{
  "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"
  ]
}