Transformación Digital para la Sostenibilidad Ambiental. IoT, Big Data y cambio climático.
Keywords:
transformación digital ambiental, sostenibilidad, Internet de las Cosas, Big Data, cambio climáticoSynopsis
El libro Transformación Digital para la Sostenibilidad Ambiental. IoT, Big Data y cambio climático analiza el papel de las tecnologías digitales en la comprensión, monitoreo y gestión de los problemas ambientales contemporáneos. A lo largo de sus cuatro capítulos, se examina la relación entre crisis ambiental y transformación digital, destacando cómo la información confiable, la conectividad, la sensorización, el análisis de datos y la inteligencia artificial pueden fortalecer la toma de decisiones sostenibles. La obra aborda el uso del Internet de las Cosas en el monitoreo de variables ambientales, la importancia del Big Data para construir evidencia, anticipar riesgos y modelar escenarios climáticos, así como los desafíos éticos, técnicos y sociales asociados a la digitalización ambiental. Asimismo, se propone una visión responsable de la tecnología, donde la innovación no sustituye el criterio humano ni la gobernanza pública, sino que los complementa para mejorar la prevención, la adaptación, la restauración ecológica y la resiliencia territorial. En conjunto, el libro ofrece una mirada crítica y propositiva sobre la transformación digital como herramienta estratégica para avanzar hacia modelos de sostenibilidad ambiental más inteligentes, inclusivos y basados en evidencia.
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References
Aliane, N. (2025). Drones and AI-Driven Solutions for Wildlife Monitoring. Drones, 9(7). https://doi.org/10.3390/drones9070455
Bibri, S. E., Huang, J., Jagatheesaperumal, S. K., y Krogstie, J. (2024). The synergistic interplay of artificial intelligence and digital twin in environmentally planning sustainable smart cities: A comprehensive systematic review. Environmental Science and Ecotechnology, 20, 100433. https://doi.org/10.1016/j.ese.2024.100433
Bonilla, V., Campoverde, B., y Yoo, S. G. (2023). A Systematic Literature Review of LoRaWAN: Sensors and Applications. Sensors, 23(20). https://doi.org/10.3390/s23208440
Calvin, K., Dasgupta, D., Krinner, G., Mukherji, A., Thorne, P. W., Trisos, C., Romero, J., Aldunce, P., Barrett, K., Blanco, G., Cheung, W. W. L., Connors, S., Denton, F., Diongue-Niang, A., Dodman, D., Garschagen, M., Geden, O., Hayward, B., Jones, C., … Ha, M. (with Lee, H.). (2023). Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (P. Arias, M. Bustamante, I. Elgizouli, G. Flato, M. Howden, C. Méndez-Vallejo, J. J. Pereira, R. Pichs-Madruga, S. K. Rose, Y. Saheb, R. Sánchez Rodríguez, D. Ürge-Vorsatz, C. Xiao, N. Yassaa, J. Romero, J. Kim, E. F. Haites, Y. Jung, R. Stavins, … C. Péan, Eds.; First). Intergovernmental Panel on Climate Change (IPCC). https://doi.org/10.59327/IPCC/AR6-9789291691647
Choudhary, A. (2024). Internet of Things: A comprehensive overview, architectures, applications, simulation tools, challenges and future directions. Discover Internet of Things, 4(1), 31. https://doi.org/10.1007/s43926-024-00084-3
Cohen-Manrique, C., Camacho-Leon, S., y Villa, J. L. (2025). Emerging trends in IoT for aquatic systems: A systematic literature review. Frontiers in Water, 7. https://doi.org/10.3389/frwa.2025.1699240
Copernicus. (2025). Climate reanalysis. https://climate.copernicus.eu/climate-reanalysis
Elia, G., Solazzo, G., Lerro, A., Pigni, F., y Tucci, C. L. (2024). The digital transformation canvas: A conceptual framework for leading the digital transformation process. Business Horizons, 67(4), 381–398. https://doi.org/10.1016/j.bushor.2024.03.007
E-Waste Monitor. (2024, marzo 20). The Global E-waste Monitor 2024. E-Waste Monitor. https://ewastemonitor.info/the-global-e-waste-monitor-2024/
Feroz, A. K., Zo, H., y Chiravuri, A. (2021). Digital Transformation and Environmental Sustainability: A Review and Research Agenda. Sustainability, 13(3). https://doi.org/10.3390/su13031530
Food and Agriculture Organization. (2026). Digital Agriculture and AI [Innovation at FAO]. OpenInnovationNetwork. https://www.fao.org/innovation/digital-agriculture-and-ai-innovation/en
Garcia, A., Saez, Y., Harris, I., Huang, X., y Collado, E. (2025). Advancements in air quality monitoring: A systematic review of IoT-based air quality monitoring and AI technologies. Artificial Intelligence Review, 58(9), 275. https://doi.org/10.1007/s10462-025-11277-9
Google Earth Engine. (2026). Google Earth Engine. https://earthengine.google.com
Hussien, L. F., Alshaketheep, K., Al-Ahmed, H., Shajrawi, A., Alghizzawi, M., Zraqat, O., y Deeb, A. (2025). The impact of big data analytics on the sustainability reports quality. Discover Sustainability, 6(1), 776. https://doi.org/10.1007/s43621-025-01678-9
IEA. (2025). Energy demand from AI – Energy and AI – Analysis. IEA. https://www.iea.org/reports/energy-and-ai/energy-demand-from-ai
Intergovernmental Panel on Climate Change. (2023). CLIMATE CHANGE 2023 Synthesis Report (p. 184). IPCC. https://doi.org/10.59327/IPCC/AR6-9789291691647
Intergovernmental Panel On Climate Change (Ipcc). (2023a). Climate Change 2022 – Impacts, Adaptation and Vulnerability: Working Group II Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (1a ed.). Cambridge University Press. https://doi.org/10.1017/9781009325844
Intergovernmental Panel On Climate Change (Ipcc) (Ed.). (2023b). Energy Systems. En Climate Change 2022—Mitigation of Climate Change (1a ed., pp. 613–746). Cambridge University Press. https://doi.org/10.1017/9781009157926.008
IPCC. (2023). Climate Change 2023: Synthesis Report (Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, pp. 35–115) [Report]. Intergovernmental Panel on Climate Change. https://doi.org/10.59327/IPCC/AR6-9789291691647
Khan, T., Singh, K., Bhati, B. S., Ahmad, K., Al-Rasheed, A., Getahun, M., y Soufiene, B. O. (2025). Trust-driven approach to enhance early forest fire detection using machine learning. Scientific Reports, 15(1), 14480. https://doi.org/10.1038/s41598-025-99032-6
Laha, S. R., Pattanayak, B. K., Pattnaik, S., Laha, S. R., Pattanayak, B. K., y Pattnaik, S. (2022). Advancement of Environmental Monitoring System Using IoT and Sensor: A Comprehensive Analysis. AIMS Environmental Science, 9(6), 771–800. https://doi.org/10.3934/environsci.2022044
Lam, R., Sanchez-Gonzalez, A., Willson, M., Wirnsberger, P., Fortunato, M., Alet, F., Ravuri, S., Ewalds, T., Eaton-Rosen, Z., Hu, W., Merose, A., Hoyer, S., Holland, G., Vinyals, O., Stott, J., Pritzel, A., Mohamed, S., y Battaglia, P. (2023). Learning skillful medium-range global weather forecasting. Science, 382(6677), 1416–1421. https://doi.org/10.1126/science.adi2336
Medaglia, R. (2024). Measuring the Impacts of Digital Transformation on Climate Change Mitigation and Adaptation. United Nations ESCAP. http://www.unescap.org/kp
NASA Earth Science Data Systems. (2026, junio 5). Your Gateway to NASA Earth Observation Data. Earth Science Data Systems, NASA. https://www.earthdata.nasa.gov/
OECD. (2024). AI principles. OECD. https://www.oecd.org/en/topics/ai-principles.html
OECD. (2025). Government at a Glance 2025. OECD Publishing. https://doi.org/10.1787/0efd0bcd-en
Okafor, N., Ingle, R., Matthew, U., Saunders, M., y Delaney, D. (2024). Assessing and Improving IoT Sensor Data Quality in Environmental Monitoring Networks: A Focus on Peatlands. IEEE Internet of Things Journal, 11(24), 40727–40742. https://doi.org/10.1109/JIOT.2024.3454241
Okot, T., Madrigal-Mendez, P., y Solorzano-Arias, D. (2023). The Internet of Things (IoT) for Sustainability: A Framework for Costa Rica. Journal of technology management and innovation, 18(4), 3–17. https://doi.org/10.4067/S0718-27242023000400003
Organisation for Economic Cooperation and Development. (2020). Smart Cities and Inclusive Growth: Building on the outcomes of the 1st OECD Roundtable fon Smart Cities and Inclusive Growth. OECD Regional Development Papers. https://doi.org/https://doi.org/10.1787/8a4ce475-en
Organisation for Economic Cooperation and Development. (2024). Digitalisation and the environment. OECD. https://www.oecd.org/en/topics/digitalisation-and-the-environment.html
Papadopoulos, T., y Balta, M. E. (2021). Climate Change and big data analytics: Challenges and opportunities. International Journal of Information Management. https://doi.org/10.1016/j.ijinfomgt.2021.102448
Popescu, S. M., Mansoor, S., Wani, O. A., Kumar, S. S., Sharma, V., Sharma, A., Arya, V. M., Kirkham, M. B., Hou, D., Bolan, N., y Chung, Y. S. (2024). Artificial intelligence and IoT driven technologies for environmental pollution monitoring and management. Frontiers in Environmental Science, 12. https://doi.org/10.3389/fenvs.2024.1336088
Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., Luccioni, A. S., Maharaj, T., Sherwin, E. D., Mukkavilli, S. K., Kording, K. P., Gomes, C. P., Ng, A. Y., Hassabis, D., Platt, J. C., … Bengio, Y. (2023). Tackling Climate Change with Machine Learning. ACM Computing Surveys, 55(2), 1–96. https://doi.org/10.1145/3485128
Santarius, T., Dencik, L., Diez, T., Ferreboeuf, H., Jankowski, P., Hankey, S., Hilbeck, A., Hilty, L. M., Höjer, M., Kleine, D., Lange, S., Pohl, J., Reisch, L., Ryghaug, M., Schwanen, T., y Staab, P. (2023). Digitalization and Sustainability: A Call for a Digital Green Deal. Environmental Science & Policy, 147, 11–14. https://doi.org/10.1016/j.envsci.2023.04.020
Teh, H. Y., Kempa-Liehr, A. W., y Wang, K. I.-K. (2020). Sensor data quality: A systematic review. Journal of Big Data, 7(1), 11. https://doi.org/10.1186/s40537-020-0285-1
UNESCO. (2022). Recommendation on the Ethics of Artificial Intelligence (SHS/BIO/PI/2021/1). United Nations Educational, Scientific and Cultural Organization. https://unesdoc.unesco.org/ark:/48223/pf0000381137/PDF/381137eng.pdf.multi
United Nations. (2024). Big Data for Sustainable Development. United Nations. United Nations. https://www.un.org/en/global-issues/big-data-for-sustainable-development?utm_source=chatgpt.com
United Nations Environment Programme. (2025). Emissions Gap Report 2025: Off target—Continued collective inaction puts global temperature goal at risk (A. Olhoff, J. Christensen, W. F. Lamb, M. Pathak, T. Kuramochi, T. Fransen, M. den Elzen, J. Rogelj, y D. Tong, Trads.). https://doi.org/10.59117/20.500.11822/48854
United Nations Environment Programme y International Resource Panel. (2024). Global Resources Outlook 2024—Bend the trend: Pathways to a Liveable Planet as Resource Use Spikes (H. Bruyninckx, S. Hatfield-Dodds, S. Hellweg, H. Schandl, B. Vidal, H. Razian, R. Nohl, R. Marcos-Martinez, J. West, Y. Lu, A. Miatto, S. Lutter, S. Giljum, M. Lenzen, M. Li, L. Cabernard, M. Fischer-Kowalski, V. Kulionis, C. Oberschelp, … D. A. L. Silva, Trads.). https://wedocs.unep.org/handle/20.500.11822/44901
United Nations Human Settlements Programme (UN-Habitat). (2020). Centering People in Smart Cities A playbook for local and regional governments. United Nations. https://unhabitat.org/sites/default/files/2021/11/centering_people_in_smart_cities.pdf
United Nations Office for Disaster Risk Reduction. (2025). Global Status of Multi-Hazard Early Warning Systems 2025. United Nations. https://doi.org/10.18356/9789213587058
Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Qi Dong, J., Fabian, N., y Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901. https://doi.org/10.1016/j.jbusres.2019.09.022
Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S., Felländer, A., Langhans, S. D., Tegmark, M., y Fuso Nerini, F. (2020). The role of artificial intelligence in achieving the Sustainable Development Goals. Nature Communications, 11(1), 233. https://doi.org/10.1038/s41467-019-14108-y
World Bank. (2021). World Development Report 2021: Data for Better Lives. Washington, DC: World Bank. https://doi.org/10.1596/978-1-4648-1600-0
World Meteorological Organization. (2023, febrero 28). WMO and the Early Warnings for All Initiative. World Meteorological Organization. https://wmo.int/activities/early-warnings-all/wmo-and-early-warnings-all-initiative
World Meteorological Organization. (2025). State of the Global Climate 2025 (2025a ed.). World Meteorological Organization. https://doi.org/10.59327/WMO/S/CRI/SOC/1
Zaman, M., Puryear, N., Abdelwahed, S., y Zohrabi, N. (2024). A Review of IoT-Based Smart City Development and Management. Smart Cities, 7(3), 1462–1501. https://doi.org/10.3390/smartcities7030061
Zeng, F., Pang, C., y Tang, H. (2024). Sensors on Internet of Things Systems for the Sustainable Development of Smart Cities: A Systematic Literature Review. Sensors, 24(7). https://doi.org/10.3390/s24072074
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