"EDGE-BATT: Battery Depletion and System Telemetry Dataset for Edge Devices"

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Authors: Adithi Ambatipudi, Aditya Shinde
Cited by: 0

Abstract

"The EDGE-BATT dataset provides system-level telemetry and battery voltage measurements collected from four resource-constrained microcontroller platforms: ESP32 DevKit, ESP32-C3, Arduino Nano 33 BLE, and Raspberry Pi Pico. Data were recorded under controlled operational and stress conditions designed to capture battery depletion behavior and device-level response without packet payload inspection. The ESP32 dataset includes communication and workload metrics such as BLE connection attempts, signal strength, CPU cycles, and latency, while the remaining platforms focus on voltage evolution and normalized voltage variation features. All measurements were logged at fixed sampling intervals during battery-powered operation. This dataset supports research in packet-agnostic anomaly detection, energy depletion attack modeling, TinyML benchmarking, and resource-aware intrusion detection on extreme edge devices. It enables reproducible evaluation of lightweight machine learning models directly on microcontroller-class hardware."

Fields of Study & Subjects

IoT and Edge/Fog Computing Energy Efficiency in Computing Arduino and IoT Applications

Publication details

Journal / source
IEEE DataPort
Publication date
18 February 2026
Language
EN
Document type
Dataset