AI-IoT-based Smart Drip Irrigation System (SDIS) dataset specifically designed for rice plants considering local agronomic characteristics, featuring soil moisture, weather data, and irrigation control decisions for precision agriculture.
Dataset documenting IoT sensor deployments in horticulture operations including greenhouse monitoring, fruit/vegetable cultivation parameters, and automated control systems for temperature, humidity, light, and nutrient delivery.
Comprehensive multi-sensor dataset with 9 parameters including environmental (temperature, humidity, light) and soil measurements (moisture, temperature, pH) plus solar battery voltage and water TDS, collected via Arduino-ESP8266 system with cloud integration.
Cold storage monitoring dataset from IoT-enabled system designed for smallholder farmers in Uganda, featuring temperature, humidity, door events, and power status for training predictive models to classify environmental conditions and assess post-harvest food spoilage risk.
Comprehensive bibliometric dataset of research publications on AI and IoT-based irrigation systems from Scopus and Web of Science (2006-2025), enabling systematic reviews, trend analysis, and research mapping in precision irrigation technology.
Comprehensive collection of research papers on IoT attacks and security models published between 2005-2025 in IEEE, Elsevier, Springer, ACM, and MDPI, compiled for systematic review of IoT network security across all layers, enabling meta-analysis and trend identification.
Comprehensive Industrial IoT security dataset from the Canadian Institute for Cybersecurity, featuring realistic network traffic with 34 types of attacks including DDoS, ransomware, data exfiltration, and advanced persistent threats across multiple IIoT protocols.
Large-scale reproducible IoT network dataset with traffic from 100+ diverse IoT devices including smart home, wearable, and industrial sensors, featuring multiple attack scenarios and benign behavior for intrusion detection research.
Novel dataset correlating real wearable device data (heart rate, steps, sleep, calories) with Self-Reported Quality of Life (SRQoL) measures using the WHOQOL-BREF questionnaire for health monitoring and QoL prediction research.
Multimodal smart city dataset combining IoT sensor data (environmental, traffic, infrastructure) with ground-truth anomaly labels for urban safety applications, anomaly detection, and multi-source data fusion research in smart cities.
Complete and labeled IoT dataset from physical data center with NFC smart passive temperature sensors, containing normal operations and anomalous behaviors for time-series anomaly detection in critical infrastructure environments.
Spatio-temporal water quality dataset from 36 monitoring sites in Georgia, USA, with 11 indices including dissolved oxygen, temperature, conductance, and pH for daily forecasting of pH levels.