logistics anomaly detection dataset

This dataset captures real-time operational, environmental, and behavioral data from a fleet of connected vehicles and UAVs involved in logistics, supply chain, and autonomous delivery services. Designed to support advanced research in anomaly detection, sensor fault prediction, and driver behavior analysis, the dataset reflects realistic conditions observed in decentralized and distributed logistics environments. 🧾 Data Overview The dataset contains over 60,000 timestamped records collected from multiple edge nodes (vehicles, drones, and IoT-enabled transport units). Each record encapsulates multi-dimensional readings ranging from vehicular dynamics and cargo conditions to network latency and access control status. These data points enable the modeling of context-aware anomalies in logistics systems. ⚙️ Feature Groups The dataset includes more than 55 features, which can be grouped into the following categories: 1. Vehicle and Driving Dynamics Vehicle_ID, Speed, RPM, Gear_Position, Brake_Status, Steering_Angle, Odometer Accel_X, Accel_Y, Accel_Z, Harsh_Braking, Harsh_Acceleration, Drowsy, Seat_Belt 2. Geospatial and Route Metrics Latitude, Longitude, Altitude, Route_Deviation, Distance_Traveled, ETA, Arrival_Delay 3. Environmental Conditions Ambient_Temperature, Humidity, Road_Type, Traffic_Density, Weather_Condition 4. Cargo Telemetry Cargo_ID, Cargo_Type, Cargo_Weight, Cargo_Temp, Shock_Events, Vibration_Level, Seal_Status 5. Driver and Identity Attributes Driver_ID, Phone_Use, Access_Code_Used, Access_Time, Access_Location, Auth_Status, Unauthorized_Access 6. Sensor and Communication Data Sensor_ID, Sensor_Type, Sensor_Status, Latency, Packet_Loss, System_Uptime, Firmware_Version 7. Maintenance Records Last_Maintenance, Next_Maintenance, Maintenance_Type, Component_Replaced, Breakdown_History, Repair_Duration 8. Target Label Anomaly_Status: Binary flag (0 = normal, 1 = anomaly), indicating whether an anomaly was detected based on combined system-level criteria (e.g., unexpected shocks, route deviations, latency spikes, unauthorized access, etc.).