Monitorización Ambiental con IoT y Big Data: Una Revisión Sistemática de Avances y Desafíos.
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Resumen.La integración del Internet de las Cosas (IoT) y el análisis de Big Data ha revolucionado la
monitorización ambiental, permitiendo avances cuantitativos y cualitativos en la gestión de recursos
naturales. Esta revisión sistemática, basada en 55 estudios publicados entre 2019 y 2024 y siguiendo
el protocolo PRISMA, identifica tendencias, logros y desafíos en la aplicación de estas tecnologías.
En agricultura, la adopción de sensores IoT ha reducido el consumo hídrico en un 35% e
incrementado la productividad en un 12%. En la gestión del agua, los nanosensores IoT han
quintuplicado la capacidad de detección de contaminantes respecto a métodos convencionales.
Modelos de aprendizaje profundo, como las redes LSTM alimentadas por datos de más de 15,000
nodos IoT, han logrado una precisión superior al 92% en la predicción de eventos climáticos
extremos. Además, la integración de plataformas IoT y Big Data en ciudades ha contribuido a reducir
las emisiones de CO₂ en un 15% mediante la optimización del tráfico y el consumo energético.
Innovaciones como la arquitectura edge computing han disminuido la latencia de procesamiento en
un 68%, y los gemelos digitales han mejorado la precisión de los modelos predictivos en un 40%.
Globalmente, el mercado de IoT ambiental se proyecta en 21.5 mil millones de dólares para 2028, con
más de 152 ciudades implementando redes IoT para calidad del aire y 35 millones de hectáreas bajo
agricultura de precisión. Sin embargo, persisten retos como la interoperabilidad (23% de las
implementaciones), el costo inicial de despliegue y la brecha tecnológica entre regiones. La
convergencia IoT-Big Data impulsa una transición hacia sistemas de gestión ambiental proactivos,
aunque su escalabilidad depende de superar estos desafíos.
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