Environmental pollution poses serious threats to ecosystems, human health, and global sustainability, necessitating efficient real-time monitoring solutions. This project focuses on tracking air, water, and soil pollution using advanced sensors. MQ2 and MQ3 sensors detect harmful gases, a turbidity sensor assesses water quality, and soil moisture and temperature sensors monitor soil conditions. The collected data is transmitted to a Raspberry Pi controller, converted digitally via the MCP3008 ADC, and sent to an IoT platform for real-time analysis. This structured approach ensures efficient data management, enabling timely identification of pollution levels. The proposed system efficiently detects pollutants and issues alerts when pollution exceeds critical thresholds, allowing proactive intervention. By leveraging IoT technologies, it provides real-time insights and facilitates pollution prevention strategies. Additionally, integrating sustainable methodologies, such as hydroponic technology, enhances its scalability and cost-effectiveness for large-scale applications. Designed for industrial, urban, and agricultural settings, this model offers a versatile, reliable, and modular solution. Extensive testing has demonstrated its accuracy and effectiveness under various environmental conditions, making it a valuable tool for pollution management and ecological conservation.