Task Scheduling Algorithm for Power Minimization in Low-Cost Disaster Monitoring System: A Heuristic Approach  
[PERSON]  
1 Department of Information Technology, School of Informatics, Walailak University,  
Nakhon Si Thammarat 80160, Thailand; [EMAIL_ADDRESS] (C.J. ); [EMAIL_ADDRESS] (J.K.); [EMAIL_ADDRESS] (P.K.) 2 Informatics Innovative Center of Excellence (ICE), School of Informatics, Walailak University,  
Nakhon Si Thammarat 80160, Thailand  
3 Faculty of Engineering, Cambodia University of Technology and Science, CamTech Street, Sangkat Prek Tasek,  
Khan Chroy Chongvar, Phnom Penh 121003, Cambodia; [EMAIL_ADDRESS]
* Correspondence: [EMAIL_ADDRESS]  
[PERSON]  
1 Department of Information Technology, School of Informatics, Walailak University,  
Nakhon Si Thammarat 80160, Thailand; [EMAIL_ADDRESS] (C.J. ); [EMAIL_ADDRESS] (J.K.); [EMAIL_ADDRESS] (P.K.) 2 Informatics Innovative Center of Excellence (ICE), School of Informatics, Walailak University,  
Nakhon Si Thammarat 80160, Thailand  
3 Faculty of Engineering, Cambodia University of Technology and Science, CamTech Street, Sangkat Prek Tasek,  
Khan Chroy Chongvar, Phnom Penh 121003, Cambodia; [EMAIL_ADDRESS]
* Correspondence: [EMAIL_ADDRESS]  
[PERSON]  
1 Department of Information Technology, School of Informatics, Walailak University,  
Nakhon Si Thammarat 80160, Thailand; [EMAIL_ADDRESS] (C.J. ); [EMAIL_ADDRESS] (J.K.); [EMAIL_ADDRESS] (P.K.) 2 Informatics Innovative Center of Excellence (ICE), School of Informatics, Walailak University,  
Nakhon Si Thammarat 80160, Thailand  
3 Faculty of Engineering, Cambodia University of Technology and Science, CamTech Street, Sangkat Prek Tasek,  
Khan Chroy Chongvar, Phnom Penh 121003, Cambodia; [EMAIL_ADDRESS]
* Correspondence: [EMAIL_ADDRESS]  
May 19  
obtained from the physical environment [3]. IoT technology also allows remote control of devices, enhancing real-time information about disaster-prone areas. Big data technology enhances the performance of these systems by processing, storing, and analyzing large volumes of data in real time. These data, including environmental and telemetry data, can identify patterns, trigger alerts, inform decision-making processes, and improve machine learning algorithms. Big data enhances disaster monitoring systems by providing real-time insights, efficient decision-making, and improved risk management. IoT devices face resource constraints in memory, computation, low-power radio communication, and power sources. These limitations affect the accuracy and delay of transmitted data and the lifetime of sensor nodes [4]. The software perspective is crucial in designing constraint devices to address these limitations. Low-power operating systems for IoT devices should be designed for task execution [5; 6; 7], and network protocols like Constrained Application Protocol (CoAP) [8], Message Queuing Telemetry Transport (MQTT) [9], or Web-Socket Protocol should be used [10]. The process scheduling technique provides an optimal solution, such as a scheduling a plan based on the directed acrylic graph and quantum particle swarm optimization to optimize energy consumption [11]. The complexity of power consumption and sensor data scheduling in IoT devices encompass both hardware and software challenges. Hardware concerns encompass the optimization of transmit power over time using causal channel state information [12], the management of energy for data sensing in the face of unpredictable energy harvesting [13], and the maximization of environmental sensor coverage while conserving energy [14]. The software focuses on improving data transmission efficiency by using AI-driven decision-making models to minimize redundancy and power consumption [15]. It also includes energy-efficient data acquisition systems considering spatiotemporal data sparsity [13]. Additionally, adaptive sampling methods are developed to conserve energy while maintaining data quality, considering environmental factors such as temperature and humidity [16].