Environmental Monitoring using IoT using Ardunio UNO and Data Analysis

The increasing global challenges of resource depletion, and climate change underscore the critical need for robust environmental monitoring. The integration of Internet of Things (IoT) technology has ushered in a new era of Environmental Monitoring (EM), enabling real-time, data-driven insights into air quality, water pollution, and waste management. EM systems leverage sophisticated sensor networks to collect comprehensive environmental data. These sensors, coupled with IoT connectivity, facilitate the transmission of information to centralized platforms for analysis and interpretation. By examining a multitude of research studies, this paper categorizes and evaluates the methodologies and findings related to air monitoring. Key areas of focus include the types of sensors employed, IoT architectures, data processing techniques, and the practical applications of derived insights. Machine learning algorithms are then incorporated to extract valuable patterns from the collected data, enabling predictive modelling, and early warning systems.