Environmental Monitoring with IoT and Big Data: A Systematic Review of Advances and Challenges. (Innovation & Development in Engineering and Applied Science, 2025)
The integration of the Internet of Things (IoT) and Big Data analytics has revolutionizedenvironmental monitoring, enabling quantitative and qualitative advances in natural resourcemanagement. This systematic review, based on 55 studies published between 2019 and 2024 andfollowing the PRISMA protocol, identifies trends, achievements and challenges in the application ofthese technologies. In agriculture, the adoption of IoT sensors has reduced water consumption by 35%and increased productivity by 12%. In water management, IoT nanosensors have increased thedetection capacity of contaminants fivefold over conventional methods. Deep learning models, suchas LSTM networks fed by data from more than 15,000 IoT nodes, have achieved greater than 92%accuracy in predicting extreme weather events. In addition, the integration of IoT and Big Dataplatforms in cities has helped reduce CO₂ emissions by 15% by optimizing traffic and energyconsumption.Innovations such as edge computing architecture have decreased processing latency by 68%, anddigital twins have improved the accuracy of predictive models by 40%. Globally, the environmentalIoT market is projected to be worth $21.5 billion by 2028, with more than 152 cities implementingIoT networks for air quality and 35 million hectares under precision agriculture. However, challengesremain, such as interoperability (23% of deployments), initial deployment cost and the technologygap between regions. The IoT-Big Data convergence drives a transition towards proactiveenvironmental management systems, although its scalability depends on overcoming these challenges.
Keywords: Environmental IoT; Big Data; sensors; sustainability