AIRC-LABWSN: A synchronized multimodal node-level time-series dataset for cross-layer anomaly detection in wireless sensor networks

AIRC-LABWSN is a multi-modal time series dataset at the node level, created to facilitate research on anomaly detection and inter-layer analysis in wireless sensor networks for smart agricultural applications. The dataset integrates environmental data from the Artichoke farming region in Da Lat, together with temporally and spatially expanded environmental data, topological information, and network data produced by ns-3 simulation. The data generation method has two phases: **Phase 1** of environmental data processing include air temperature, air humidity, soil temperature, soil humidity, pH, electrical conductivity, and light intensity. The data augmentation model incorporates seasonal elements, diurnal variations, short-term meteorological changes, node discrepancies, and sensor interference. This step concurrently establishes a simulated topology including 40 sensor nodes and one sink/base station within a 100 m × 100 m region. **Phase 2** use ambient data and topology as inputs for simulating packet transport in ns-3. The nodes are configured using IEEE 802.15.4 Low Rate Wireless Personal Area Network (LR-WPAN), 6LoWPAN, Internet Protocol version 6 (IPv6), and User Datagram Protocol (UDP). In normal operational settings, each sensor node produces a UDP packet every five minutes and relays it to the sink across a multi-hop pathway. Throughout the simulation procedure, network measurements are consolidated in five-minute intervals and exported into network tables. Node-level dynamic tables are linked using the key `(node_id, timestamp)`, while the link table incorporates `neighbor_id` as well. Rows impacted by network events are designated using the fields `is_anomaly`, `anomaly_type`, `anomaly_label`, and `related_event_id`. The network data in AIRC-LABWSN represents inter-layer data produced via ns-3 simulations at the packet level, rather than data obtained directly from a physical network including 41 nodes.