AI_BATTERY_OPTIMIZER / dataset_info.json
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dataset_info.json
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{
"description": "The AI Battery Optimizer Dataset is a synthetic smartphone battery usage dataset created for research in energy optimization and ML-based app usage prediction.",
"citation": "@dataset{teamneuralbattery2025,\n author = {Aishwarya Singh and Lavanya Arora and Shreya Kathuria and Navya Jain},\n title = {AI Battery Optimizer Dataset},\n year = {2025},\n publisher = {Hugging Face},\n license = {CC-BY-4.0}\n}",
"homepage": "https://huggingface.co/datasets/teamneuralbattery/AI-Battery-Optimizer",
"license": "CC-BY-4.0",
"features": {
"timestamp": {
"dtype": "string",
"description": "UTC timestamp of the log entry"
},
"battery_percentage": {
"dtype": "int32",
"description": "Battery percentage remaining"
},
"power_usage_mw": {
"dtype": "int32",
"description": "Power usage in milliwatts"
},
"time_remaining_min": {
"dtype": "int32",
"description": "Estimated time remaining in minutes"
},
"predicted_app": {
"dtype": "string",
"description": "Predicted app to be opened next"
},
"confidence": {
"dtype": "float32",
"description": "Confidence score of the prediction (0\u20131)"
},
"brightness": {
"dtype": "int32",
"description": "Screen brightness percentage"
},
"fps": {
"dtype": "int32",
"description": "Frame rate setting (30 or 60 FPS)"
}
},
"splits": {
"train": {
"num_examples": 40,
"name": "train"
},
"test": {
"num_examples": 10,
"name": "test"
}
},
"size_categories": [
"n<1K"
]
}