AI; ML; IoT
PPE Usage Dataset
This repository provides the Personal Protective Equipment (PPE) Usage Dataset, designed for training deep neural networks (DNNs). The dataset was collected using the EFR32MG24 microcontroller and the ICM-20689 inertial measurement unit, which features a 3-axis gyroscope and a 3-axis accelerometer.
The dataset includes data for four types of PPE: helmet, shirt, pants, and boots, categorized into three activity classes: carrying, still, and wearing.
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The paucity of data has long hindered the accurate modeling of CO2 concentrations within peatland regions, despite their significance as carbon reservoirs. Peatlands naturally sequester substantial carbon underground, yet disturbances, whether due to climate change or land use shifts, can trigger the release of significant amounts of carbon and other greenhouse gases, thereby disrupting the atmosphere and impacting human lives. The lack of comprehensive data has rendered it challenging to thoroughly assess the peatland regions' contribution to the net ecosystem carbon budget (NECB).
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