This work investigates the use of a swarm of robots for environmental monitoring in disaster-stricken areas, focusing on critical metrics such as air quality, temperature, and humidity. In this investigation, each autonomous robot is equipped with contemporary sensors that capture data in real time, allowing for a thorough analysis of the impacted area. Using swarm intelligence, the robots work together to adjust their monitoring patterns based on the data they acquire, ensuring optimal coverage and an efficient response to changing conditions. This adaptive method enhances the ability to recognize risky locations and monitor healing actions over time. The autonomous robotic swarm lowers the need for human intervention in hazardous environments, increasing safety and data dependability. Furthermore, the communication between the robots enables dynamic strategy changes, allowing for rapid deployment in a range of disaster scenarios. The research study aims to improve effective decision-making and resource allocation for recovery efforts by using cutting-edge technology, as well as give critical insights into environmental consequences of disasters. Finally, this study provides a scalable and practical approach for continuous ecological monitoring, which represents a significant improvement in the application of robotics for environmental protection and disaster management.