Smart agriculture

Enhancing the Evaluation of Fault Detection Models in Smart Agriculture Using LLM Agents for Rule-Based Anomaly Generation

In the context of Agriculture 4.0, advanced technologies such as the Internet of Things (IoT), artificial intelligence (AI), and big data analytics play a critical role in enhancing the efficiency and sustainability of farming operations. These …

Deep learning meets smart agriculture: using LSTM networks to handle anomalous and missing sensor data in the compute continuum

In the era of the Internet of Things (IoT), conventional cloud-based solutions struggle to handle the huge amount, high velocity, and heterogeneity of data generated at the network edge. In this context, the edge-to-cloud compute continuum has …