Smart Home Data Preprocessing Using Python

Proceedings of International Scientific Conference „ALFATECH – Smart Cities and modern technologies“ (pp. 137-142) 

 

AUTOR(I) / AUTHOR(S): Ana ĐOKIĆ , Hana STEFANOVIĆ and Dragana DUDIĆ

 

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DOI:  10.46793/ALFATECHproc25.137DJ

SAŽETAK / ABSTRACT:

Smart home systems generate large volumes of data from various sensors, such as temperature, humidity, motion, and energy consumption. Effective preprocessing is essential to enhance data quality, reduce noise, and enable accurate analysis. This paper examines Python-based data preprocessing techniques for smart home environments. The preprocessing workflow includes data cleaning, handling missing values, normalization, feature selection, and data transformation. Data cleaning addresses duplicate records, outliers, and inconsistencies, while missing values are imputed using statistical and machine learning approaches. Normalization techniques standardize sensor readings to ensure consistency across data points. Feature engineering and dimensionality reduction refine the dataset for improved predictive modeling. By enhancing data quality, preprocessing contributes to smarter home automation, efficient anomaly detection, and optimized energy management. This study underscores the critical role of preprocessing in smart home analytics, facilitating reliable and meaningful insights for decision-making. The proposed techniques enhance the integration of smart home data into machine learning models, driving advancements in intelligent home automation systems.

KLJUČNE REČI / KEYWORDS:

data preprocessing; Python programming language; smart homes

PROJEKAT / ACKNOWLEDGEMENT:

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