IoT and Big Data Technologies for Real-Time Monitoring and Data Processing
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".
Deadline for manuscript submissions: 31 May 2026 | Viewed by 88
Special Issue Editor
Interests: sensor fusion; intelligent geospatial computation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent years, Artificial Intelligence (AI), Big Data, and the Internet of Things (IoT) have become ubiquitous technologies, completely transforming the global industrial landscape. Their widespread adoption is no coincidence; it's a direct response to the urgent need to optimize processes, improve decision-making, and unlock new sources of value from data.
These technologies do not operate in isolation; rather, they act in synergy. The IoT, through a vast network of connected sensors and devices, is responsible for collecting a massive and continuous volume of real-time data. For its part, Big Data provides the necessary tools and infrastructure to process, store, and manage this information on an unprecedented scale. Finally, AI feeds on these vast datasets to identify patterns, predict trends, automate complex tasks, and generate valuable insights.
This powerful integration is evident in virtually every sector. In manufacturing, IoT sensors monitor production lines to predict machine failures (predictive maintenance), while AI optimizes quality and performance. In the healthcare sector, Big Data facilitates the analysis of patient histories to accelerate research, and AI assists with diagnostics and creating personalized treatment plans. In retail, AI is used to provide personalized recommendations to customers, and Big Data is used to intelligently manage supply chains
This Special Issue aims to publish various research related, but not limited to, Geospatial AI for Ubiquitous Monitoring.
This could include areas such as:
Multi-sensor data fusion (satellite, UAV, IoT, in-situ) for environmental and climate monitoring
Real-time and near-real-time geospatial data processing
AI-based anomaly detection for hazards such as wildfires, floods, and droughts
Digital Twins for agriculture, climate resilience, and disaster management
Interoperability and standardization for environmental monitoring systems
Citizen science and participatory sensing integrated with GeoAI
Dr. Sara Saeedi
Guest Editor
Manuscript Submission Information
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Keywords
- IoT
- big data
- real-time monitoring
- geospatial AI
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