Evaluating IoT Sensor Data Reliability and Fluctuation in Cloud Integrated Systems

This study investigates the consistency and variation of IoT sensor data in a cloud computing context. The findings show that the data collected from sensors is generally consistent with moderate variation and a handful of probable extremes indicating outliers. Humidity is shown to have a greater variation than temperature, which is consistent with the environmental factors involved. The merging of IoT data with cloud processing enables new opportunities for better real-time analytics, scales and detects anomalies with better accuracy of the data and greater system performance. The findings indicate a demand for strong cloud analytics, and outlier handling processes streamlining datasets generated through IoT technology.