Sensor data analysis is a vital part of IoT applications.

Analysis of sensor data in IoT Applications.
Sensor data analysis is a vital part of IoT applications.
From smart greenhouses, swimming pools to industrial automation, the collection and processing of data from sensors leads to critical information and decision making.

Data sources:

Environment: Temperature, humidity, PH, ORP, CO2
Condition: Door/window sensors, smoke detectors.
Function: Liquid level, distance sensors.
Analysis process:

Data collection: Collection of measurements from sensors in real time.
Preprocessing: Data cleaning, homogenization and calibration.
Storage: Store data in databases for history and analysis.
Analysis: Application of statistical methods, machine learning and visualization.
Exceptional Inference: Detecting patterns, predicting future situations, making decisions.
Advantages:

Optimizing operations and resources.
Early problem detection and damage prevention.
Improving security and protection.
Personalized experience for users.
Applications:

Smart homes: Automatic regulation of temperature, lighting, security.
Industry 4.0: Production monitoring, maintenance prediction, process optimization.
Smart cities: Management of traffic, lighting, waste, energy.
Sensor data analysis is a cornerstone for leveraging IoT technology.
The correct processing and analysis of data leads to intelligent and effective solutions in a multitude of fields, improving the quality of life and productivity.