For humankind to survive, access to sufficient and safe drinking water is fundamental. This study explores the connection between rising domestic water consumption and planetary phenomena, such as rapid population growth, climate change, and pandemics. To achieve the study’s objectives, it provides a thorough forecast of water use, considering probable global scenarios for the years 2030 and 2050. The modeling approach is adapted from a consistent case study taken from the body of scientific literature on water supply hydraulics. The study’s results highlight the necessity for proactive and flexible management strategies for water resources. Notably, it observes significant alterations in water supply management to adjust water allocation due to the unanticipated and ongoing increase in consumer demand. The forecasted scenarios indicate potential difficulties that may arise in meeting rising domestic water demand amid planetary phenomena. The presented results offer valuable insights to policymakers and water supply authorities, enabling them to effectively address the rising domestic water demand while considering potential adverse conditions, ensuring a sustainable water supply for future generations.

The rapid growth of Internet of Things (IoT) applications is reshaping countless sectors and, in the process, exposing the limitations of existing connectivity solutions—especially in rugged regions like South America’s Andean highlands, where conventional infrastructure networks are scarce. To address this gap, this research introduces an automated system that captures uplink and downlink data from LoRaWAN nodes in real time. The system continuously monitors essential indicators—RSSI, SNR, transmit power, spreading factor, bandwidth, device speed, and packet interval—and stores them for later analysis. Thanks to its modular design, the system adapts easily to urban, semi-urban, and challenging rural topographies. Field trials show that our tool gathers reliable performance data while cutting the time and manual effort typical of traditional measurement campaigns. These results streamline IoT roll-outs in demanding terrain and lay the foundation for scalable LoRaWAN deployments throughout the Andean region.

The increasing adoption of Internet of Things (IoT) devices, coupled with the transition to Industry 4.0, has highlighted the necessity of evaluating LoRaWAN performance in complex geographical environments. This study presents an automated system for assessing LoRaWAN coverage in mountainous regions. The system addresses critical performance parameters such as Received Signal Strength Indicator (RSSI), Signal-to-Noise Ratio (SNR), transmission power, velocity, and data transmission intervals. The proposed methodology integrates qualitative and quantitative approaches in three phases: Analysis, Implementation, and Evaluation. The system is deployed in urban and rural regions of southern Ecuador, where real-time data acquisition enables both uplink and downlink performance assessment. The results demonstrate the feasibility of automating LoRaWAN coverage evaluation, minimizing manual intervention, and enhancing network monitoring efficiency. The findings support the optimization of IoT deployments in challenging terrains, facilitating improved communication reliability and scalability.