Effective data handling techniques: ensuring quality and efficiency in datasets

The integration of IoT, sensors, and Internet connectivity is essential in meeting diverse real-world challenges in the present era. The scope of applications includes diverse domains such as smart cities, healthcare systems, smart buildings, intelligent transportation, precision farming, and smart environments. Though, real-time IoT device data presents quite a lot of challenges, including an overwhelming volume of noisy data and significant resource consumption costs. This paper focuses on methods for processing of data, integration beside different data sources, and analysis to uncover valuable insights into unknown data patterns, which facilitate fast decision-making. It discusses various data processing methods, including outlier detection, data denoising, data aggregation missing and data imputation. Additionally, that emphasizes importance of outlines, data fusion and different fusion techniques, including Extracting features, declaring identity, fusing data, and applying direct fusion. To conclude, this study represents the first comprehensive examination of processing of data, integration and evaluation.