Environmental Sensor Dataset for LSTM-Based Predictive Irrigation in Smart Home Gardening Using Edge IoT
Published: 1 June 2026| Version 1 | DOI: 10.17632/jtsyb593fy.1
Contributors:
MD NAZMUL HOWLADER, Description
This dataset contains 960 time-series environmental observations collected from an IoT-based smart irrigation testbed over 20 days at 30-minute intervals. The dataset includes soil moisture, temperature, humidity, light intensity, and pump status measurements, and was developed to support predictive irrigation research using machine learning and edge IoT platforms such as ESP32.
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Categories
Agricultural Engineering, Machine Learning, Internet of Things, Climate-Smart Agriculture