Power Consumption Patterns Using Telemetry Data

2026-02-25

AI Summary

This study challenges the conventional assumption that device power consumption is predominantly determined by hardware, instead investigating the influence of user behavior on system-level energy usage. Leveraging Intel telemetry data, the research employs exploratory data analysis and linear regression models to compare power consumption patterns across users in different countries, with a focus on the United States and China. The findings reveal a statistically significant association between user behavior and overall power draw, demonstrating that behavioral factors exert a non-negligible impact on energy consumption. This insight offers a novel perspective for green computing initiatives and provides empirical evidence to inform stakeholders such as Intel in refining energy-efficiency strategies and mitigating environmental impact.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Machine Learning: Hardware-aware ML

Application Category

• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Security and Privacy: Large-scale security measurements

Abstract

This paper examines the analysis of package power consumption using Intel's telemetry data. It challenges the prevailing belief that hardware choice is the primary determinant of a device's power consumption and instead emphasizes the significant role of user behavior. The paper includes two sections: Exploratory Data Analysis (EDA) and a linear model for power consumption. The EDA section provides valuable insights from Intel's telemetry data, comparing power consumption across countries, with a specific focus on power consumption patterns in the US and China. Our simple linear model affirms those patterns and highlight the possible importance of user behavior and its influence on power consumption. Ultimately, the paper underscores the need to understand power consumption patterns and identifies areas where stakeholders like Intel can make improvements to reduce environmental impact effectively and efficiently.

Problem

• power consumption
• user behavior
• telemetry data
• hardware choice
• energy efficiency

Innovation

• power consumption patterns
• telemetry data
• user behavior
• linear model
• exploratory data analysis