stick for Visually Impaired Person," in IEEE Transactions on Instrumentation and Measurement, vol. 72, pp. 1-11, 2023, Art no. 2501311, doi: 10.1109/TIM.2022.3227988.eng
dcterms.referencesC.-C. Wei, C.-W. Chen, y L.-C. Hung, Establish a smart healthcare system with AIoT for Chinese Medicine. 2022. doi: 10.1109/icot56925.2022.10008112.eng
dcterms.referencesV. Arivukkody, T. Gokulakannan and S. Kalpana, "Aiot Based Residential Smart Energy Meter with Power Saving Methodology," 2022 1st International Conference on Computational Science and Technology (ICCST), CHENNAI, India, 2022, pp. 80-85, doi: 10.1109/ICCST55948.2022.10040364.eng
dcterms.referencesL. Kumar et al., "Electric Vehicle (EV) Preventive Diagnostic System: Solution for Thermal Management of Battery packs using AIOT," 2023 IEEE 13th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 2023, pp. 0041-0046, doi: 10.1109/CCWC57344.2023.10099185.eng
dcterms.referencesB. -W. Chen, Y. -S. Jhang, H. -T. Pai, S. -H. Wang, M. -H. Sheu and T. -H. Chen, "AIoT-based Audio Recognition System for Smart Home Applications," 2021 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW), Penghu, Taiwan, 2021, pp. 1-2, doi: 10.1109/ICCE-TW52618.2021.9603103.eng
dcterms.referencesW. -C. Hu, L. -B. Chen, B. -H. Wang, G. -W. Li and X. -R. Huang, "An AIoT-Based Water Quality Inspection System for Intelligent Aquaculture," 2022 IEEE 11th Global Conference on Consumer Electronics (GCCE), Osaka, Japan, 2022, pp. 551-552, doi: 10.1109/GCCE56475.2022.10014181.eng
dcterms.referencesC. -J. Chen, Y. -Y. Huang, Y. -S. Li, C. -Y. Chang and Y. -M. Huang, "An AIoT Based Smart Agricultural System for Pests Detection," in IEEE Access, vol. 8, pp. 180750-180761, 2020, doi: 10.1109/ACCESS.2020.3024891.eng
dcterms.referencesJ. Chen et al., “Edge2Analysis: A Novel AIoT Platform for Atrial Fibrillation Recognition and Detection,” IEEE J Biomed Health Inform, vol. 26, no. 12, pp. 5772–5782, 2022, doi: 10.1109/JBHI.2022.3171918.eng
dcterms.referencesP. A. Sánchez-Sánchez, «Autoregressive Moving Average Recurrent Neural Networks Applied to the Modelling of Colombian Exchange Rate», 2018. https://bonga.unisimon.edu.co/handle/20.500.12442/2384eng
dcterms.referencesS. M. Paul, «Internet de las cosas y la salud centrada en el hogar». http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0120-55522016000200014eng
dcterms.referencesY.-J. Lin, C.-W. Chuang, C.-Y. Yen, S.-H. Huang, J. Y. Chen, y S.-Y. Lee, Live Demonstration: An AIoT Wearable ECG Patch with Decision Tree for Arrhythmia Analysis. 2019. doi: 10.1109/biocas.2019.8919138.eng
dcterms.referencesN. Boutros-Saikali, K. Saikali and R. A. Naoum, "An IoMT platform to simplify the development of healthcare monitoring applications," 2018 Third International Conference on Electrical and Biomedical Engineering, Clean Energy and Green Computing (EBECEGC), Beirut, Lebanon, 2018, pp. 6-11, doi: 10.1109/EBECEGC.2018.8357124.eng
dcterms.referencesM. M. Misgar and M. P. S. Bhatia, "Detection of Depression from IoMT Time Series Data using UMAP features," 2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS), Greater Noida, India, 2022, pp. 623-628, doi: 10.1109/ICCCIS56430.2022.10037751.eng
dcterms.referencesM. Shahzad and A. Ganji, "IoTm: A Lightweight Framework for Fine-Grained Measurements of IoT Performance Metrics," 2018 IEEE 26th International Conference on Network Protocols (ICNP), Cambridge, UK, 2018, pp. 12-22, doi: 10.1109/ICNP.2018.00012.eng
oaire.versioninfo:eu-repo/semantics/acceptedVersioneng
sb.programaIngeniería de Sistemasspa
sb.sedeSede Barranquillaspa

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