## 6 Conclusions  
This study introduces a cost-effective IoT-based disaster monitoring system emphasizing the minimization of power consumption. The system employs affordable hardware components, such as the ESP8266 microcontroller, and utilizes solar power for efficient monitoring. Our task scheduling algorithm, which incorporates polling and deep sleep techniques, significantly reduces power consumption, extending IoT devices' operational life through strategic management. This study optimizes energy consumption during the sensing and transmission phases, demonstrating a balance between performance and power efficiency through methodical scheduling and energy-efficient delay techniques.  
This study found promising results but identified several limitations. These include the constraints posed by energy-efficient hardware and sensors, the inability to isolate individual sensor or state power consumption, and the exclusion of the 3G access point power consumption from the analysis. Despite these limitations, the system's resilience and efficiency in crisis scenarios highlight the need for further exploration of adaptive task scheduling and dynamic routing algorithms to overcome resource limitations.  
The proposed low-cost IoT system for disaster monitoring represents a significant advancement towards developing sustainable, energy-efficient solutions for real-time environmental monitoring. Integrating affordable hardware, solar power, and advanced task scheduling algorithms provides a robust framework that can be further refined and expanded to meet the demands of diverse disaster monitoring applications.  
The findings of this study underscore the critical importance of energy-aware design in IoT systems. By demonstrating how strategic task scheduling and energy-efficient techniques can extend the operational life of IoT devices, this research paves the way for future innovations in this vital area. The proposed system offers a practical solution for current disaster monitoring challenges and sets the stage for future advancements in sustainable IoT technology.  
Further research is recommended to address the identified limitations, particularly in enhancing the precision of power consumption measurements and integrating more sophisticated adaptive scheduling algorithms. By continuing to refine and expand upon this framework, future studies can contribute to developing even more efficient and resilient IoT-based disaster monitoring systems, ultimately improving our ability to respond to and manage environmental crises.  
Conceptualization, C.J. and S.S.; methodology, C.J. and S.S.; software, C.J. and S.S.; validation, J.K., P.K. and M.T.; formal analysis, C.J. and P.K.; investigation, J.K.; resources, J.K.; data curation, C.J.; writing--original draft preparation, C.J.; writing--review and editing, S.S. and M.T.; visualization, J.K.; supervision, C.J.; project administration, S.S.; funding acquisition, C.J. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Walialak University's individual research grant (grant number WU66254).  
The raw data supporting the conclusions of this article will be made available by the authors on request.  
The authors declare no conflicts of interest.