Digital Agriculture, Remote Sensing and IoT
Articles here cover multispectral and thermal remote sensing, digital twins, IoT systems, and machine learning applications. Data collection, cleaning, processing pipelines, and MLOps are discussed as part of decision-support systems. The output is improved monitoring accuracy, predictive insights, and operational optimization in smart farming.
Geospatial Foundation Models for Farm Yield
Geospatial foundation models combine satellite imagery, embeddings, and field data to improve crop monitoring and water management, but farm yield forecasting still requires local validation and auditable data.
SAR for Smart Agricultural Insurance Assessment
SAR enables faster, more transparent smart agricultural insurance assessment by monitoring crop lodging, storm damage, and flooding, provided satellite data is linked to farm boundaries and audited against algorithms and ground data.
RAG Agricultural GenAI Agent for Climate Risk
A RAG agricultural GenAI agent is valuable when it delivers planting, crop nutrition, and climate-risk advice based on local data, trusted sources, human oversight, data governance, water limits, market standards, and multidimensional evaluation.
Federated Learning for Farm Sensor Data Security
Federated learning keeps raw data on the farm while training AI models across sensors and edge gateways, making it directly relevant to data security, water management, communication costs, and farmer trust.
Simulating Livestock Behavior with AI and Advanced Deepfake Technology
Advanced deepfake technology enables the creation of digital twins for livestock, allowing accurate simulation of their behavior and emotional responses. This innovation plays a key role in improving animal welfare and optimizing herd management.
Livestock Health Monitoring with Smart Sensors and Artificial Intelligence
Wearable sensors and intelligent algorithms continuously track animals’ vital signs, helping reduce disease outbreaks, lower treatment costs, and boost efficiency in livestock farming.
Early Detection of Plant Stress Using UV–VIS Drone Imaging
UV–VIS drone-based imaging enables the detection of subtle changes in leaf pigments and structure before any visible symptoms appear, helping to improve irrigation efficiency.
Thermal Remote Sensing Technology
Thermal monitoring of farmland using infrared imagery enables early detection of water stress and accurate assessment of plant health, paving the way for optimized irrigation strategies.
Biosensors in Advancing Health and Food Quality
Biosensors ensure food safety by rapidly detecting contamination and pathogens. This modern technology enhances the quality of the food industry supply chain.
Development of Advanced Technologies in Iran’s Beekeeping Industry
Modern technologies in beekeeping, utilizing precise sensors and artificial intelligence systems, provide optimal environmental conditions and enhance honey quality, paving the way for the sustainable development of beekeeping.